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A Context Discovery Middleware for Context-Aware Applications with

Heterogeneous Sensors

Yu-Min Tseng

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Sensor & Sensor Network

Deployed freely in the environmentContext information may be sensed & extracted by various sensors - Temperature, pressure, location, audio, image…Heterogeneous (Different sensing & computing capabilities)

Sensor mote are named via high-level descriptionsSelf-organization, power efficiency, large scale, reliabilityNeed ad hoc interaction for energy conservation & operation efficiency

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The fundamental issue - How to deploy a sensor network that provide ad hoc comm. between sensors - An atomic ad hoc talk is end-to-end communicationBriefly - A robust & efficient ad hoc data-centric routing infrastructure

Problem Statement

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Assumption

Each sensor is capable ofWireless comm.

•Only can talk to its geographical neighborComputationBuffering

Each sensor does not need GPS, MAC, or IP address supportTransmit requests & responses of sensory data only between those interested partiesOther nodes shouldn’t be involved, except those nodes that must relay messages

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Support data-centric routing, request can be directed easily & efficiently. This reduces the overhead of address mapping & directory lookup.Self-calibration, self-management, self-healing.

Assumption (cont’d)

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Data-centric Routing

Concept

Q: Prof. King’s cellular phone?

•A friend is contacted. Who ever taught by Prof. King

•The friend may ask his graduate classmate who joined the lab hosted by Prof. King

•The graduate student may ask the lab assistant

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Data-centric Routing (cont’d)

Numerical perspectives

Translate each query to a number

Search a given number by numerically approaching

Example

•Q: Search a given number N1=Prof. King’s cellular phone

•N2=the friend

•N3=the graduate student

•N4=the assistant

•N2 > N3 > N4 > … Nm = N1

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Data-centric naming

A sensor is characterized by its meta descriptor about its sensory data

The meta descriptor is attribute-value pairs

Example

Data-centric Routing (cont’d)

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Data-centric Routing (cont’d)

Convert each sensor’s meta descriptor to a value by adopting a hash function (ex. SHA-1)

Requirement for the hashing

Generate a unique hashing value

•For naming various sensor

Uniform distribution

•Prevent overloading some particular sensors

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v0 v1v2v3

Reference

R/2

R/4

R/8

u1u2u3 v4

R/4

R/8

Leader

Data-centric Routing (cont’d)

Example:

Vo receive a request for V4

Vo V1

V1 V4

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Operations - Route

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Operations - Join

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Operations - Update

Cost(x, y) denotes the total energy consumed by routing arequest torwards y from xThe energy of signal consumed between 2 sensor is 1/d4, where d is the distance between the antennas

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Operations - Construct

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When to trigger a mote to update its discovery & neighbor tables?

1. A mote detects that leader stop forwarding requests

• Failure of link or motes

2. A node cannot communicate with its neighbor nodes

3. Periodical update

Maintenance

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Evaluation

1 ~ 5000 sensors

Uniformly & randomly deploy over 210x210 meters square

Each sensor is randomly named

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Result

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Result (cont’d)

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Result (cont’d)

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Optimization

The logical network may not follow the actual network topologyExample

A given named value u not appear in mote vIf the cost of path from v to u is relatively economic than the one from v to a leader representing mote v’s i-th discovery scopeMote u replace the leader

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Optimization (cont’d)

Each mote v locally eliminates loops

Ex: a b c a d c e d f a d c e d f a d f

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It is possible that multiple leaders & neighbors appeared in he discovery & neighbor tables in a mote are the same

The path to the same leaders & the neighbors may not have same route

Replace those with the one have the minimally routing cost

Optimization (cont’d)

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Summary

Heterogeneity Sensor motes are named via high-level descriptions

Data-centric

Discovery is based on named dataNamed data resolution and routing are integrated

Robustness

Each mote (a)periodically refreshes its discovery and/or neighbor tablesMultiple routes are constructed by having multiple leaders for a given particular discovery scopeMultiple neighbors in a mote are also maintained

Large-scale

Each mote only maintain O(log n) leadersThe discovery overhead is O(log n) in terms of messages and energy consumptionVicinity motes help the discovery

Maintenance-free

See the operation algorithm (Join, Construct, Update)Each mote refresh its discovery and neighbor tables

Energy-constrained

Via the vicinity discovery