these diallo
TRANSCRIPT
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Doctor of Science ThesisUPMC Sorbonne Universites
Specialization
COMPUTER SCIENCE
presented the 7th march 2013 by
Mr. Mohamed BOBO DIALLO
Submitted in partial satisfaction of the requirements for the degree of
DOCTOR OF SCIENCE of UPMC Sorbonne Universites
Content-based Networking forGlobal Scale Mediation Services
Commitee in charge:
Serge FDIDA Advisor Professor, UPMC Sorbonne universites { Paris 6
Promethee SPATHIS Advisor Associate Professor, UPMC Sorbonne universites { Paris 6
Walid DABBOUS Reviewer Researcher, INRIA Sophia Antipolis
Farouk KAMOUN Reviewer Professor, SESAME
Paul MOCKAPETRIS Examiner Nominum
Sebastien TIXEUIL Examiner Professor, UPMC Sorbonne universites { Paris 6
Kave SALAMATIAN Examiner Professor, Universite de Savoie
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Doctor of Science ThesisUPMC Sorbonne Universites
Specialization
COMPUTER SCIENCE
presented the 7th march 2013 by
Mr. Mohamed BOBO DIALLO
Submitted in partial satisfaction of the requirements for the degree of
DOCTOR OF SCIENCE of UPMC Sorbonne Universites
Content-based Networking forGlobal Scale Mediation Services
Commitee in charge:
Serge FDIDA Advisor Professor, UPMC Sorbonne universites { Paris 6
Promethee SPATHIS Advisor Associate Professor, UPMC Sorbonne universites { Paris 6
Walid DABBOUS Reviewer Researcher, INRIA Sophia Antipolis
Farouk KAMOUN Reviewer Professor, SESAME
Paul MOCKAPETRIS Examiner Nominum
Sebastien TIXEUIL Examiner Professor, UPMC Sorbonne universites { Paris 6
Kave SALAMATIAN Examiner Professor, Universite de Savoie
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Remerciements
Je remercie Serge Fdida qui a rendu possible la redaction de ce manuscrit.Je remercie Promethee Spathis qui m'a ouvert les portes du Lip6.Ensuite, je remercie ma famille qui m'a soutenu dans les moments diciles.Puis, je remercie chacun pour son aide la plus inme. Je pense a Mubashir, Minh,
Marguerite, Konstantin, Pierre-Emmanuel, Nicolas, Vasilis, Vincent, Mehdi, Youcef, Abdouet les autres.
Louange a Dieu le ma^tre du possible.
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Abstract
Online information consumers are increasingly overwhelmed by the volume of informationavailable at global scale. As such, they have been privileging mediation services deliveringonly those publications relevant to their registered information interests. This includesaggregators, syndication and alerting services. We envision an infrastructure realizingglobal scale mediation between information providers and information consumers calledthe mediation network. Realizing such infrastructure raises several requirements. First,decentralization is an essential feature for the mediation network to be sustainable. Second,information consumers should register their interests according to expressive subscriptionlanguages. Third, it is desirable that the service integrates the search, content retrieval anddissemination activities. Finally, achieving communication-eciency is important, giventhe scarcity of end-to-end bandwidth and the huge volume of information available at largescale.
Content-based networking (CBN) is an appealing technology to provide ecient dissemi-nation channels to information providers to reach information consumers in a decentralizedand loose coupled manner. It supports naturally expressive subscription languages. Ex-isting CBN proposals support an exhaustive ltering semantic, i.e. a consumer registeringits interests will receive all the corresponding matching publications. Such semantic isappropriate for a wide range of applications including distributed games, stock quote ormonitoring applications. However, for applications such as news distribution or contentsharing, the amount of relevant publications available at global scale may be overwhelmingas information consumers have limited attention span. Implementing the same exhaustiveltering semantic for these applications would result in a huge information overload andcommunication overhead.
We extend CBN by dening a new service model supporting both content retrieval anddissemination trac, but also quantifying information consumers' attention capabilities inorder to address the information overload. Secondly, we dene the e-CBN framework whichaddresses the key design issues in implementing eciently the service model. Thirdly, wedescribe and discuss the results of extensive simulations that we led in order to quantifythe gains of the framework over baseline CBN as well as quantify the gains introduced byeach of the component of the framework. Finally, we conclude the thesis with perspectivesand open research problems.
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Key Words:
Content-based networking, publish/subscribe, content distribution.
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Table of contents
1 Introduction 15
1.1 Context . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
1.2 Problem statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
1.3 Contributions of the thesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
2 The E-CBN framework for extreme-scale content-based networking 21
2.1 Content-based networking (CBN): Overview . . . . . . . . . . . . . . . . . . 22
2.2 e-CBN: An enhanced service model for extreme scale content-based networking 24
2.3 e-CBN: Architecture and mechanisms . . . . . . . . . . . . . . . . . . . . . . 27
2.3.1 Router model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
2.3.2 Caching policies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
2.3.2.1 Selection and replacement policies . . . . . . . . . . . . . . 31
2.3.2.2 Caching policies . . . . . . . . . . . . . . . . . . . . . . . . 33
2.3.3 Interest forwarding . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
2.3.4 Dissemination strategies . . . . . . . . . . . . . . . . . . . . . . . . . 34
2.3.4.1 Pull/delayed push (PDP) . . . . . . . . . . . . . . . . . . . . 35
2.3.5 Publication forwarding . . . . . . . . . . . . . . . . . . . . . . . . . . 36
2.3.6 Forwarding optimizations . . . . . . . . . . . . . . . . . . . . . . . . 38
2.3.6.1 Congestion-aware forwarding . . . . . . . . . . . . . . . . . 38
2.3.6.2 Handling duplicate responses . . . . . . . . . . . . . . . . . 38
2.4 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
3 Evaluation 41
3.1 Workload characterization . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
3.1.1 On the relevance of workload modelling . . . . . . . . . . . . . . . . 42
3.1.2 Evaluation methodology . . . . . . . . . . . . . . . . . . . . . . . . . 43
3.2 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
3.3 Caching policies evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
3.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
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4 Conclusion 554.1 Summary of contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 564.2 Originality of the contributions . . . . . . . . . . . . . . . . . . . . . . . . . 574.3 Open Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
List of gures 61
List of tables 63
References 67
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14
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Chapter1Introduction
Contents
1.1 Context . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
1.2 Problem statement . . . . . . . . . . . . . . . . . . . . . . . . . . 19
1.3 Contributions of the thesis . . . . . . . . . . . . . . . . . . . . . . 20
15
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16 1.1. CONTEXT
1.1 Context
The reference Internet model was adequate in the early days of the web, when information
consumers' behavior consisted in browsing a repository of web documents and fetching the
rare HTML pages of interest. Nowadays, information consumers' attention span does no
longer follow the pace of relevant information generated online at global scale and most
of them are privileging aggregators, as well as services enabling personalized delivery of
information by ltering the stream of online content according to consumer preferences at
various granularity (channel, topic or content). This includes content syndication services
enabled by the RSS [Boa07] and ATOM [NS05] standards, as well as alerting services [ale],
which enable consumers to keep abreast of the latest news related to an aair, an individual
or a subject, or to be notied of updates on specic channels or feeds. Additionally, an
increasing number of users are privileging attractive services such as Miro [mir] to access
online video, which seamlessly integrates search, pre-fetching and downloading functional-
ities, and provides access to a large number of online video stores and TV channels.
Handling old and new trac patterns in the current Internet involves several layers
of indirections including DNS resolution, which may become a bottleneck, if improperly
engineered. Moreover, trac crossing the middle mile of the Internet usually suers from
signicant delays and losses [Lei09]. As a consequence, caching proxies, DNS caching and
content distribution networks (CDN) have emerged as solutions of choice in order to meet
the requirements of content-related applications at global scale.
To fulll data-intensive applications needs, the receiver-driven approach has been re-
cently introduced. This approach is in contrast with the historical Internet model which
relies on host reachability. The receiver-driven approach instead focuses on content de-
livery given predened consumer requirements resulting in the choice of stateful switches
and in-networking caching. In fact, it has been argued that extending routers with caching
resources would eliminate the redundancy existing in the Internet trac [AGA+08]. In this
context, the ow of data is implicitly steered according to receivers' registered interests,
rather than explicitly relying on the binding of the corresponding data objects to their host
location. Data objects are directly addressed through names, which may oer dierent lev-
els of expressiveness. Several architectures have emerged under the banner of information-
centric networking as a consensus label in the research community working on receiver-
driven architectures for global communications [NBEK+] [FTP09] [JST+09] [CPW11].
We believe that the Next Generation Internet (NGI) will provide a substrate supporting
several communication architectures, including TCP/IP. It will enforce isolation, as well as
interoperability depending on stakeholders policies. The NGI will involve network operators
participating in the basic substrate, and virtual operators deploying and managing global
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CHAPTER 1. INTRODUCTION 17
communication networks. Experimentation platforms such as GENI [BFH+06], ONELAB
[FFM10] and openflow [MAB+08] are already implementing part of this vision. Competing
receiver-driven architectures should demonstrate strong incentives for adoption by virtual
network operators and users as well as achieve satisfying performances.
To be successful in providing eciently global scale mediation services meeting users'
expectations receiver-driven architectures should meet two additional requirements. First,
they should provide an integrated service supporting the search, retrieval, and dissemi-
nation activities and supporting expressive subscription languages and rich metadata for
content description. In fact, rich metadata are more and more used to improve search
quality [cal]. Second, they should be decentralized. Decentralization is an incontrovertible
requirement for mediation services to sustain at global scale. Existing mediation services
operate as centralized or two-tiers systems operating over clusters of thousands of com-
puters to satisfy global scale workloads and consumer requirements. Nowadays, large-scale
distributed applications are usually deployed over clusters of computers. However, cluster
sizes are often limited by practical constraints such as power supply, cooling and switch-
ing technology limitations. For instance, it has been estimated that information retrieval
systems would require at least 30 clusters of 50000 computers by 2010 to operate, which
is obviously not sustainable [BYCJ+07]. Also, information consumers are more and more
scared about the big brother scenario emerging from the situation of monopoly of major
search engines such as Google, Bing or Yahoo.
Among emerging receiver-driven architectures, content-based networking (CBN)] [cbn]
enables receivers to register their information interests according to expressive subscription
languages and be notied with matching publications. Moreover, CBN implements a decen-
tralized content-based publish/subscribe (CBPS) [CS04] communication model and provides
ecient dissemination channels for a wide range of applications such as distributed games,
stock quote or monitoring applications. This thesis focuses on extending baseline content-
based networking (CBN) with the ability to meet large scale deployments characterized by
a large number of widely spread consumers with heterogeneous requirements, the scarcity
of end-to-end bandwidth and the information overload.
Publish/subscribe communications involve subscribers or receivers registering informa-
tion interests, and publishers or senders publishing information. The purpose of a pub-
lish/subscribe system is to mediate between subscribers and publishers by guaranteeing
the timely delivery of relevant publications to receivers. Publish/subscribe communica-
tions have been categorized according to the expressiveness of the subscription languages
in channel-based, topic-based and content-based publish/subscribe.
In channel-based publish/subscribe systems, subscribers subscribe to notications on
specic feeds or channels. A channel or feed is a localized source of information typically
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18 1.1. CONTEXT
identied by an URL. In common implementations of channel-based publish/subscribe sys-
tem, subscribers poll the publishers to know whether new publications are available. This
polling behavior generates much overhead for the network that have been addressed by
many work. RSS cloud is an optional sub-element of the RSS protocol's channel element
that enables realtime push notications for feeds. This is done using a cloud element al-
lowing a software service to register with a cloud which noties subscribers of updates to
the channel. RSS cloud is not limited to RSS feeds but can also be used with other feed
formats such as ATOM. Another protocol superseding the default polling behavior of RSS (or
ATOM) is the pubsubhubbub protocol [pub]. In pubsubhubbub, a subscriber initially polls
the RSS (or ATOM) feed in the conventional way, i.e. by requesting it from the feed server.
The subscriber then inspects the feed, and if it references a hub, the subscriber can sub-
scribe to the feed URL topic on that hub. The subscriber runs a server so that hubs can
directly notify it when any of its subscribed topics have updated. Publishers expose their
content as RSS (or ATOM) feeds, but with the inclusion of hub references. They post notica-
tions to those referenced hubs whenever they publish something. Thus, when a publication
event occurs, the publisher calls its hubs and the hubs call their subscribers [wik]. Also,
FeedTree [SMPD05] and Corona [RPS06] are peer-to-peer systems for distributing Web
feeds faster and with lower bandwidth requirements for publishers. Instead of polling feeds
independently, FeedTree and Corona users cooperate to share feeds updates [wik].
In topic-based publish/subscribe systems [CMTV07] [PRGK09] [BBQ+07] [RKCD01],
messages are published on abstract event channels called topics. Users interested to receive
messages published on certain topics issue subscribe requests specifying their topics of
interest. Then, the publish/subscribe infrastructure guarantees to distribute each newly
published message to all the users that have expressed in the message's topic [CMTV07].
The notion of topic is very similar to the notion of group. Consequently, subscribing to a
topic T is equivalent to becoming a member of group T and publishing a message on topic
T can be viewed as broadcasting the message among the members of group T [EFGK03].
Content-based publish/subscribe [CS04] [CRW00] [CRW03] [AT10] [GSAA04] [MSRS09]
[CCP08] provides a ner granularity, enabling subscribers to issue predicates on publica-
tion message's content. Content-based publish/subscribe is more dynamic and expressive
than topic-based publish/subscribe. The expressiveness of content-based publish/subscribe
should be traded against increased complexity. Content-based publish/subscribe solutions
operate acoording to two modes: (1) ltering, and (2) rendezvous based [BV05]. When
ltering applies, the brokers determine the next hop(s) in the delivery tree of a message
M on a hop-by-hop basis by evaluating M against the subscription forwarding table which
aggregates the set of advertised subscriptions. When the publish/subscribe system oper-
ates as a rendezvous network, it is either based on distributed hash tables (DHTs) or on
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CHAPTER 1. INTRODUCTION 19
dynamic partitioning of the event space among a set of brokers. Content-based networking
is an attempt to implement ltering-based content-based publish/subscribe as a network
level communication service.
1.2 Problem statement
Existing content-based networking schemes [CRW04] [CRW06] are designed to eciently
implement an exhaustive ltering semantic (or simply exhaustive semantic), which is ap-
propriate for many notication services. For instance, in sensor network applications, a
sink or receiver subscribing to an event such as, the temperature monitored by any sensor is
larger than a given threshold, is interested in every occurrence of that event. Consequently,
it is necessary to advertise subscriptions in the mediation network using ooding mecha-
nisms in order that any event matching a set of interests be notied to the corresponding
receivers, ideally, through a spanning tree rooted at the source of that event.
However, in many application scenarios, information consumers have a limited atten-
tion span and are in most cases interested in few responses relevant to their information
interests. In fact, with the globalization of the Internet, consumers are overwhelmed by
the huge volume of information accessible. This situation which has been popularized by
the futurologist Alvin Toer [Tof84], as information overload, has fostered the emergence
of mediation services capturing consumers' attention span in order to deliver only the
estimated most relevant content to them. Several online alerting services already enable
information consumers to keep abreast of the latest news related to a topic, a personality or
a real-world event. An example of such services is Google alerts [ale], which provides an
interface allowing consumers to personalize their alerts in terms of frequency (immediately,
daily, weekly) and volume (exhaustive search or ranked search) of notications.
Content-based networking is an appealing technology for dissemination services and
implementing the exhaustive semantic in scenarios where consumers register their infor-
mation interests jointly with a quantication of their attention span is not incongruous.
In fact, one can imagine solutions where ranking functions would be executed at the edge
of the network in order to display only the most relevant publications tting consumers'
attention span. However, devising ranking functions for decentralized content-based pub-
lish/subscribe (CBPS) is questionable, since matching consists in assessing a predicate
against meta-data describing available content according to an exact semantic and as such
diering from the behavior of search engines which help users locate a needle in a haystack.
Consequently, implementing the same exhaustive semantic in presence of information over-
load, would generate more trac than necessary to satisfy consumers.
Shifting from the exhaustive semantic towards a service model quantifying consumers'
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20 1.3. CONTRIBUTIONS OF THE THESIS
attention capability, opens new opportunities to reduce the amount of trac carried by
content-based networks. Reducing the amount of trac necessary to satisfy each interest,
will reduce congestion in the network and increase the probability to timely satisfy sub-
scriptions. Moreover, it is important that content-based networking technology captures
the qualitative heterogeneity of information consumers that are not interested in future
publications only, but in publications immediately available as well. This will only increase
the attractiveness of content-based networking technology, given that the larger the number
of users, the larger online mediation services will make revenue through advertising.
1.3 Contributions of the thesis
This thesis introduces the e-CBN framework which extends baseline content-based network-
ing with the ability to meet the requirements of global scale mediation services, namely
large number of widely spread information consumers, information overload, and scarcity
of end-to-end bandwidth. e-CBN denes a generic service model supporting both content
retrieval and dissemination trac, and capturing information consumers' attention capa-
bility in order to address the information overload. Additionnaly, e-CBN leverages caching
in order to increase content availability, and denes the protocols required to eciently
implement the service model (Chapter 2). A characterization of the framework under re-
alistic workload assumptions reveals that e-CBN drastically improves performances for a
wide range of congurations (Chapter 3).
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Chapter2The E-CBN framework forextreme-scale content-basednetworking
Contents
2.1 Content-based networking (CBN): Overview . . . . . . . . . . . . 22
2.2 e-CBN: An enhanced service model for extreme scale content-based networking . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
2.3 e-CBN: Architecture and mechanisms . . . . . . . . . . . . . . . . 27
2.3.1 Router model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
2.3.2 Caching policies . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
2.3.3 Interest forwarding . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
2.3.4 Dissemination strategies . . . . . . . . . . . . . . . . . . . . . . . . 34
2.3.5 Publication forwarding . . . . . . . . . . . . . . . . . . . . . . . . . 36
2.3.6 Forwarding optimizations . . . . . . . . . . . . . . . . . . . . . . . 38
2.4 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
21
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22 2.1. CONTENT-BASED NETWORKING (CBN): OVERVIEW
This chapter describes a framework for extreme scale content-based networking charac-
terized by the heterogeneity of information consumer requirements, the information over-
load and the scarcity of end-to-end bandwidth. The framework introduces a service model
which captures the quantitative and qualitative heterogeneity of information consumer
needs, and addresses the key design issues in implementing eciently the service model at
extreme scale.
Mediation network
Interests
Publications
Broadcasters/PublishersInformation consumers
provider 2 provider 1
provider 3provider 4
Channel providers
Figure 2.1: Mediation network
2.1 Content-based networking (CBN): Overview
Content-based networking(CBN) involves three types of entities: subscribers, receivers
or information consumers, publishers or information providers and routers or brokers.
Each receiver submits its interests by sending a subscription to the network where
routers acting as proxies are responsible for returning the corresponding matching
pieces of data. The rst router to handle the subscription advertised by a receiver,
i.e. one of the proxy mentionned above, is called a home router. Note that receivers
select their home routers on the basis of trust or proximity. Publishers upload their
publications so that they can be disseminated to interested receivers. A publication
consists of a data item and a metadata description, while an interest is described
by a predicate over the metadata space. Predicates and metadata typically follow
an attribute/value schema. A publication P matches a subscription S, whenever
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CHAPTER 2. THE E-CBN FRAMEWORK FOR EXTREME-SCALECONTENT-BASED NETWORKING 23
the metadata describing P matches the predicate dened by S. Routers cooperate to
eciently and reliably disseminate data items corresponding to uploaded publications
towards interested receivers.
Content-based forwarding (CBF) is the algorithm that based on the information es-
tablished by the routing algorithm, processes incoming messages to decide on which
interface an incoming message should be forwarded. That information is compiled in
the forwarding table which associates each interface to a lter combining the pred-
icates of the descendants in the dissemination tree via that interface. We dene a
lter as a compact representation of a set of predicates. Ecient data structures
for forwarding tables are mentioned in [CW03] [TK06]. Carzaniga et al. [CRW06],
describes two content-based forwarding schemes requiring a spanning tree rooted at
each sender that can be congured through shortest-path trees or reverse-path for-
warding. However, these CBF schemes are correct only if spanning trees verify the
all-pairs path symmetry property, i.e. only in the case where shortest-paths are unique
or routes between routers are symmetric. In practice, it is dicult to enforce such
properties. Consequently, the deployment of such protocols is realistic only atop a
global spanning tree.
In order to reduce the complexity of content-based forwarding protocols, which re-
quires evaluating publications against the index of advertised subscriptions at every
hop of the dissemination tree, other work have proposed to implement matching only
at the publishing brokers and switching at subsequent brokers of the disseminaton
tree on the basis of explicit forwarding directives. For instance, the DV/DRP proto-
col [HCW+06] is proposed with an optimization which consists in doing matching
only at the source of publications and appending a particular structure which identi-
es the recipients of the message. When a message has to be pushed on two or more
interfaces, the destination set structure is aected before being attached to the mes-
sage and forwarded to the destinations downstream each interface. However, DV/DRP
uses a compact bit vector data structure to address the message, whose size equals
the number of sink nodes in the system. This assumes a small number of potential
receivers and is thus not scalable. Similarly, LIPSIN [JZER+09] is a forwarding proto-
col that encodes dissemination trees in message headers as bloom lters and achieves
line-speed forwarding. However, LIPSIN requires that each link of the topology be
assigned an identier and requires either a separation of the control plane from the
forwarding plane or/and that each router has a global overview of the topology.
Content-based routing (CBR) is the distributed algorithm that collects, propagates and
assembles receivers' interests as well as topological information to the router for-
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242.2. E-CBN: AN ENHANCED SERVICE MODEL FOR EXTREME SCALE
CONTENT-BASED NETWORKING
warding functions. Existing content-based routing (CBR) [CS04] [CCP08] [CRW06]
schemes are designed to support an exhaustive semantic where receivers register for
all relevant publications matching their interests. Typically, routing consists in broad-
casting subscriptions within the network in order to congure the dissemination tree
required to eciently forward publications from senders to receivers. Content-based
routing requires a broadcast layer for operation on top of arbitrary topologies, which
can be implemented through spanning trees.
2.2 e-CBN: An enhanced service model for extreme scale content-based networking
We consider a mediation network constituted of routers or brokers, involving independent
stakeholders, interconnected according to an arbitrary topology that captures the specic
features of content networks, and that provides ecient dissemination channels for infor-
mation providers to reach information consumers at global scale.
Information providers (or publishers) upload their publications to the mediation net-
work so that they can be disseminated towards interested receivers. We assume that author-
itative publishers upload publications once to the mediation network and each publication
is assigned a unique identier. The purpose of restricting publications to authoritative
publishers is to guarantee that two publications with dierent identiers embed dierent
content.
A receiver r advertises its information needs to its home router R, as a subscription
S (predicate, max, lifetime, freshness) where predicate denes its information interest,
max species the maximum amount of publications admissible by r over a period of time
lifetime, and freshness the maximum age for a relevant publication matching the infor-
mation interest. The age of a publication is the elapsed time since its initial upload in the
mediation network. S is constituted of more attributes which are introduced throughout
the chapter.
A publication P matches a subscription S, whenever the metadata describing P matches
the predicate dened by S and the age of P is less than freshness at the end of the service
period. Routers cooperate to eciently disseminate data items corresponding to uploaded
publications towards receivers which have advertised relevant interests.
We will refer to max as the selectivity of the subscription and lifetime can be in-
terpreted as the delay allocated by receivers to the content-based network to satisfy an
interest. The content-based network delivers to receiver r (via home router R), at most
max relevant publications before lifetime expires. Depending on r preferences, content
delivery is either performed in real-time or delayed until lifetime expires at the latest or
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CHAPTER 2. THE E-CBN FRAMEWORK FOR EXTREME-SCALECONTENT-BASED NETWORKING 25
until r requests the publications retrieved on its behalf by R. This latter possibility re-
quires to provision a minimum amount of caching resources at home routers, but provides
further temporal decoupling between receivers and their home routers allowing temporary
disconnections of the receivers.
These two variants are depicted by Fig. 2.2. Content delivery from home routers to
receivers require that the former maintain some states regarding their registered customers.
For the sake of clarity, we assume that retrieved publications are delivered to receivers in
real-time.
Receiver Home router
subscribe(predicate, max, lifetime, freshness)
deliver(pub1)
deliver(pubmax)
...
refresh(predicate, max, lifetime, freshness)
lifetime
(a) Real-time content delivery
Receiver Home router
subscribe(predicate, max, lifetime, freshness)
pub1 available
pubmax available
...
refresh(predicate, max, lifetime, freshness)
lifetime
consume
deliver(pub1,...,pubmax)
(b) Delayed content delivery
Figure 2.2: Interactions between receivers and home routers
The service model described above captures the attention span of information consumers
by allowing them to specify the maximum amount of relevant information they would like to
receive over a period of time. Also, it captures the qualitative heterogeneity of information
consumers at global scale.
When freshness equals zero, the interest has the conventional semantic of a subscrip-
tion, i.e. the interest selects only future publications. When freshness and lifetime are
both positive, the interest is a loose subscription which diers from a conventional sub-
scription by the fact that requesters are only interested in publications that they did not
consume previously. Loose subscriptions can be refreshed after lifetime expires. Then,
the system guarantees to the requester that the refreshed subscription is not satised with
previously delivered publications. Finally, in the case where lifetime equals zero, then the
interest is non-persistent, i.e. a request to the mediation network to retrieve immediately
up to max available publications. Table 2.2 provides typical parameter settings for various
applications.
This thesis focuses on the ecient processing of loose subscriptions which have not
been previously studied in the literature. Ecient processing of non-persistent interests
(resp. subscriptions) in an unstructured overlay have been largely studied [YGM02] (resp.
[CRW04] [CRW06]) and previous work can be leveraged. Note that within the framework,
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262.2. E-CBN: AN ENHANCED SERVICE MODEL FOR EXTREME SCALE
CONTENT-BASED NETWORKING
Application predicate selectivity lifetime freshness
Notication services (terms="RER+C+Infos") all 7 days 0
News alerting services (type=article, terms="election+2012") 10 24h 24h
Content retrieval (type=article, terms="sophia+perennis") all 24h any
Table 2.1: Examples of interests for dierent applications
non-persistent interests can be processed similarly to loose subscriptions advertised with a
very small lifetime.
Loose subscriptions (freshness > 0 and lifetime > 0)
Non persistent interests (lifetime = 0)
Subscriptions (freshness = 0)
Lifetime
Freshness
Lmax
Fmax
0
Figure 2.3: Illustration of the dierent semantics of the service model
Receivers are allowed to refresh their interests (loose subscriptions) when they expire.
As such, an important requirement for the usability of the service is dened as follows:
Req. 1 The service should guarantee that a refreshed interest will be satised at most once
by any publication over its successive lifetimes. This condition should be enforced without
having to track an exhaustive history of all interests satised with a publication or of all
publications already consumed by a subscription.
To allow routers to dierentiate refreshed interests from new ones, we assume the ex-
istence of an agreement between routers and receivers for such purpose. Control messages
exchanged by routers to advertise interests include a refresh ag indicating whether inter-
ests are refreshed or not (see Fig. 2.7).
Denitions 1 Let S(predicate;max; lifetime; freshness) be a subscription registered at
t0 issued by r, NS be the number of publications notied to r by t0 + lifetime and MS be
the total number of publications uploaded between t0 and t0 + lifetime and matching S.
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CHAPTER 2. THE E-CBN FRAMEWORK FOR EXTREME-SCALECONTENT-BASED NETWORKING 27
DPT
OPT
PPT
caching memory
index
forwarding table
PITcache indexes
Boxes table
(Subscribers preferencesand monitoring data)
PIT: Pending interest table
DPT: Disseminated publication table
PPT: Pending publication table
OPT: Overflowing publication table
Buffer
Figure 2.4: Broker model
S is satised when:NS = max: (2.1)
Starvation happens when:NS < max MS (2.2)
Starvation occurs due to congestion or due to the service failing to timely satisfy inter-
ests. The starvation probability, i.e. the frequency of occurrence of starvation, is the metric
used to characterize the quality of service oered by an implementation of the service model
compared to an implementation of the exhaustive ltering semantic. Starvation does not
account for interests which are not satised due to content unavailability.
Problem statement: We aim at minimizing with a low state complexity,the starvation probability and the communication costs required to sat-isfy a workload of loose subscriptions assuming bandwidth, storage andprocessing resource constraints.
2.3 e-CBN: Architecture and mechanisms
In order to implement the service model introduced previously in this chapter, the e-CBN
framework addresses the following design issues :
-
28 2.3. E-CBN: ARCHITECTURE AND MECHANISMS
PPT
OPTforward garbage
DPT
()
()
()
()
()
()
(): Publication selected by local interest. Enable DF.
(): Publication selected by remote interest and DF is disabled.
(): Publication selected by remote interest.
(): Publication selected by local interests.
(): Publication selected by any interest.
(): Publication selected by a remote interest and DF is enabled.
Figure 2.5: Publication lifecycle inside a broker B
Content forwarding schemes supporting both content retrieval and dissemination traf-
c. Content dissemination trac should be handled by leveraging existing content-
based forwarding schemes. Integrating content retrieval and dissemination in the
same middleware is not straightforward. An important requirement is the ability to
take into account bandwidth and resource constraints by assigning priorities to tran-
siting content. Such forwarding algorithms should minimize starvation in presence of
congestion.
Dissemination strategies dening the conditions making a publication eligible for dis-
semination towards interested receivers. Our service model requires strategies pacing
the dissemination process to information needs.
Interest forwarding strategies necessary to support content forwarding schemes and
dissemination strategies that should take advantage of locality in content availability
patterns as well as attention span quantication in order to minimize communica-
tion costs, unlike existing content-based routing schemes that broadcast subscription
messages to satisfy an exhaustive ltering semantic.
Caching policies increasing content availability as well as communication-eciency.
2.3.1 Router model
The model of a broker is depicted by Fig. 2.4. Each broker needs the following data
structures to operate:
-
CHAPTER 2. THE E-CBN FRAMEWORK FOR EXTREME-SCALECONTENT-BASED NETWORKING 29
matchforward
P
()
()
()
()
()
PPT: pending publication table
DPT: disseminated publication table
OPT: overflowing publication table
PPT
OPT
DPT
()
()
()
()
()
()
represents exclusive transitions
ending
! : P is a publication requested by B and used to satisfy local interests.
! ! : P is a transiting publication that matches interests advertised by downstream brokers/receivers while the NRT policy is enabled or whileB is a recipient of the publication and PF disabled or P is an uploaded publication matching local and remote interests.
! : P is an uploaded publication matching local interests or no interests.
! ! : P is an uploaded publication selected by remote interests only or P is a transiting publication matching remote interests only, while theNRT policy and PF are enabled.
! : P is a transiting publication with PF enabled matching no interest in the table while the NRT option is enabled or matching already satisedlocal interests.
Figure 2.6: Caching and forwarding decisions inside a broker B
Pending interests table (PIT), which is constituted of an index of interests advertised
to this router and a forwarding table which provides information about the origin of
the interest. The index supports a matching method which provides the identiers of
the interests matching a given publication and the forwarding table associates interest
identiers to the originating broker. We assume that once an interest is satised, the
corresponding home router removes the interest states from the PIT.
Pending publications table (PPT) references pending publications, which have just been
uploaded at some router from publishers and that are waiting for opportunities to be
further disseminated i.e. which have not been used to satisfy remote interests. Pend-
ing publications are referenced in the PPT. A pending publication may have been used
to satisfy interests, which are local to a router. In order to avoid that refreshed in-
terests consume the same publication at their home router, we add a dispatched ag
(DF) in the PPT indicating whether a pending publication has been used to satisfy
local interests or not. Note as well that when a publication is disseminated for the
rst time, it is forwarded with the pending ag (PF) enabled, except when the PDP
option is used (See section 2.3.4.1).
-
30 2.3. E-CBN: ARCHITECTURE AND MECHANISMS
predicate
max
lifetime
freshness
identifier
refresh flag
metadata
identifier
pending flag
payload data
Interest message Publication message
nonce
score
in reply of: interest identifier
The timestamp of an interest message is used to compute the validity of an interest and the timestamp in publication messages is used to compute the age of apublication. Interest messages may include also the origin of the message but this is considered as an implementation detail.
Figure 2.7: Interest and publication messages structure
Overowing publications table (OPT) references overowing publications, which have
been disseminated to remote subscribers, but that never served locally. In fact, they
may be useful for refreshed interests in future lifetimes. New entries are added to
the OPT for pending publications selected by remote interests with dispatched ag
DF disabled and for publications incoming with pending ag PF enabled without
satisfying local interests. The latter situation occurs whenever the content-based
network returns more publications than requested or the states corresponding to
an interest are still in the forwarding table or the en-route caching optimization is
enabled (See Section 2.3.2.2).
Disseminated publications table (DPT) references publications which have been dis-
seminated towards remote routers and used to satisfy local interests.
Boxes table (BT), which references abstractions called box, which are used to keep the
preferences of the consumers as well as to monitor the service oered to them. For
instance, brokers will use boxes to monitor the set of publications selected to satisfy
local interests during their lifetime and use that information to detect duplicates.
Also, they will use the boxes to detect that interests are satised and stop advertising
them in their PIT and optionally advertise overload for that interest in the mediation
network (See Section 2.3.4).
Buers upstream and downstream the forwarding decision modeling the two bottlenecks
of the brokers. The rst bottleneck is related to the matching method of the PIT and
the second bottleneck is related to the transmission of publications (Fig. 2.6).
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CHAPTER 2. THE E-CBN FRAMEWORK FOR EXTREME-SCALECONTENT-BASED NETWORKING 31
The cache indexes introduced above have been designed to eectively support Req. 1,
while maximizing opportunities to satisfy refreshed interests. Fig. 2.5 depicts the lifecycle
of a publication inside the cache of a broker i.e. the transitions between the indexes. Fig.
2.6 depicts the processing of an incoming (uploaded or transiting) content by a broker.
Besides the new/refreshed classication, from the perspective of a broker, a remote interest
denotes an interest advertised by downstream brokers, while a local interest denotes an
interest registered by a local receiver.
2.3.2 Caching policies
We assume that brokers are provisioned with a nite amount of caching resources. One
might argue that it is always possible to extend brokers caching resources by distributing
broker behaviors over a cluster of COTS servers as performed today by major online service
providers. In practice, the size of a cluster is limited by practical reasons such as the lack
of space or some energy considerations. Also, the size of the cache impacts the size of
the cache indexes which should ideally t into main memory1. Consequently, beyond some
amount of caching resources, it may be necessary to partition the cache indexes over several
nodes. But, the response time of every broker to satisfy an interest will increase with the
number of nodes involved in the processing and may impact timely delivery of content.
A publication incoming at a brokerB and originating from a receiver or another broker is
cacheable whenever, B is the broker that originally advertised the interest(s) that triggered
the retrieval/dissemination of the content in the mediation network, or B is the broker
where the publication is originally uploaded or, B is allowed to opportunistically cache
transiting publications i.e. when the en-route option introduced in Section 2.3.2.2 is
enabled.
2.3.2.1 Selection and replacement policies
Each router executes a selection policy to determine which publication to select rst to
satisfy an incoming interest, and a replacement policy to determine which publication to
replace rst in case of cache overow. Ideally, selection and replacement policies should
achieve an optimal trade-o between the following tussles: receivers privileging fresh infor-
mation, publishers wanting to reach the widest possible audience with their publications
and network operators willing to minimize communication costs and maximize the quality
of service oered to consumers.
Selection policies should guarantee that new interests are satised with any available
publication, while refreshed interests are served only with publications that have not been
1A common assumption in Information retrieval research
-
32 2.3. E-CBN: ARCHITECTURE AND MECHANISMS
delivered to them during previous lifetimes. In order to be consistent with Req. 1, refreshed
interests should not be satised with publications indexed in DPTs or in OPTs of remote
routers. More precisely, refreshed interests are satised rst with overowing and pend-
ing publications available at the originating router with DF disabled, then with pending
publications available at remote routers of the network.
Consequently, new interests have more opportunities to be satised than refreshed ones.
We can increase content availability for refreshed interests by making pending publications
more persistent. At high-level, selection and replacement policies may discriminate or not
publications according to their type (disseminated, pending, overowing).
We consider two high-level discriminating policies simply called discriminators:
DPF (disseminated publications rst), which returns rst disseminated publications,then overowing and nally pending ones.
PPF (pending publications rst), which returns rst pending publications, then over-
owing and nally pending ones.
We note discriminator-selection policy/discriminator-replacement policy the combination
of policies executed by a broker. The rst discriminator in the notation applies to the
selection policy and the second one applies to the replacement policy. In the case where
no discriminator applies, the discriminator eld of the notation and the following dash are
left blank.
Selection and replacement policies should be designed/chosen in order to balance the
trade-o between new and refreshed interests as well as to meet the expectations of infor-
mation consumers, information providers and network operators:
In order to balance the tradeo between new and refreshed interests, the followingcombinations of policies can be considered: (DPF-*/DPF-*), and (PPF-*/DPF-*) where
* may refer to one of the following policies: most recently used (MRU), least recently
used (LRU), most frequently used (MFU), most fresh (MF) or least fresh (LF). These
policies make pending publications more persistent than other publications, which is
risky as pending publications may correspond to unpopular publications.
Information consumers request most recent publications (freshness) and want theirinterests to be satised (availability). Consequently, selecting most fresh information
rst and replacing least fresh information rst i.e. an MF/LF policy, will make most
fresh publications more persistent in the mediation network. An LF/LF policy is also
worth investigating w.r.t. the availability of fresh information.
Information providers want to reach the widest possible audience. Fairness amonginformation providers in terms of content availability for content of similar popularity
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CHAPTER 2. THE E-CBN FRAMEWORK FOR EXTREME-SCALECONTENT-BASED NETWORKING 33
is important in order that some popular content providers do not get discriminated.
An interesting policy to investigate to achieve such fairness is LFU/MFU.
From the perspective of network operators, communication-eciency and contentavailability for consumers can be achieved by enforcing an MRU/LRU policy [JST+09].
In the next chapter, we evaluate the following congurations:
Conguration Expected properties Name
LFU/MFU Fairness LFU
MRU/LRU Communication-eciency and availability MRU
MF/LF Availability of fresh content MF
LF/LF Availability of fresh content LF
DPF-MF/DPF-fLF, LRUg Increases availability of content for refreshed interests DPF, DPFuPPF-MF/DPF-fLF, LRUg Increases availability of content for refreshed interests PPF, PPFu
Table 2.2: Caching congurations to investigate
2.3.2.2 Caching policies
Besides the selection and replacement policies, routers can enforce one of the following
policies:
Default: With this policy enabled, publications are cached only at publishing or requesting
routers.
En-route caching (NRT): With this policy enabled, routers are allowed to cache tran-
siting publications according to the enforced replacement policy and if the content
items are not already present into the cache. The evaluation in the next chapter clar-
ies situations where routers have incentives to cache transiting content. Selecting
publications replicate those publications at several routers and consequently increase
their availability. Replication and persistence of selected publications are expected
to increase when the NRT policy is enabled.
2.3.3 Interest forwarding
Interests have a persistent and/or temporary lifetime. In their temporary lifetime, i.e.
during their propagation in the network, interests are satised with cached publications.
Instead, in their persistent lifetime, interests are satised with pending publications which
have just been uploaded or selected for dissemination. Advertising an interest consists in
ooding the interest in the mediation network until it is satised or all brokers are notied
with the interest.
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34 2.3. E-CBN: ARCHITECTURE AND MECHANISMS
Note that in order to avoid loops and duplicates with arbitrary topologies, we assume
that interest messages embed a globally unique identier to detect cycles. This is more
convenient than operating over global spanning trees. Designing such scheme is an im-
plementation detail, but it can be achieved by generating hierarchical identiers where
the prex is the identier of the Mediation router. In our work, we assumed that during
their lifetime, interests are advertised once in the mediation network, otherwise a nonce
would have been necessary. Moreover, we assume that interests have dierent identiers
throughout their successive lifetimes.
Routers exchange interests using the following procedure: Upon reception of S(max; )by router R, if the interest identier has already been advertised in the PIT, then drops the
interest. Otherwise, if the number of relevant publications available into the cache exceeds
or equals max, then max publications are selected for delivery and the propagation is
stopped. Otherwise, S is further advertised with the max parameter decremented by the
number of matching publications oered by R (See g. 2.8).
Fig. 2.8 illustrates a scenario where starvation may occur: Three publications relevant
to I are available but only two of them are forwarded to BrokerC . This is due to the bad
selection decision of BrokerP which returns c4 instead of c5 that would have contributed
to satisfy the interest. This situation underlines the sensitivity of selection policies on
starvation. Moreover, forwarding c4 in the mediation network generates an overhead that
should not be neglected. Note that the requesting broker can always detect duplicate
publications occuring during a lifetime retrieved from the network for the same interest
using the states available in the BT.
In order to attenuate that overhead, we introduce in Section 2.3.6.2 the in-network
duplicate dropping (IDD) mechanism, where a broker drops a publication already present
in the cache because it may have already responded with that content. In order to reduce
starvation due to bad selection decisions, we propose in Section 2.3.6.2, the proactive dupli-
cate dropping (PDD) mechanism or duplicate avoidance, where interests are forwarded with
the list of publication identiers already used to satisfy them along the forwarding path.
These schemes are not perfect. They may infer themselves starvation and an overhead of
publication messages in scenarios such as the one described by Fig. 2.10. Note that both
schemes can be combined.
2.3.4 Dissemination strategies
We discuss below, two simple yet eective strategies in the trade-o between satisfaction
and communication-eciency.
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CHAPTER 2. THE E-CBN FRAMEWORK FOR EXTREME-SCALECONTENT-BASED NETWORKING 35
BrokerC BrokerPConsumer
subscribe(I(ps, 3, T, f))
deliver(c1, c4)
forward(c4)
advertise(I(ps, 1, T, f))
{c1, c4} {c4, c5}
cache c4 if possible, otherwise drop it
T
select c4
starvation
{c2, c3}cache replacement
Note: We assume that c1, c4, c5 are relevant to interest I. BrokerC is the
home router of Consumer and the cache replacement event may correspond to
the upload of new content forcing the cache replacement policy to apply.
overhead
Figure 2.8: Starvation illustration
Push/pull and explicit overload notication (EON)
Overload corresponds to the situation where the number of publications retrieved from
the network w.r.t. an interest exceeds the selectivity of the subscription. A publication
P is disseminated by a router R, whenever at upload time, P matches an interest in the
forwarding table or if a matching interest transits through the node while the publication
is pending (push/pull). When an interest is satised i.e. max or more publications have
been retrieved, the corresponding home router advertises an overload notication message
in order that remote routers remove the corresponding states from their tables (overload
notication). Fig. 2.9 describes the interest forwarding strategy operation with the EON
mechanism enabled.
2.3.4.1 Pull/delayed push (PDP)
Unlike EON, PDP does not use explicit notication messages to notify remote routers of
overload. PDP uses the propagation of new and refreshed interests by the content-based
routing protocol to pace the dissemination process (pull) instead of pushing publications
additionally. In order to avoid that starvation occurs in some cases, we compute a most
lately publication time for each uploaded publication matching pending interests. Let P be
a publication uploaded at a router R at time t0 and SP be the set of matching interests
advertised in R's forwarding table (excluding local interests), the most lately publication
time tP associated to P is given by the relation:
-
36 2.3. E-CBN: ARCHITECTURE AND MECHANISMS
BrokerC BrokerPConsumer Provider
subscribe(I(ps, 2, T, f))
deliver(c1)
upload(c2)
{c2}
{c1}
forward(c2)
deliver(c2)
advertise overload(I)
refresh(I(ps, 2, T, f ))
advertise(I(ps, 1, T, f))
{}
Note: We assume that c1 and c2 are relevant to I.
T
No relevant content available
Remove states corresponding to I
Figure 2.9: Interest forwarding and content dissemination
tP = t0 + minS2SP
(deadline(S)) : (2.3)
being a system parameter and deadline(S) being the remaining time before S expires.
At last, any publication that may contribute to satisfy an interest not yet satised, is
nally disseminated. Note that should be engineered such that it is greater or equal to
the time required to forward a publication between two endpoints of the network. In the
case where a scheduled publication is eligible for replacement by another one, the scheduled
publication is immediately disseminated and the incoming publication cached.
A publication scheduled with PDP is disseminated at scheduling time even though a new
interest selects the publication before its dissemination. Once scheduled, the publication
stops being pending, but overowing or dispatched, depending on whether there exists
local/remote recipients. Thus, while the publication is scheduled it may be selected by
other interests and forwarded into the mediation network. Consequently, publications
disseminated with PDP are forwarded with the pending ag disabled.
2.3.5 Publication forwarding
Publications are forwarded in the content-based network depending on whether they are
selected by pending or transiting interests. In Fig. 2.7, the nonce eld is used to iden-
tify publication messages and the identier eld is used to identify content embedded in
publication messages. Nonces are used to detect duplicates on cyclic topologies. We use
nonces embedded in publication messages in order to avoid forwarding loops instead of
global spanning trees.
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CHAPTER 2. THE E-CBN FRAMEWORK FOR EXTREME-SCALECONTENT-BASED NETWORKING 37
BrokerC BrokerPConsumer
subscribe(I(ps, 3, T, f))
forward(c1, c2)
advertise(I(ps, 3, T, f))
{c1, c2}
T
c2 replaced by c3
BrokerI
{c2}{}
deliver(c1, c2)
forward(c2) {c1,c3}
forward(c2)drop c2
{c1, c2}
overhead
advertise(I(ps, 1, T, f))
Note: We assume that only c1 and c2 are relevant to I.
Figure 2.10: Duplicate dropping mechanism limitations
Unicast delivery: A publication selected by a transiting interest is forwarded on the
reverse path only towards the requesting broker. The in reply of eld of the cor-
responding publication message (see Fig. 2.7) is initialized to the identier of the
interest that selected the publication and triggered the forwarding of the publication
message. The information of the broker that advertised a particular interest identier
is provided by the PIT.
Multicast delivery (content dissemination): When a pending publication is selected
by pending interests, it is disseminated towards all the receivers that have advertised
the interest. Each broker which belongs to the dissemination tree DT of the pending
publication rooted at the publishing broker, can determine the next hop in DT by
evaluating the publication description against the set of interests advertised in the
PIT. Content dissemination can be realized according to baseline content-based for-
warding (section 2.1), either by performing matching on a hop-by-hop basis or by
performing matching at the publishing broker and switching on the subsequent nodes
of the delivery tree such as the DV/DRP protocol [HCW+06] described in section 2.1.
The latter case would require to encode the in reply of eld of publication messages
(Fig. 2.7) as a type-length-value (TLV) element.
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38 2.3. E-CBN: ARCHITECTURE AND MECHANISMS
2.3.6 Forwarding optimizations
2.3.6.1 Congestion-aware forwarding
Congestion may appear at some routers. It is important in these conditions to maximize
the satisfaction of the service. This can be done by assigning priorities to transiting publica-
tions. The priorities are used to schedule publications in buers upstream and downstream
the forwarding decision.
For this purpose, we compute a score for each publication embedded in publication
messages. The score is recomputed by every hop on the delivery path. Let R be a router
and be the set of publications buered at R that are waiting to be further disseminated.
For each publication P 2 , we dene SP the set of interests matching P downstream R,and compute a score Cbf(P) giving higher priority to popular and urgent publications.
We estimate popularity by the number of matching interests advertised downstream R and
urgency by the minimum deadline among matching interests. Cbf(P) is dened by the
following equation:
Cbf(P ) =jSpj
minI2SP
(deadline(I)): (2.4)
Note that in the unicast case, the score associated to a publication selected by an
interest I is simply 1=deadline(I). Obviously, in any case, to avoid a division by zero in
equation 2.4, interests whose deadlines have been reached are removed from the PIT and
not considered in the computation of the score.
2.3.6.2 Handling duplicate responses
When an interest is advertised in the content-based network, dierent brokers may reply
with the same (overowing or dispatched) publication. In the worst-case, the duplicate
responses will be detected by the requesting broker. This may infer starvation in scenarios
such as the one depicted by Fig. 2.8, as well as a communication overhead. In order, to
mitigate that overhead, we propose the mechanisms described below.
In-network duplicate dropping: Every broker, upon the arrival of a publication,
checks whether the publication already appears in its cache and if this is true, it dis-
cards it. Otherwise, it forwards the publication according to the technique described in
Section 2.3.5. The reason for searching the cache of a broker upon the arrival of a pub-
lication, is because publications follow the reverse path that interests follow. This means
that the interest that selected the corresponding publication has also been processed by
the broker under question which may have responded to that interest with the same cached
publication(s). Note that this mechanism is not always eective as depicted by Fig. 2.10:
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CHAPTER 2. THE E-CBN FRAMEWORK FOR EXTREME-SCALECONTENT-BASED NETWORKING 39
The intermediate router BrokerP cannot detect that content c2 has already been forwarded
to BrokerC (that itself forwarded). As a consequence, BrokerP redundantly forwards c2 to
BrokerC which nally drops it thanks to the states installed in the BT.
Note that the duplicate dropping heuristic does not thoroughly solve the problem ad-
dressed but are expected to alleviate the communication overhead. Fig. 2.10 exhibits
extreme cases where in-network duplicate generates starvation and communication over-
head.
Duplicate avoidance: In order to improve the eectiveness of the in-network duplicate
dropping scheme, we propose a proactive counterpart such that a broker processing an
interest and selecting cached publications to serve an interest, append the list of identiers
of the selected publications to the corresponding eld in the interest message before further
forwarding the interest. With this mechanism, duplicate responses will be eliminated from
every branch of the tree within which the interest is forwarded.
2.4 Discussion
This chapter described the E-CBN framework for extreme-scale content-based networking.
The framework introduces a service model capturing the quantitative and qualitative het-
erogeneity of information consumers and addresses the key design issues in implementing
eciently the service model. In the next chapter, we quantify the communication gains
of E-CBN over baseline content-based networking under realistic workload assumptions and
evaluate the eectiveness of each mechanism implemented by the framework.
-
40 2.4. DISCUSSION
-
Chapter3Evaluation
Contents
3.1 Workload characterization . . . . . . . . . . . . . . . . . . . . . . 42
3.1.1 On the relevance of workload modelling . . . . . . . . . . . . . . . 42
3.1.2 Evaluation methodology . . . . . . . . . . . . . . . . . . . . . . . . 43
3.2 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
3.3 Caching policies evaluation . . . . . . . . . . . . . . . . . . . . . . 50
3.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
41
-
42 3.1. WORKLOAD CHARACTERIZATION
This chapter provides a characterization of the framework with respect to the quality of
service oered to consumers and communication-eciency. Firstly, we quantify the gains
of the framework (e-CBN) over a baseline scheme implementing the exhaustive ltering se-
mantic (EF). We assume in the EF case that receivers caching resources are unlimited which
is an extremely unfavorable assumption for e-CBN. Secondly, we evaluate the eciency of
the eight policies introduced by table 2.3.2.1 and discuss the benets of en-route caching
(NRT). Finally, we measure the performances of the congestion-aware forwarding scheme.
Note that in the experiments, we did not observe any occurrence of duplicates ltered at
the edge. Consequently, it is worthless to evaluate the IDD and PDD schemes.
Performances are characterized using the following metrics:
Satisfaction, which is the percentage of interests satised as dened by Eq. 2.1. Weuse this metric mainly to compare an instance of the framework to EF.
Starvation probability (SP), which is the frequency of occurrence of starvation. SPis preferred when comparing two instances of the framework. Unlike the semantics of
satisfaction as dened above, SP does not account for interests which are not satised
due to the unavailability of relevant publications. SP accounts only for interests which
are not satised, while EF would have satised the interest assuming unlimited caching
resources at the receivers.
Message trac, which is the total number of publication messages forwarded intothe mediation network. We also characterize the message trac by the bandwidth
saved, which is how much bandwidth has been saved for a given scenario using e-CBN
instead of EF.
Control trac, which is the number of interest messages forwarded into the me-diation network. We characterize the control trac also by the control overhead,
which is the ratio between the control trac generated by an instance of e-CBN and
the control trac generated by an instance of EF.
3.1 Workload characterization
3.1.1 On the relevance of workload modelling
When evaluating content-based publish/subscribe approaches, workload assumptions in
terms of popularity and locality signicantly impact measured performances. Due to the
lack of publicly available datasets of large scale content-based publish/subscribe systems,
synthetic workload generation has been widely accepted. The resulting challenge is how to
-
CHAPTER 3. EVALUATION 43
choose the parameters of the workload model in order to generate a workload consistent
with a given application prole.
For instance, content-based routing (CBR) [CRW04] is preferable over pure broadcast
only in scenarios with a sparse density of receivers. For this reason, previous CBR research
has been evaluated under specic popularity and locality assumptions.
The seminal work on content-based routing [CRW04] is evaluated assuming that the
density of receivers equals 75%, and the popularity distribution is characterized by the
matching message distribution, which represents the number of messages matching a per-
centage of predicates. Most messages match 5% to 15% of the predicates, a signicant num-
ber of messages do not match any predicate, and no message matches more than 25% of the
predicates. Another signicant work, Kyra [CS04] was characterized for comprehensiveness
with four dierent popularity and volume distributions reported in the publish/subscribe
literature.
Majumder et al. study in [MSRS09] the impact of locality patterns on the communication-
eciency of several clustering algorithms for content-based routing. The workload is tuned
from a localized subscription model, i.e. similar subscriptions originating from the same
region, to an uniform model. In fact, the locality of similar subscriptions has a signicant
impact on the eciency of multicast-based schemes and the eciency of optimizations such
as subscription covering [TK06].
The sensitivity of topologies on the communication-eciency of content-based routing
schemes is discussed in [MC07], where a run-time algorithm to adapt the topology to the
application demand is proposed.
A very interesting fact about the importance of workload assumptions on the conclusions
one can draw from the evaluation of its solution is the positioning of Riabov et al. in
[RLW+02] regarding the conclusions on the benets of multicast in one of the Gryphon
papers [OAA+00]. Riabov et al., demonstrated that the conclusions from the Gryphon
papers were not always true and that they depend on the assumptions made on locality
and similarity properties.
3.1.2 Evaluation methodology
For the evaluation of the framework, we assume a news dissemination application such
as Google alerts implemented with e-CBN distributed over a network of brokers. The
workload is generated in order to meet this application prole. In order to validate our
algorithms and design choices, we implemented the framework in the PEERSIM simulator
which is a common choice for the evaluation of large-scale publish/subscribe solutions.
Up to 8 GB of RAM memory were necessary to run the experiments given the size of the
forwarding and caching indexes.
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44 3.1. WORKLOAD CHARACTERIZATION
We consider that a set of events generate both publications and interests, and that three
parameters characterize each event: popularity, locality and volume. The popularity of an
event refers to the number of interests related to it, its volume to the number of related
publications and its locality to the regions of the topology likely to originate related interests
and publications. A similar methodology is used in [CS04]. We prefer this methodology
because it ts the target application model, and because it allows an easier control of
popularity and locality assumptions.
In the generation of our workload, we assume an arbitrary router topology of 100 nodes
characterized by average degree 4, diameter 6 and following a power-law distribution with
few nodes of high degree and many nodes of small degree (See Fig. 3.1). We assume that
each broker is provisioned with some amount of caching resources and can cache up to CS
objects.
Figure 3.1: Evaluation topology
We assume that most popular events are characterized by larger and broader audiences in
terms of number of interests, and are also likely to trigger larger volume of publications. In
other terms, event popularity and volume are generated according to the same distribution.
Remember that we evaluate only loose subscriptions.
We investigate two dierent locality patterns for the workload generation:
Random: Publications and interests originate from random locations.
Realistic: Most popular events are more widely spread in the topology.
Let us consider ei (1 i E), an event of popularity pi, volume vi and locality li.pi is sampled from a power-law distribution and the volume vi is such that vi = P pi,where P is the total number of publications generated by the scenario. When the random
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CHAPTER 3. EVALUATION 45
Date Monitored events Volume Peak popularity
12-04-2011 33 9507 30%
13-04-2011 31 7941 40%
14-04-2011 29 8875 45%
Table 3.1: Statistics from the front page of Google news
Parameter Default Value
Dissemination policy EON
Number of interests 100 000
Number of publications 50 000
Cache size (CS) 5000
Refresh probability 1.0
Number of events 50
Zipf exponent 1.0
Buer size 50000
Average selectivity 10
Simulation time 100
Average lifetime 20
Freshness 50
Network Size 100
Locality pattern realistic
Selection/replacement policy MF
Caching policy Default
1
Table 3.2: Default parameter values for the evaluation
locality pattern is enforced, publications and interests associated to ei can be issued by any
of the N routers constituting the mediation network. When the realistic locality pattern
is enforced, publications and interests associated to ei can be issued only from a set of
nodes computed using li. In that case, we dene li such that li = pi and such that dli Nerouters are potential issuers (hosting interested receivers) of interests related to ei. This set
of routers is computed by choosing a random root node and dli Ne 1 additional nodesamong the closest routers to the root. We assume a constant arrival rate for interests
(resp. publications) equals to rs = S=T (resp. rp = P=T ), where S is the total number of
subscriptions generated by the scenario.
For each publication (resp. interest), we randomly select an event and a location among
the routers eligible to generate trac related to that event. When the volume (resp.
popularity) associated to an event is reached, it is removed from the set of events that can
be used to generate new publications (resp. interests). We generate selectivity and lifetime
values associated to interests according to Poisson distributions of average reported by
table 3.2. Randomizing selectivity and lifetime values is necessary to model heterogeneous
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46 3.1. WORKLOAD CHARACTERIZATION
consumer requirements.
We assume that each interest is refreshed at the end of its lifetime with a probability Pr
called refreshed probability, otherwise a new interest related to the same event is generated.
For the simulation of PDP, we set to 1, which is an upper bound of the end-to-end transfer
delay between any pair of brokers in absence of bottleneck.
Simulation time is set to 100. Consequently, every time unit, 500 new publications
are uploaded followed by the generation of 1000 new interests. Note that the PEERSIM
simulator does not provide any guarantee about the order in which the scheduler processes
the scheduled events.
Evaluation settings In order to model the event popularity distribution used to generate
the trac, we measured the volume distribution of the top stories reported by the french
front page of Google news during three consecutive days. It is interesting to note that on
the 14th April, the top story reached a popularity of 45% (see table 3.2) illustrating the
fact a single event may represent a major fraction of trac.
5 10 15 20 25 300
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
event ID
volu
me
120420111304201114042011
(a) Volume distribution
5 10 15 20 25 300
0.05
0.1
0.15
0.2
0.25
0.3
event ID
12042011zipf(1.0)zipf(0.7)zipf(2.4)
(b) Volume distribution tting (I)
5 10 15 20 25 300
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
event ID
volu
me
14042011zipf(1.0)zipf(0.7)zipf(2.4)
(c) Volume distribution tting(II)
Figure 3.2: Measures from Google news
Fig. 3.2 shows that the measured volume distribution can be approximated by a power-
law distribution of exponent 1.0 (12th april) or 2.4 (14th april). For workload generation, we
choosed exponent 1.0 in order to avoid a too much favorable scenario, where a single event
would generate most of the trac. The peak popularity equals 30% followed by a peak
of 10% i.e. the two most popular events generate 40% of publications and subscriptions
trac. We use the same series of event popularity in all our experiments. In fact, Fig.
3.3(c) shows that there is much volatility in the generated series and demonstrates the
importance to use the same series for the comprehensiveness of the results.
Regarding the refresh probability, we choose Pr = 1:0 i.e. each interest is automatically
refreshed after expiration. This is inline with the fact that RSS trac has been reported to
be sticky contrarily to web trac [LS05]. The number of events and publications simulated
has been sized on the basis of measures reported in table 3.1. Without explicit mention,
the reader should refer to table 3.2 for the default parameters values.
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CHAPTER 3. EVALUATION 47
Workload characterization We characterize the workload using three distributions:
matching distribution, density of recipients and gap distribution. The matching distribution
represents the CCDF of the popularity distribution of publications, which associates each
publication to the percentage of matching interests. The density of recipients represents
the CCDF of the topological popularity distribution of publications, which associates each
publication to the percentage of brokers which have requested the publication. The gap
distribution characterizes the dierence existing between consumers' attention span and
the volume of information available.
0 0.005 0.01 0.015 0.02 0.0250
0.2
0.4
0.6
0.8
1
popularity
proba
bili
ty
(a) Matching distribution
0 0.2 0.4 0.6 0.8 10
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
density of recipients
proba
bili
ty
random localityrealistic locality
(b) Density of recipients
0 10 20 30 40 500
0.05
0.1
0.15
0.2
0.25
0.3
0.35
event ID
(c) Popularity distribution
0 2000 4000 6000 8000 100000
0.05
0.1
0.15
0.2
0.25
0.3
0.35
gap values
(d) Gap distribution
Figure 3.3: Workload characterization
Fig. 3.3(b) characterizes the density of recipients and shows that no publication is
requested by more than 24 % of brokers with realistic locality enabled. Conversely, with
random locality enabled, most publications have a topological popularity superior or equal
to 90 %. Realistic locality provides a less extreme scenario than random locality. Moreover,
this is inline with what has been reported from [LFHKM05], that for 60 % of les in an
e-Donkey network, more than 80 % of the replicas were in the same country. Fig. 3.3(a)
shows that in the workload there is no publication with popularity larger than 2.5%. The
gap distribution depicted by Fig. 3.3(d) is positive and clearly describes a situation of
information overload.
3.2 Results
Comparison of an instance of the framework to a variant of EF First, we compare
an instance of e-CBN to EF for dierent load levels obtained by varying the selectivity and
with realistic locality enabled.
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48 3.2. RESULTS
In Fig. 3.4(a), e-CBN satises 13% more interests than EF for various load levels.
e-CBN satises more interests than EF because e-CBN use cached publications to satisfy the
interests while EF doesn't take advantage of the cache. Consequently, more publications
are available with e-CBN than with EF. Fig. 3.4(b) shows that for small selectivity values,
e-CBN saves almost 100% of bandwidth and up to 40% of bandwidth for larger selectivity
values. These gains are obtained while still generating less control trac than EF.
Fig. 3.5 shows that with the MF policy and larger cache sizes, more interests are satised
(Fig. 3.5(a)), and communication-eciency is improved. Also, there is no incentive to add
caching resources beyond 1% of the total volume of publications. This is not a surprising
result, since with more caching resources, brokers have more opportunities to satisfy local
interests with cached publications. Note that Fig. 3.5(a) does not display the percentage
of satised interests by EF, because it is obvious that EF does not take advantage of the
cache to satisfy more interests.
Finally, 3.6(a) shows that the when the size of the network increases also increases the
satisfaction ratio of the two methods. Of course this increase is not very signicant (double
satisfaction ratio when the number of nodes is six times larger). More nodes/brokers might
mean more dierent cached messages, but on the other hand more brokers also increase
the replication degree of the cached messages which does not allow the retrieval of unique
cached items. At any case we observe that e-CBN performs on average 10%-34% better
than the EF. Also, it is obvious that for the default selectivity value the e-CBN saves almost
88% of bandwidth for small networks and up to 98% of bandwidth for larger network (see
Figure 3.6(b)), while generating less control trac (see Figure 3.6(c)).
0 %
20 %
40 %
60 %
80 %
100 %
5 10 15 20 25 30 35 40 45 50
satisfaction
selectivity
e-CBNEF
(a) Satisfaction
0 %
20 %
40 %
60 %
80 %
100 %
5 10 15 20 25 30 35 40 45 50
bandwidth saved
selectivity
(b) Message trac
0 %
20 %
40 %
60 %
80 %
100 %
5 10 15 20 25 30 35 40 45 50
control overhead
selectivity
(c) Control trac
Figure 3.4: Performance comparison of an instance of e-CBN to EF for dierent load levels
Dissemination methods evaluation Fig. 3.7 compares the performances of PDP to
EON for dierent load levels. We observe that PDP and EON display close performances
with respect to the quality of service (less than 2% of starvation even for extremely large
selectivity values) and the amount of trac generated by the content-based network. It is
noticeable that PDP generates slightly less control trac than EON. This may be due to the
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CHAPTER 3. EVALUATION 49
20 %
25 %
30 %
35 %
40 %
0 100 200 300 400 500 600 700 800 900 1000
satisfaction
cache size
(a) Satisfaction
60 %
65 %
70 %
75 %
80 %
85 %
90 %
95 %
100 %
0 100 200 300 400 500 600 700 800 900 1000
bandwidth saved
cache size
(b) Message trac
88 %
90 %
92 %
94 %
96 %
98 %
100 %
102 %
104 %
106 %
108 %
110 %
0 100 200 300 400 500 600 700 800 900 1000
control overhead
cache size
(c) Control trac
Figure 3.5: Performance comparison of an instance of e-CBN to EF for dierent cache sizes
25 50 75 100 125 150 175 200 225 250 275 300
0%
10%
20%
30%
40%
50%
60%
70%
80%
e-CBN
EF
satisfaction
network size
(a) Satisfaction
25 50 75 100 125 150 175 200 225 250 275 300
86%
88%
90%
92%
94%
96%
98%
100%
bandwidth saved
network size
(b) Message trac
25 50 75 100 125 150 175 200 225 250 275 300
75%
80%
85%
90%
95%
100%
105%
110%
control overhead
network size
(c) Control trac
Figure 3.6: Performance comparison of an instance of e-CBN to EF for dierent networksizes
fact that PDP does not generate overload notication messages.
Enhanced forwarding scheme evaluation We compare the performances of the en-
hanced forwarding scheme (CBF) to a simple FIFO policy for dierent buer sizes. Fig.
3.8(a) shows that FIFO achieves a bad quality of service and does not take advantage of
larger buer sizes. CBF instead takes better advantage of the available bandwidth and
processing capacity to improve the QoS oered to consumers.
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50 3.3. CACHING POLICIES EVALUATION
0.001 %
0.01 %
0.1 %
1 %
10 %
100 %
5 10 15 20 25 30 35 40 45 50
starvation probability
selectivity
EONPDP
(a) Starvation
0
0.5
1
1.5
2
2.5
3
3.5
5 10 15 20 25 30 35 40 45 50
message traffic (million of messages)
selectivity
EONPDP
(b) Message trac
0
5
10
15
20
25
30
5 10 15 20 25 30 35 40 45 50
control traffic (million of messages)
selectivity
EONPDP
(c) Control trac
Figure 3.7: Performance comparison of EON and PDP
0 %
5 %
10 %
15 %
20 %
25 %
30 %
100 200 300 400 500 600 700 800 900 1000
starvation probability
buffer size
FIFOCBF
(a) Starvation
0.1
1
10
100
1000
100 200 300 400 500 600 700 800 900 1000
message traffic (thousand