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An Innovative Architecture for Context Foraging. Vassileios Tsetsos and Stathes Hadjiefthymiades Pervasive Computing Research Group Dept of Informatics and Telecommunications National and Kapodistrian University of Athens. June 29, 2009 @ MOBIDE ’09, Providence, Rhode Island.

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an innovative architecture for context foraging
An Innovative Architecture for Context Foraging

Vassileios Tsetsos and Stathes Hadjiefthymiades

Pervasive Computing Research Group

Dept of Informatics and Telecommunications

National and Kapodistrian University of Athens

June 29, 2009 @ MOBIDE ’09, Providence, Rhode Island

introduction motivation
Introduction & Motivation

Nomadic computing

Embedded devices with limited resources

Frequent node relocation / ad hoc communications

Broadcast-based data dissemination

Context-aware applications

A realistic assumption: not all nodes have sensors but all nodes require context inference

Context Foraging: efficient collaborative sensing and distributed context inference

Cyber Foraging

Context Foraging

Knowledge Foraging

context modeling
Context Modeling




User Situation





Declarative context description

Action Rules:

Fire  BroadcastAlert (100)

Situation Classification Rules (SCR):

Temperature>80 ^ Humidity<10  Fire (100, 10)


Spatial Validity

Temporal Validity



User Context





vali : property of Context class Ci

overall architecture
Overall Architecture
  • Nodes are moving in random trajectories
  • Nodes have location sensors
  • Short range communications: WiFi, WiseMac, DSRC, IEEE 1609 WAVE, ZigBee
  • Not all nodes have sensors
  • Nodes are willing to cooperate


Nomadic Applications

CR: Context Requestor

CP: Context Provider

CRel: Context Relay

Context Modeling

& Reasoning



Context Foraging



Short Range





Node Architecture

context requestors
Context Requestors

Nodes that require context values not locally available

periodically generate & disseminate Context Requests

Context Request

CReq := vali op Vi Viє R(Ci), op є{>, <, =, <=, >=}

Spatial validity: the maximum valid range

Temporal validity: the period of request retransmissions

context request formation dissemination
Context Request Formation & Dissemination

Local condition

Remote condition


Temperature>80 ^ Humidity<10  Fire (100, 10)

Spatial Validity

Temporal Validity


Humidity<10 (100, 10)








CReq is retransmitted every 10 time units

and within a range of 100 space units


SVCReq = 100

context providers
Context Providers
  • Nodes with sensors
  • They have an index structure that is used:
    • as a registry of all event filters received through context requests,
    • as a mechanism that matches incoming sensor values with event filters (context request conditions)
  • Index resembles a message forwarding engine of content-based network routers
  • A context request is always decomposed into atomic requests before registered in the index
  • Context Response
    • CRes:= vali = V
    • Spatial validity: equal to the request’s value
context providers index
Context Providers’ Index

1. Context Request

(Event filters)

2. Sensor value

Humidity < 10

3. Context


Humidity = 7

Humidity = 7

The responses are aggregated

context relays
Context Relays

They just forward messages they have not forwarded before

They may or may not be interested in the forwarded message contents

notes on spatial temporal validity
Notes on spatial/temporal validity
  • The requestor leaves the region after it has sent a Context Request
    • CPs transmit responses until the respective filter timeouts expire
    • The responses have spatial validity
  • CPs with registered event filters go away from the requestor
    • Time validity also resolves this problem
    • However, the new neighborhood may be interested in the responses as well
lazy context requesting
Lazy Context Requesting

In many cases a situation may never occur or may occur only very seldom  context foraging scheme is not probably the most efficient solution

(Temperature>80) ^ (Humidity<20) ^ (Smoke=true)  Fire

Remote Condition

Local Condition

Local Condition

  • If Humidity >20 or Smoke = false then it makes no sense to request Temperature values
  • Proposed Solution:
    • Each SCR has a trigger level:
    • satisfied local conditions / all conditions
    • Context requests are only sent when this level exceeds a threshold that depends on the criticality of the respective application  affects the situation detection sensitivity
performance evaluation setup
Performance Evaluation Setup
  • Metrics:
    • Average Situation Detection Ratio (ASDR)
    • Number of exchanged messages
  • Comparison with a Polling Scheme
performance results iii
Performance Results III

Lazy Context Requesting

CPol also uses Lazy Requesting

ASDR’ is a more fair metric

Real sensor values are expected to give higher ASDR values

performance results iv
Performance Results IV

Without Lazy Requesting

# exchanged messages: ~3-10 times lower

ipac platform
IPAC Platform

Integrated Platform for Autonomic Computing (EU FP7)

Middleware, service creation and execution environment

Collaborative sensing, plug ‘n’ play sensors, short range communications

Probabilistic broadcasting and epidemic information dissemination


Autonomic networked objects in industry, Intelligent Transportation Systems, Crisis Management

Context models and rules implemented through standard Prolog

JIProlog engine was used (J2ME-compliant)

conclusions future work
Conclusions & Future Work
  • A framework for fully ad hoc collaborative context awareness
  • It is based on pub/sub principles but tailored to the nomadic computing setting
  • In all scenarios tested, the number of messages is much lower than the polling-based scheme, with insignificant reduction in the situation detection capability of the nodes
  • Open issues
    • Context caching
    • Context aware configuration of time validity
    • Spatial validity without absolute positioning