Middleware platform for sentient computing applications
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Middleware Platform for Sentient Computing Applications. Thirunavukkarasu Sivaharan, Maomao Wu, Gordon Blair, Adrian Friday, Paul Okanda. Computing Department, Lancaster University, UK. 2nd MiNEMA Closed Workshop@ Lancaster, 1 st Dec 2004. Overview of Presentation. Introduction

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Middleware Platform for Sentient Computing Applications

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Middleware platform for sentient computing applications

Middleware Platform for Sentient Computing Applications

Thirunavukkarasu Sivaharan, Maomao Wu, Gordon Blair, Adrian Friday, Paul Okanda.

Computing Department,

Lancaster University, UK

2nd MiNEMA Closed Workshop@ Lancaster, 1st Dec 2004


Overview of presentation

Overview of Presentation

  • Introduction

  • Sentient Objects

  • Research Challenges & Component Frameworks

  • Middleware Architecture

  • Sentient Vehicle Demonstrator

  • Conclusions

Lancaster University


Introduction 2

Introduction(2)

EU FET Project : CORTEX

  • Universidade de Lisboa (Portugal)

  • Lancaster University (United Kingdom)

  • Trinity College (Ireland)

  • Universität Ulm (Germany)

    Aims

  • Middleware support for constructing distributed mobile proactive applications based on real-time sentient objects

  • Proposes sentient object model to support the construction of mobile, context aware, decentralised ,autonomus ,proactive and collaborative applications such as intelligent vehicles and smart buildings.

  • A middleware for networked embedded systems

Lancaster University


Sentient object model 1

Sentient Object Model(1)

  • Sentient Object Model

    • System consists of environment and a set of sentient objects

    • Sentient objects are capable of independently sensing the environment, derive context and infer autonomous actions

    • Sentinet objects communicate using event channels to establish higher level context and thus cooperate with each other

Lancaster University


Sentient object 2

Sentient Object(2)

Lancaster University


Autonomous sentient vehicle application in manet

Autonomous sentient vehicle application in MANET

  • Autonomous navigation of vehicles from a source to destinations

  • Cooperating vehicles in MANET

  • Context aware vehicles

Lancaster University


Some of the research challenges addressed

Some of the research challenges addressed

  • Suitable Communication Model for MANET

  • Routing in mobile ad-hoc environment

  • Context-awareness

  • End-to-End QoS and Fail safety

  • Run time and deployment time reconfigurations

Lancaster University


Component framework based reflective middleware

Component Framework based Reflective Middleware

  • Publish-Subscribe Component framework (CF)

  • Multicast CF

  • Context CF

  • Resource Management CF

Lancaster University


Why component framework based middleware platform

Why Component Framework based Middleware Platform?

  • Middleware is engineered as family of Component frameworks (CF) using Reflection and component technology

  • Each CF addresses specific research areas

  • Component Frameworks are highly configurable and dynamically reconfigurable (with the granularity of a component)

  • Clear separation of concerns

  • Adaptable to diversity of CORTEX applications

  • Reduction of memory footprint

  • CFs are implemented using Lancaster’s OpenCOM reflective component technology

Lancaster University


Middleware architecture

Middleware Architecture

Sentient

Objects

Sentient

Objects

Context CF-

Sensor Fusion

Inference Engine

M

I

D

D

L

E

W

A

R

E

Programming Interfaces

Publish-Subscribe CF- (for MANET)

Timely Computing

Base

Group Communication CF-( Ad-hoc Multicast )

Payload Channel

TCB control channel

WLAN 802.11b (ad-hoc), Windows CE

Middleware Configuration for MANET

Lancaster University


Publish subscribe cf 1

Publish-Subscribe CF(1)

  • Communication model inspired by STEAM

  • Implicit event model

  • Sender & receiver based event filtering

  • Subscription Language supports subject, content & context based event filtering

  • Supports distance based context filtering & extensible to other contexts

  • XML based generic events

  • Events transported via selectable Multicast protocol

Lancaster University


Publish subscribe cf 2

ISubscribe

IDispatch

IPublish

Subscriber

Dispatcher

Publisher

Notifier

ISOAPMessaging

IFilter

IApplicationNotify

SOAP Messaging

IFilter

Filter

Filter

ISOAPTransport

Receptacle

SOAPtoMulticast

Interface

IMulticast

Multicast

Publish-Subscribe CF(2)

Lancaster University


Multicast cf

Shared memory based

IP Multicast

Probabilistic Multicast

Multicast CF

  • Underlying event Routing Protocol is based on multicast

  • The multicast protocol for ad-hoc networks is a probabilistic, stateless and multi-hop protocol

  • We offer this service in the form of a component framework.

Lancaster University


Context cf 1

Context CF (1)

  • Sensor capture and fusion

    • Multivariate Gaussian modelling

    • Bayesian networks

    • Dead-reckoning

  • Inference engine

    • A program that reasons about a set of rules (a knowledge base) in order to derive an output.

    • The knowledge is encoded as a set of production rules, contexts are represented as “fact”.

    • CLIPS – C Language Integrated Production System, its internal implementation is based on RETE net.

Lancaster University


Context cf 2

Context CF (2)

  • CLIPS rule sample

  • The paradigm facilitates uniform treatment of both context and QoS

    • Rules to trigger adaptations and actuations based on changes in measure of QoS data

  • CLIPS DLL and OpenCOM component for WinXP and WinCE

(defrule rule-obstacle-near "CLIPS rule for obstacle near"

(car-id (id ?id))

?f1 <- (obstacle (distance near))

=>

(retract ?f1)

(publish ?id stop)

)

Lancaster University


End to end qos management and fail safety timeliness requirement

End-to-End QoS Management and Fail Safety- Timeliness requirement

  • How can this be achieved?

    • Enforcing timely perceptions of the environment and timely actuations on it.

    • Which means timely event delivery and awareness of QoS of the event channels used for inter-sentient object communication

  • The key issue in uncertain and highly dynamic environments is that timing bounds for distributed actions may be violated because of timing failure

Lancaster University


End to end qos management and fail safety timeliness requirements

End-to-End QoS Management and Fail Safety-Timeliness Requirements

  • We model the uncertainty of timely event dissemination via event channels using a dependable timing failure detection service.

  • This service is provided by University of Lisboa’s Timely Computing Base (TCB)

  • TCB facilitates to construct distributed event channels with timing bound specification

  • This enables publisher or subscriber to be aware of the timing failures of event channels

  • Thus providing awareness of timing failure probability for a given required coverage

  • Fail safety is achieved by switching to fail-safe state as soon as QoS specifications are violated.

Lancaster University


Autonomous sentient vehicles demonstrator

Autonomous Sentient Vehicles Demonstrator

  • Two Sub problems

    • Cooperative behaviour without human control

    • Autonomous vehicle navigation from a given source to pre-determined destination

  • Vehicles Objectives

    • Travel along a given path( virtual circuit-VC) defined by set of GPS waypoints and bearings.

    • Every vehicle that travels on the VC cooperate with other vehicles to avoid collisions and travel safely

    • Obey external roadside traffic lights.

    • Give way to pedestrians who cross the road.

Lancaster University


Location aware cooperating sentient vehicles

Location aware Cooperating Sentient Vehicles

Satellites

Car publishes on Carcontrol channel: Event Packet: <car status, Location>

Car publishes on Carcontrol channel: Event Packet: <car status, Location>

Car subscribes to: CarControlChannel &

Receives events from other cars

Car subscribes to: CarControlChannel &

Receives events from other cars

IEEE 802.11b(ad-hoc)

---Event Channel---CarControlChannel

Car A

Car B

4m

OC BEHIND

OC CLOSE( 4m)

OC FAR(4- 10m)

OC VERY FAR

OC BEHIND

OC CLOSE

Other Car’s location context w.r.t Car B

Other car’s location context w.r.t car A

OC – Other car

Lancaster University


Pedestrian detection

Non event publishing obstacle

Ultrasonic sensors

Ultra sound waves

Pedestrian detection

  • Obstacle Sensing Service: Consumes raw ultrasonic sensor data and fuses using a suitable algorithm (reliable, timely-unreliable, Gaussian, …) to derive higher level obstacle distance context such as NEAR , FAR , NOOBJECT.

Lancaster University


Middleware platform for sentient computing applications

Inference Service

Obstacle Sensing Service

Location Sensing Service

Direction Sensing Service

GPS Fusion 2

Component

Ultrasonic Fusion 2

Component

GPS Fusion 1

Ultrasonic Fusion 1

Compass Fusion 1

CLIPS Inference Engine

Speed

Actuator

Ultrasonic sensor

Example: The Car Sentient Object & Context CF

Steer

Actuator

GPS sensor

Consume

Produce

Sentient object

Sentient object

Digital Compass

sensor

Interface

receptacle

Lancaster University


Sentient vehicle test bed

Sentient Vehicle Test Bed

Lancaster University


Cont d

Cont’d

Lancaster University


Cont d1

Cont’d

Lancaster University


Middleware platform for sentient computing applications

Demo Settings

Lancaster University


Middleware platform for sentient computing applications

Waypoint 3

Waypoint 2

Traffic Light

Waypoint 4

Waypoint 1

Virtual Circuit

Lancaster University


Demo video

Demo Video

Lancaster University


Concluding remarks

Concluding Remarks

  • The sentient object model

    • has proved to be valuable programming abstraction for the development of real-time, cooperative, context-aware applications.

  • The component-Framework based Middleware approach

    • offers benefits of flexible configuration and reconfiguration of the middleware components

  • The middleware architecture

    • also provides the management of non-functional concerns such as timeliness and reliability properties.

  • Our middleware is reusable

    • we are keen to investigate the generality of our approach by applying our middleware to other application domains involving embedded autonomous components.

Lancaster University


Thank you

Thank You

Questions

Lancaster University


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