Component-based, Context-aware Software Systems

1 23.08.2006 michael.przybilski@cs.helsinki.fi

Component-based, Context-aware Component-based, Context-aware Software SystemsSoftware Systems

Workshop on Advances in Methods of Information and Communication Technology

Petrosavodsk State University

Michael Przybilski

2 23.08.2006 michael.przybilski@cs.helsinki.fi

MotivationMotivation

• Increase of available context information• Wireless information devices• Integrating increasing number of input and output devices

• Use for applications• Explicit, potential

• Use of communication possibilities• Remote devices• Number of devices

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OutlineOutline

•Challenges

•Approaches

•Component-based Systems

•Examples

•Ongoing Work

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ChallengesChallenges

• Acquisition, processing and provision of context data• Rapidly changing and uncertain sources

• Adapt behaviour (of system / application) depending on the situation ((physical) environment, location, …)

• Reactive / pro-active systems (real-time)

• Seamless vs. seam-full

• Reuse• Common steps• Context information

• Scalability, flexibility, privacy and trust, re-configurability, …

• Development vs. Runtime support

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Typical Mobile ConstraintsTypical Mobile Constraints

• Energy consumption• Data processing

• Data storage

• (Wireless) Communication• Bandwidth, Reliability (range, signal detection)• Infrastructure (dynamic network topology; ad-hoc and P2P networks)• Networking technologies (IrDA, BT, WLAN, HomeRF, PicoNet, …)• Routing protocols for PAN and MANET (AODV, DSDV, …)

• IO capabilities (form factor)

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Context and Context ReasoningContext and Context Reasoning

• A. Dey and G. Abowd, 1999: “Context is any information that can be used to characterize the situation of an entity. An entity is a person, place, or object that is considered relevant to the interaction between a user and an application, including the user and application themselves.”

• Other definitions by Chen and Kotz, Yau and Karim, …

• Categorization of context: Mayrhofer, Lieberman and Selker, Schilit, Adams and Want, Gross and Specht, …

• Context-reasoning can be defined as deducing new and relevant information from the various sources of context-data

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ApproachesApproaches• Monolithic systems

• Blackboard• Information exchange through shared (structured) spaces• Indirect communication• Data stored in tuple spaces

• Widget• Direct information exchange between objects• Message or RPC-based

• Level of re-use• Frameworks

• Design structure for a specific class of components or systems• Middleware systems

• software system that operates (logically) between operating system and application and provides commonly used services

• Infrastructures• Set of technologies (well-established, pervasive, reliable, and publicly

accessible) that act as a foundation for other systems

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The Context Toolkit (CTK)The Context Toolkit (CTK)

• Structure approach to context-aware systems• encapsulation of sensors• access to context data through a network API• abstraction of context data through interpreters• sharing of context data through a distributed infrastructure• storage of context data, including history• basic access control for privacy protection

• Standardized API for applications

• Enables monitoring• Active context input, application logic behavior, notification of context

output

• and control of context• Modification of application logic behavior, triggering of context output

• Java-based component framework• Also Python and C++ widgets

• Common subscription mechanism (call-backs)• HTTP + XML

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The Context Toolkit (CTK)The Context Toolkit (CTK)

• Context Widgets• Abstract context

information

• Interpreters• Raising the level of

abstraction

• Aggregators• Collection of multiple

pieces of context information

• Services• Execute (common) actions on behalf of applications

• Discoverers• Registry of capabilities available in the framework

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The Context Toolkit (CTK)The Context Toolkit (CTK)

•Widget Class: IdentityPresence

•Attributes• Location: Location the widget is

monitoring• Identity: ID of the last user

sensed• Timestamp:Time of the last arrival

•Callbacks• PersonArrives (location, identity, timestamp)

• Triggered when a user arrives• PersonLeaves (location, identity, timestamp)

• Triggered when a user leaves

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The Reconfigurable Context-Sensitive The Reconfigurable Context-Sensitive Middleware (RCSM)Middleware (RCSM)

• Context and resource sensitive

• Instant establishment and termination of communication channels (changing context, node mobility)

• High density of nodes and scalability for exponential interaction

• Categorization in terms of sources

• Network (routing, transport protocols)

• Device (power, ambient light, location, time, other devices in range)• User-Interaction (application specific and originating)

• Context-sensitive interface definition• Tuples of n values + time• Several operators for specification of temporal relationships

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ConFabConFab

•Infrastructure system• Platform (HW, OS) and language

independent• In-place upgrade of new sensors

and services• Easier development

•Standard Data Formats and Protocols (Data Model)

•Privacy issues• Decentralized architecture• control and feedback

mechanisms• Plausible deniability• Special exceptions for

emergencies

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ConFabConFab

•Entities (people, places, things and services) have InfoSpaces

• Contain context information (tuples)

• Held on infospace servers• Populated by Contextsources• Applications retrieve and

manipulate infospace data

•Operators defined on InfoSpaces• In – access policies, privacy tags,

notification

• Based on standard web technologies• Webservers (infospaces)• XML documents (context tuples; only tags and attributes)

• Out – access policies, privacy tags, notification, invisible mode, add privacy tag, interaction

• On – garbage collection, periodic reports, delete duplicated tuples

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ConFabConFab

<ContextTuple dataformat=“edu.school.building”datatype=“location”description=“location of an entity”entity-link=“http://myhost.com/~jdoe”entity-name=“John Doe”timestamp-created=“2003.Feb.13 16:06 PST”><Values>

<Value value=“523” /></Values><Sources>

<Source datatype=“location”link=“http://localhost/map.jsp”source=“Location Simulator”timestamp=“2003.Feb.13 16:06 PST”value=“523” />

</Sources><PrivacyTags>

<Notify value=“mailto:addr@mail.net” /><TimeToLive value=“1 day” /><MaxNumSightings value=“5” /><GarbageCollect>

<Where requestor-location=“not edu.school.building” />

</GarbageCollect></PrivacyTags>

</ContextTuple>

•Context tuples• Intrinsic attributes (e.g.

persons age)• Extrinsic (relationship)

attirbutes (person is in room)• Static attributes (email

address)• Dynamic attributes (location)

• Common parts• Dataformat, datatype, [entity link,]

values, • [Privacy Tags]

• Hints to the use of the information when it leaves the users infospace

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• Mobiware (Columbia University)• ALICE (Architecture for Location Independent CORBA Environments; Trinity College)• LIME (Washington University)• XMIDDLE (University College, London)• QoS-Aware Middleware and iMAQ (University of Illinois)• TSPACES (IBM Research)• GAIA – for smart spaces middleware (Univ. of Illinois)• CORTEX (Lancaster University)• ContextPhone• Project Aura• Solar• JCAF• Sentient Model• TEA framework

• CARISMA

• …

OtherOther

• ReMMoC• MobiPADs• Active Campus• Carmen• Smart-its• DiSUS• AGAPE

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Software ComponentsSoftware Components

•A component is a coherent package of software artifacts that

• can be independently developed and delivered as a unit, and• can be composed, unchanged, with other general components to

build something larger

•An interface is a description of a set of operations related to the external specification of a component. An interface consists of:

• a set of operations that a component needs to access in its surrounding environment (required interface),

• a set of operations that the surrounding environment can access on the given component (provided interface).

•An operation is unit of functionality implemented by a component which may map to:

• a method, • a function,• a procedure.

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DistributionDistribution

• Distributed processing / information sharing• Nearby, resulting in a context-aware system• Remote

• Simple sensors

• Wireless information devices• Online processing• Groups of devices• Limited resources (processing, storage, networking, power,

etc.)

• …

• Servers• High level of resources• Specialized

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Simple ApplicationSimple Application

•The stolen / forgotten mobile phone•Sensor

• Simple BT beacon• Attached to user• Transmit Freq. <= 1 Hz

•Reasoning• Beacon is with user• Mobile phone is owned by user• Should never be out of reach

=> stolen / forgotten•Application logic

• Sound / display alarm if stolen / forgotten

Reasoning

Beacon

Application

subscribe(select NULL where user = Michael, epoch = 1000)

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Advanced “Application”Advanced “Application”

•Inferring User Activity from 3D Acceleratometer•Steps

Data gathering

Pre Processing

Feature Extraction

Feature Selection

Classification

20 23.08.2006 michael.przybilski@cs.helsinki.fi

Inferring User Activity from 3D Inferring User Activity from 3D AcceleratometerAcceleratometer

Sensor

Preproc. FeatureExtr. FeatureSel.

Classifier

•Components

subscribe(select x, y, z from acceleratometer where user = Michael, epoch = 10)

subscribe(select variance, absoluteMagnitude from Feature-Selection where source = acceleratometer and user

= Michael, epoch = 10)

get(select activity from activity where user = Michael)

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Inferring User Activity from 3D Inferring User Activity from 3D AcceleratometerAcceleratometer

SensorPreproc. FeatureExtr.

FeatureSel.Classifier

Node 1

Node 2

•Sensor•220 000 samples (100 Hz)

•Preprocessor•Feature Extraction•Feature Selection

•Variance, absolute Magnitude of Acceleration

•Classifier•Simple linear classifier•300 samples for learning•300 samples for calibration

Nokia 6600BT Link L2CAPSensorbox

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Inferring User Activity from 3D Inferring User Activity from 3D AcceleratometerAcceleratometer

Variance

Absolute Magnitude

*International Conference on Artificial Intelligence 2005

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Other workOther work

•Agent-paradigm• Distributed preprocessing• Integration of policy-based privacy and security• Autonomous Intelligent Systems: Agents and Data Mining, 2005

•Evaluation of reasoning mechanisms• Software framework for remote data gathering• WS / EJB components / WEKA• Pervasive Systems and Computing, 2005

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Ongoing WorkOngoing Work

•Further integration• iMotes (NesC)• Series 60 / 80 Mobilephones (Symbian C++)• JBoss Application Server

•Communication• Ad-hoc (BT) and P2P (IP; 3G/GPRS / LAN)

•Energy saving by remote processing

•Reasoning mechanisms• Simple Bayesian networks, SVM

•Other Applications• Training management and heart-rate monitoring

25 23.08.2006 michael.przybilski@cs.helsinki.fi

Questions?Questions?