mice: monitoring and modeliing the context evolution

Luca Berardinelli [email protected]

Flavia Di Paolo [email protected]

An3nisca Di Marco [email protected]

Dipar4mento di Ingegneria e Scienze dell’Informazione e Matema4ca (DISIM) University of L’Aquila (ITALY)

MICE: Monitoring and modelIng the

Context Evolu4on Lyon

10/09/2012

•  Keywords •  Mo4va4ons and Mo4va4ng Example

•  Background: our context modeling and analysis approach

•  The MICE Tool

•  Ongoing and Future Works

•  Conclusions

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OUTLINE

Context: The heterogeneous informa3on that the soXware system is capable to sense from itself or from the external environment that can influence the behavior of the services it provides.

Context Awareness: The ability of the soXware system to sense the context in which it is execu4ng and to change the behavior in response to changes of the sensed context.

Context Evolu3on: The set of changes in the sensed context and their possible (cause-‐effect) rela4onships.

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KEYWORDS

MOTIVATIONS

•  The Goal: –  Valida,on and refinement of (context) models at run-‐,me, as the basis for

•  Predic/ve Analysis of QoS: predic4ng the QoS of a context-‐aware soXware system within ranges of parameters that are not (yet!) experienced in prac4ce;

•  Proac/ve Context Evolu/on: provinding in advance QoS informa4on so that the system adapta4on is not blindly taken, but it can be QoS-‐aware

•  Our Contribu,on: –  MICE (Monitoring and modelIng the Context Evolu4on), a suppor4ng tool

for our context modeling and analysis approach.

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MOTIVATING EXAMPLE

5

PlaBorm Layer

PDA Wireless Network

TCP/IP

Mobile eHealth Doctor Pa3ent Service Layer

Request Pa3ent Info Send Alarm

Service Manager

Component Layer

Doc GUI Server App Beeper Client Doc Client

home

surgery open air

pa3ent’s home

Mobile eHealth (MeH) is a mobile, component-‐based applica4on for assis4ng doctors in their everyday ac4vi4es through services running on their PDAs.

MeH Context may be (but not limited to) a combina3on of: •  Physical Loca4on of its users •  Logical Loca4on of its sw components •  Configura4on of its hardware resources

BACKGROUND: CONTEXT MODELING

–  An approach presented at FASE 2010

–  Based on Awareness MANAGERs, a stochas4c extension of Harel’s Statecharts •  can be associated to any modeling element whose aCributes contribute to define the

applica4on-‐specific context where

•  each state (par4ally) represents the actual context as a set of ajribute values.

•  transi,ons are triggered by the occurrence of certain event(s) when certain condi4on(s) are verified.

•  Paramenters : Probabili3es are associated to transi4ons.

•  Assump3on: Probabili3es are exponen3ally distributed à Markov Model (CTMC) à Steady State probability vector may be associated to the state space (π probB)

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Best Paper Award

Luca Berardinelli, Vijorio Cortellessa, An4nisca Di Marco: Performance Modeling and Analysis of Context-‐Aware Mobile SoXware Systems. FASE 2010

DSLs or

ELEMENT::Awareness Manager

attri=va attri=vb

A B

Context-‐related ELEMENT

a@r1…aCri …a@rn

tr. prob “,” event “/” [condition] “/” action

(π probB)

System Design Model

BACKGROUND: CONTEXT MODELING IN MEH

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Awareness Manager examples for the MeH System…

…and an excerpt of their combina4on. At any 4me, the context of MeH is triple of three values

At design-‐4me all the parameter are the transi4on probabili4es (assumed) and the steady state probabili4es (calculated).

MICE: Moving AMs from design-‐ to run-‐4me •  Problem: collec4ng contextual data at run-‐4me to con4nuously update the AMs –  Req.1: MICE has to support our Context Modeling approach –  Req.2: The implementa4on effort should be appropriate w.r.t. the availability of human resources and their skills (few undergraduate/graduate students)

–  Req.3: The maintenance effort should be as lower as possible (students usually leave the project aXer the end of the exam/thesis).

–  Req.4: MICE has to reuse COTS as much as possible (it helps in sa4sfying Req.2 and 3).

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MICE: Moving AMs from design-‐ to run-‐4me MICE is a composite and distributed system that includes three main components with the following roles:

• Monitor. It is in charge of collec4ng the heterogeneous data that are sensed by the context-‐aware applica4on (e.g., the bajery level or the CPU frequency). The raw data are then sent to a remote Context Data Repository.

• Context Data Repository. It collects the contextual data sent by any Monitor and makes them available for further elabora4ons.

• Modeling Component. It retrieves data from a Context Data Repository and elaborates them to generate context models (i.e. AMs).

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MICE: Moving AMs from design-‐ to run-‐4me

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Monitoring Component (Ba@ery Status Cosm) Context Data

Repository (Cosm Web Service)

HTTP Modeling Component

Context Model API (EMF-‐based API)

MICE

• Monitor: Bajery Status (COTS)

• Context Data Repository: Cosm (COTS)

• Modeling Component: Context Model API (in-‐house)


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PDA (Android Device)

Context Aware System (MeH Client)

Monitoring Component (Ba@ery Status Cosm)

BaYery WiFi Card

Screen

ßlevel (%)

ßon

/off

ßon

/off

ßtemp (°C)

ßplugged (1/0)

hjps://play.google.com/store/apps/details?id=nfcf.BajeryStatus&hl=en

Keep track of your bajery informa4on. This app runs in the background collec4ng you bajery level, voltage, temperature and plugged state and sends this informa3on to your Cosm account. Addi4onal data is also collected: -‐ Screen brightness -‐ Network status -‐ Phone Call state -‐ WiFi on/off -‐ Bluetooth on/off -‐ Data transferred

Monitor: Bajery Status App (COTS)

HTTP


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hjps://cosm.com/how_it_works

Context Data Repository (Cosm Web Service)

ßRaw Data (feed)

Cosm-‐enabled device

Raw Data (feed)à

Cosm-‐enabled device Cosm-‐enabled device feedà

Cosm is a RESTful Web service that, through the HTTP protocol, allows the publica4on (POST) and retrieval (GET) of sensor-‐derived contextual data to/from the Web. The whole heterogeneous contextual data collected from a Cosm-‐enabled device is organized in feeds. The lajer are divided in (typed) datastreams that, in turn, are composed by datapoints, each represen4ng a single value of a datastream at a specific point in 4me. Any feed on Cosm belongs to a registered user that may decide to keep them private or public.

Context Data Repository: Cosm (COTS)


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hjps://cosm.com/how_it_works

Context Data Repository: Cosm (COTS)

Battery Level: 35 (%) at Aug 15 20:01:15

Plugged: 1 (true) at Aug 15 20:01:15

Data Not Collected


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hjp://code.google.com/a/eclipselabs.org/p/context-‐manager/

Modeling Component (in house)

Modeling Component


It includes a -‐  Parameters Extractor that sets the state-‐

steady probabili4es π of the modeled Manager by processing the real data collected by the Monitoring Component.

-‐  Context Manager Editor that allows the modeling of the Managers

They are both based on a Context Model API

Manager(s)à

MICE: Moving AMs from design-‐ to run-‐4me Context Model API has been automa4cally obtained from a Ecore-‐based

AM Metamodel

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Modeling Component: Context Model API (in-‐house)

Modeling Component


The Modeling Component has been implemented from scratch in Java. It is composed by a Context Manager Editor that allows the modeling of the Managers, plus a Parameters Extractor that sets the state-‐steady probabili3es π of the modeled Manager by processing the real data collected by the Monitoring Component. The Parameter Extractor retrieves the raw monitored data stored in the Context Repository COTS and then calculates the state-‐steady probabili4es from the sojourn 4mes in the iden4fied awareness states.

hjp://code.google.com/a/eclipselabs.org/p/context-‐manager/

Thanks to Giovanni Di Santo (Context Editor, Bachelor Thesis)

JVM-‐compa4ble Device

PDA (Android Device)

Context Aware System (MeH Client)

BaYery WiFi Card

Screen


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Monitoring Component (BaCery Status Cosm) Context Data

Repository (Cosm Web Service)

ßRaw Data (feed)

HTTP

ßlevel (%)

ßon

/off

ßon

/off

ßtemp (°C)

Modeling Component


Raw Data (feed)à

MICE feedà

ßplugged (1/0)

Cosm-‐enabled device Cosm-‐enabled device Cosm-‐enabled device

Thanks to Flavia Di Paolo (co-‐author)

(MICE, Bachelor Thesis)

MICE at a glance

Manager(s)à

MICE@WORK: MeH Running Example The following list summarizes the main steps that have been undertaken to set up the running example (Mice v.1): •  We created a Cosm account; •  We installed, set up and started the BaYeryStatus applica4on on two Android

devices so that new datapoint were sent by BajeryStatus every 15 minutes;

•  We retrieved from Cosm the up-‐to-‐date collec4on of level datapoints of the latest 30 calendar days (as a CSV file).

•  We set a user-‐defined percentage threshold, for example strictly greater than 25%, and coupled each level datapoint with the high power or the low power awareness states, respec4vely;

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Data Not Collected

25% threshold

High Power

Low Power

MICE v1

MICE@WORK: MeH Running Example •  We calculated the sojourn 3mes in the high and low power states by

coun4ng the number of couples, each corresponding to a 4me slot of 15 minutes, assigned to the high and low power awareness states.

•  Given the total amount of minutes in a single day (1440) and in a month of 31 days (46400) we calculated the percentage of 3me spent in high and low power (i) during the latest monitored day at the 4me of wri4ng and (ii) in the latest monitored month.

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MICE v1

ONGOING AND FUTURE WORKS •  We are combining different datastreams (e.g., level and plugged) to

create more complex Awareness Managers.

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MICE v2


Plugged: 1 (true) at Aug 15 20:01:15

Data Not Collected

25%

High Power

Low Power

Under Charge

ONGOING AND FUTURE WORKS •  We are formalizing the proposed context modeling nota3on to suitably

combine ( ◦ ) two or more Awareness Managers, including remote firings (i.e. AM dependencies), into a mul4-‐ajribute Context Manager that s4ll remains a valid Markov Model.

•  We are combining Context, Design and Analysis Models at run-‐3me. We already combine these different kind of models but at design-‐4me (NFPinDSML@Models 2009)

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CONCLUSIONS •  We presented MICE, a distributed tool for monitoring and

modeling the context evolu4on;

•  It is meant to support an exis4ng Context Modeling and Analysis Approach presented at FASE 2010;

•  MICE exploits exis4ng COTS to reduce its implementa4on and maintenance efforts so making it suitable for undergraduate and graduate students

•  MICE is an ongoing work available at hjp://code.google.com/a/eclipselabs.org/p/context-‐manager/

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Thanks for your a@en/on. Ques/ons and sugges/ons are very welcome

mice: monitoring and modeliing the context evolution

Education

context awareness

analysis of context

sensed context

keywords context

actual context

context evolu3on

context modeling approach

contextaware applica4on