cost-efficient rule management and traffic engineering for software defined networks
TRANSCRIPT
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Cost-Efficient Rule Management and Traffic Engineering for Software Defined
Networks
Huawei Huang
Supervisor: Prof. Song Guo
University of Aizu
Sep. 8, 2016
Presentation slides for Ph.D dissertation
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Outline
Joint Optimization of Rule Placement and Traffic Engineering
for QoS Provisioning in SDN [1]
Cost Minimization for Rule Caching in Software Defined
Networking [2]
Near-Optimal Routing Protection for Software-Defined
Networks [3]
Threads of dissertation
Introduction and background
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SDN is
an emerging network architecture / paradigm
where the
control planeis decoupled from data forwarding plane (data-plane)
and
can be directly programmable.
Software Defined Networking ( SDN )
Control planealg, protocols
Data plane:
hardware,
Packet forwarding
SDN decouples the control plane & data plane
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Data plane:
hardware,
Packet forwarding
Control planealg, protocols
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3-layred SDN Architecture
Agile provisioning
Simplify management
Automation service
Benefits:
With SDN, operators, researchers, users, 3rd parties developers:
New function
Explanation of Basic Concepts
• What is Traffic Engineering (TE) ?• Control and optimization of routing, to steer traffic through the
network in the most effective way
• Traffic oriented performance, e.g.,
• Max (throughput)
• Min ( packet transfer delay )
• Min ( packet loss )
• How? -- Approaches• Collect measurements of traffic and topology• Compute paths based on load, and requirements• Optimize the setting of the “static” parameters
• With SDN, these are easy.7
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Flow Table Entry
(also called Forwarding Rule,
which is installed in Flow-Table of a switch)
Controller
Explanation (cont.)
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How a Packet is processed in a switch / router ?
Flow table stores Flow Table Entry.
Explanation (cont.)
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Rules paly various functionalities.
Rules have to be installed in TCAMs of switch.
Explanation (cont.)
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Outline
Threads of dissertation
Introduction and background
Joint Optimization of Rule Placement and Trac Engineeringfor QoS Provisioning in SDN [1]
Cost Minimization for Rule Caching in Software Defined Networking [2]
Near-Optimal Routing Protection for In-Band Software-Defined Networks [3]
Threads of this dissertation
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Rule spaceis limited
Link bandwidthis limited
Min (rule-number)Opt (rule placement)
Min (rule caching cost)
Min (delay)Max (throughput)Link load-balance
Resilience guarantee
Cost Opt.
TrafficEngineering
Rule management
&Traffic
engineering
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Outline
Joint Optimization of Rule Placement and Traffic Engineering for QoS Provisioning in SDN [1]
Cost Minimization for Rule Caching in Software Defined Networking [2]
Near-Optimal Routing Protection for Software-Defined Networks
Threads of dissertation
Introduction and background
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Joint Optimization of Rule Placement and Traffic Engineering for QoS Provisioning in Software Defined Network
(IEEE ToC2015)
Topic 1:
• Conventionally, duplicated rule-installation
• For each traffic flow, original SDN-protocol installs forwarding rules on its traversing path
Installs 2 rules for the 2 flows.
If DstIP=0.0.0.3,
then, do Action 1
IP=0.0.0.1
IP=0.0.0.2
If DstIP=0.0.0.3,
then, do Action 1
IP=0.0.0.3
ControllerRule 1
Rule 2A motivation case.
Server
Clients
• Turning duplicated rule-installation -> multiplexing rule-installation, when we conduct the TE:
• Only install one common rule that works for multiple flows.
• Total rule-space can be reduced.
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So, we study a problem of
rule-placement:
Min (total rule No.)subject to:
limited rule space;link capacity.
Idea
Topic 1: Joint Optimization of Rule Placement and Traffic Scheduling
• 4 cases of formulations :• MIP: mixed integer programming
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Topic 1: Joint Optimization of Rule Placement and Traffic Scheduling
RM: rule-multiplexingnonRM: non rule-multiplexing
CP: candidate path providednonCP: no candidate path provided
RM-CP:
nonRM-CP:
Min (rule num)
Trivial RM-nonCP & nonRM-nonCPcases are ignored here.
NP-hardness Proof
• Theorem 1. Given a set of candidate paths, the rule placement problem (RP) mentioned above is NP-hard.
• The proof is done by reducing the well-known 2-partition problem to the RP problem.
• i.e., we construct a special case of RP problem into the 2-partition problem.
• 2-partition problem is NP-hard -> rule-place. Problem is NP-hard.
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Topic 1: Joint Optimization of Rule Placement and Traffic Scheduling
Algorithms design
• Fast heuristics based on Relaxing-and-Rounding
• 1st step: Relax the Integer-variables -> Continuous ones
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[0, 1]
Conditionally round.
Topic 1: Joint Optimization of Rule Placement and Traffic Scheduling
Algorithms design (Cont.)
• Fast heuristics based on Relaxing-and-Rounding
• Critical idea of 2nd step: conditionally select a part of relaxed varsto round them back into integer, and construct a solution.
20Conditionally round some
back into integer.
Topic 1: Joint Optimization of Rule Placement and Traffic Scheduling
Case study under CP
• With candidate paths provided.
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Topic 1: Joint Optimization of Rule Placement and Traffic Scheduling
Cost: 40 rules. Cost: 20 rules.>
Case study under nonCP
• Without candidate paths
22Cost: 40 rules. Cost: 20 rules.
Topic 1: Joint Optimization of Rule Placement and Traffic Scheduling
>
Efficiency of RM is proved.
More simulation results
• Show that Rule-Multiplexing (RM) mechanism outperforms than nonRM.
• Particularly, RM-nonCP has the best performance.
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Topic 1: Joint Optimization of Rule Placement and Traffic Scheduling
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Outline
Joint Optimization of Rule Placement and Traffic Engineeringfor QoS Provisioning in SDN [1]
Cost Minimization for Rule Caching in Software Defined Networking [2]
Near-Optimal Routing Protection for In-Band Software-Defined Networks [3]
Threads of dissertation
Introduction and background
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Topic 2: Rule Caching
Background:When traffic arrives at a switch,
packets need to be processed bylocal-switch orremote-proxy (e.g., a middleboxor even a controller).
Cost Minimization for Rule Caching in Software Defined Networking
(IEEE TPDS 2015)
Virus
Controller
controls all switches
Arriving flow
Server
Firewall
proxies
Client
… Allowed flow
Ingress
switch
Malware
DoS
redirect
Redirected flow
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Decisions for each traffic-flow at each time-slot:
System model
Topic 2: Rule Caching
remote-processinglocal processing
When to install rule?
How long to cache the rule?
Which way to process packets?
0-1 decisionyt = 0 yt = 1
At time-slot t : Remote cost:
expense at the
remote proxy.Local cost:
expense at the
switch.
xt = 0 or 1?
local-processing cost remote-processing cost
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Total Cost = +
Problem: How to Minimize a joint cost ?
Given a set of flows and required rules,
We normalize the unit cost oflocal-processing asandremote-processing as
Topic 2: Rule Caching
Formulation
Trigger of remote
processing
Fetch at least one time
before caching
Packets in each Time-
slot need to be processed
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Basic analysis:Typical patterns in an optimal solution:
Three elements of optimal solution: Only remote processing
Only local processing
Hybrid
Topic 2: Rule Caching
Idea: achieve the goal by deciding: for a flow,whether and when to install rules in a switch,& how long to cache the rules if install them.
Algorithm Design
valid
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How good of this algorithm?
If the trace of a flow is given,
Offline Algorithm
Topic 2: Rule Caching
Evaluation of offline-algorithm
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Proactive algorithm : rules are only fetched in the first time slot and cached all the remaining duration.Reactive algorithm triggers remote process at each time slot.
Topic 2: Rule Caching
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How good of this algorithm?
Online Alg 1: Exactly Match the Flow(EMF)
The 1st Online Algorithm
Topic 2: Rule Caching
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Competitive ratio of this algorithm:
Online Alg 2: fixed length of Extra Caching Alg (ECA)
Topic 2: Rule Caching
The 2nd Online Algorithm
Evaluation of online algorithms
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Performance of Online
algs is within
theoretical bound
Online algs
perform better
than the original
SDN protocol.
More experiments to
prove the correctness
of theoretical bounds
for the online algs.
Topic 2: Rule Caching
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Outline
Joint Optimization of Rule Placement and Traffic Engineeringfor QoS Provisioning in SDN [1]
Cost Minimization for Rule Caching in Software Defined Networking [2]
Near-Optimal Routing Protection for Software-Defined Networks [3]
Threads of dissertation
Introduction and background
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Background before topic-3When emergent events happen,
e.g., earthquake occurs,some critical network links might be disconnected.
Routing-protection is an important topic !
Because, in the perspective ofTraffic-engineering,
we need to guarantee theMin ( network recovery delay ).
Topic 3: routing protection
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Near-Optimal Routing Protection for In-Band SDNs(The extension of this topic has been published in IEEE JSAC, 2016. )
https://www.researchgate.net/publication/301842070_Near-Optimal_Routing_Protection_for_In-Band_Software-Defined_Heterogeneous_Networks
• Motivation:
• The controller<->switch connections are critical ( higher priority than the data-plane routing paths ),
• disconnection brings very serious damages.
• When link failure occurs, the fast recovery is needed.
Topic 3: routing protection
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• Question: How to protect the controlling channels?
• with a low recovery delay,
• with a reasonable cost of switch node-configuration.
Topic 3: routing protection
• Traditional routing protection
• Local routing via Backup paths
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Related WorkTopic 3: routing protection
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• Dedicated-backup, e.g., 1+1 (1+N) protection
• With no recovery delay at all !!
• But with high cost on both terms:
• Link ( high-bandwidth consumption )
• Node ( switch-configuration cost )
• Trade-off has to be considered:
• If adopt dedicated-backup,
• Reduce the ( cost ) !
Optional Approach :
Topic 3: routing protection
Double backup paths,
High cost: double Traffic
rate !!
Formulation
• System model
• As shown in Figure 2.
• Formulation with Obj:
• Min ( link-bandwidth cost + connection-setup cost )
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Topic 3: routing protection
Exact |Ds| number of in-use paths must be selected.
Capacity constraints on link.
Capacity constraints on node.
Algorithm• Markov-Approximate based Algorithm
• Obj: load-balancing + connection-setup cost
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Define MC
Transit between different
states
Re-Compute transition
rate of different states
Topic 3: routing protection
Basic idea: To eliminate the neighboring congestion,
refresh the entire configuration ,rather than the conventional local rerouting.
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Online handlingTheory
Online handling in case of link-failure
Topic 3: routing protection
• Simulation
• Fat-tree Datacenter network
• Representative running case
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Topic 3: routing protection
• Comparison with conventional Local routing
• on the link-bandwidth consumption
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Topic 3: routing protection
reroute via link (0,4).
• Convergence property of the proposed algorithm
• Comparing with other benchmark algs.
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Topic 3: routing protection
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Outline
Joint Optimization of Rule Placement and Traffic Engineeringfor QoS Provisioning in SDN [1]
Cost Minimization for Rule Caching in Software Defined Networking [2]
Near-Optimal Routing Protection for Software-Defined Networks [3]
Threads of dissertation
Introduction and background
Conclusion and Future Work
Conclusion and Future Work
• Conclusion
• 3 topics related to Cost-optimization problems over Traffic-Engineering & Resource-utilization.
• Future work
• I am going to focus on the business logics under SDNs:
• Network Function Virtualization (NFV)
• Resilience and Security enhancement for SDNs
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Major references in slides:
[1] Huawei Huang, Song Guo, Peng Li, Baoliu Ye and Ivan Stojmenovic,“Joint Optimization of Rule Placement and Traffic Engineering for QoSProvisioning in Software Defined Network”, IEEE Transactions onComputers, vol. 64, no. 12, pp. 3488-3499, December 2015.
[2] Huawei Huang, Song Guo, Peng Li, Weifa Liang and Albert Y.Zomaya, “Cost Minimization for Rule Caching in Software DefinedNetworking”, IEEE Transactions on Parallel and Distributed Systems (TPDS),vol. 27, no. 4, pp. 1007-1016, April 2016.
[3] Huawei Huang, Song Guo, Weifa Liang, Keqiu Li, Baoliu Ye andWeihua Zhuang, "Near-Optimal Routing Protection for In-Band Software-Defined Heterogeneous Networks", IEEE Journal on Selected Areas inCommunications (JSAC), vol. 34, no. 11, pp. 2918-2934, October, 2016.