protocols for self organisation of a wireless sensor network

Presented by

Saatviga S.

PROTOCOLS FOR SELF-ORGANIZATION OF A

WIRELESS SENSOR NETWORKPublished in “Personal Communications, IEEE, vol 7, no

5, 2000”

Authors

Katayoun Sohrabi B.S & M.S degrees in Electrical Engineering, University of Missouri, Rolla.

Ph.D. University of California, Los Angeles

Vishal Ailawadhi B.S. and M.S. degrees in electrical engineering, Ph.D. in electrical

engineering, University of California, Los Angeles

Jay L. Gao B.S. and M.S. degrees in electrical engineering, Ph.D. in electrical

engineering, University of California, Los Angeles

Gregory J. Pottie B.Sc. in engineering physics, Queen’s University, Kingston, Ontario,

Canada. M.Eng. And Ph.D. in electrical engineering from McMaster

University, Hamilton, Ontario

Road Map

Wireless Sensor Network – A General Scenario

Design Challenges Involved

Related Wireless Network Models

The Research Problem

Link Layer Issues

Mobile MAC Issues

Protocols for Wireless Sensor Networks

Multihop Routing

Cooperative Signal Processing

Conclusion

Wireless Sensor Network – A General Scenario

Internet

Wireless Sensor Network

TargetSensor Node

Sink Node

User

Sensor

Actuator In

terf

ac

e

Signal processing for event detection

Control

Processing

Event Classification

and identification

Wireless networkinterface

WINS Sensor Node Architecture

Design Challenges Involved

Hardware MEMS Sensor Technology Digital Circuit Design & System Integration Designing Low-power RF front-end and circuitry

Wireless Networking Robust & Energy-Efficient Communication Channel Access, Routing, Mobility Management

Applications Detection, Data Collection & Signal Processing

Related Wireless Network ModelsMobile Ad hoc Network

Cellular Network

Mobile NodeWireless link

Mobile Cluster Head

Wired link

Wireless link

Mobile User

Stationary Base Station

Research Problem

Energy Consumption – sensing, data processing and

communications

Communications in a network consumes lot of energy

Trade-off between data processing and wireless

communications

More local processing done in sensors

Message overhead should be reduced

Need For Highly Localized And Distributed

Algorithms For Data Processing And Networking

Link Layer Issues

Formation of topology & Channel Access

Contention/ Explicit Organization based Channel Access

TDMA/FDMA/CDMA schemes

Transceivers have to monitor channels at all times

Expensive in the context of sensor networks

Organized Channel Access

Discover neighbors and then assign collision-free channels

Hierarchical structure

Network-wide Synchronization

Centralized / Distributed Channel Assignment

Mobile MAC Issues

Provides connectivity to mobile sensors as they interact with

static networks

It has to adhere to the stationary network constraints

Mobility Management

MANET – Through Mobile Cluster Heads

Cellular Network – Hand-off Techniques by Base stations

Sensor Networks

Consists of mobile nodes and stationary nodes

Must focus on energy consumption than anything else

What is the Mechanism/Algorithm to handle mobility????

Protocols that perform ORM Network Start up & Link layer organization

SMACS (Self-Organizing Medium Access Control for Sensor Networks)

Stationary Wireless Nodes and Mobility Management EAR (Eavesdrop-And-Register) algorithm

Multihop Routing SAR (Sequential Assignment Routing) algorithm

Signaling & Data Transferring SWE (Single Winner Election) algorithm MWE (Multi-Winner Election) algorithm

SMACS It is an infrastructure building, distributed protocol that forms

a flat topology Neighbor discovery and channel assignment phases are

combined TDMA slots are assigned to links and then they operate on

different frequencies To reduce likelihood of collisions

AD

C

B

F

Link-layer self-organizing procedure

TYPE

1

TYPE1

TYPE2

TYPE

2

TYPE

3

TYPE3

TYPE4Initial listening

time

Node B

Node C

D and A find each other

B and C find each other

Trans. SLOT

Rec. SLOT

Td

Ta

fx fx

fx fx

Tb

Tc

fy

fy

T frame

Node D

Node A

Node B

Node C

EAR Algorithm A Typical Wireless Sensor Network

Attempts to offer continuous service to these mobile nodes under both mobile and stationary constraints.

Adheres to mobile nodes’ limited power constraints within the stationary network

Mobility Management

Wireless link

Mobile sensor

Stationary sensor

Signaling Method Broadcast Invite (BI)

Stationary node transmits invitation to surrounding neighbors –Stationary MAC protocol

Mobile node extracts SNR, node ID, transmitted power etc and holds it in the registry

Mobile Invite (MI) Mobile node responds to BI to request a connection

Mobile Response (MR) Stationary node accepts the connection and selects the slots for

communication Adds it to the registry

Mobile Disconnect (MD) Disconnection of nodes are determined through predefined thresholds

Timeouts for limiting errors

Routing

Multihop Routing

AODV (Ad Hoc On Demand Distance Vector)

TORA (Temporally Ordered Routing Algorithm)

Power –Aware Routing Algorithm

Minimum energy/packet

Minimum cost/packet

SAR Algorithm

Path Selection – Energy Resource, QoS , Priority of Packet

Minimizes average weighted QoS metric

Focus on High

Mobility

Focus on Energy

Efficiency

Cooperative Signal Processing

A form of hierarchical information processing where raw sensor

data is first collected and processed by individual nodes to

generate a parametric or filtered version of the original data,

and later gathered at a single location for combined processing.

Eliminates the communication cost for relaying the raw data to

some entity outside of the sensor network for processing.

Adaptive Local Routing Algorithm (SWE, MWE)

Coherent and

Non-Coherent event-based cooperative signal processing.

Noncoherent Cooperative Function

Raw data is often parameterized and or highly compressed

Data traffic is lower

Energy minimization is best achieved by reducing the overhead in the algorithm itself.

Communication cost can be significantly reduced

Processing Network Formation

• Target Detection• Data Collection• Preprocessing

Phase 1

• Membership Declaration

Phase 2

• Central Node Election

Phase 3

SNR (Signal to Noise Ratio)

SWE ,ST

algorithm

SWE Algorithm

Routing information & Election information is piggybacked on the

Elect message so that a minimum-hop spanning tree can be built

from each sensor node to the eventual winner(s) of the election

Overhead-Delay Tradeoff

By the end of the SWE process, a minimum-hop spanning tree will

completely cover the network.

ST Algorithm

The routing algorithm computes a minimum-hop spanning

tree connecting each participating sensor to the winner(s)

of the election.

No additional complexity is added to the algorithm

complexity

Ultimately shortens the duration of the entire network

routing algorithm

Also cuts overhead by compressing election and routing

information into a single message.

Coherent Cooperative Function

Raw data is only mildly filtered before combined processing takes place

Data traffic is higher

Communication cost associated with relaying long data streams can be prohibitively high because of energy resource limitation

Focus is on finding the optimal processing node and the minimum energy routes.

MWE Algorithm

Limits the number of sensor nodes that provide data

Each node will now keep up to n of the best candidates

At the end of the MWE process, each sensor in the network has a set of minimum energy path to each SN

Total energy consumption to upload data from each SN to each node is computed

Formation Process for Coherent Routing

Test Simulation Implementation The simulation environment models each node as a

separate Parsec entity. The functionality of each layer, namely MAC, mobile MAC,

and the network layer, is implemented as a function inside the node.

Conclusion The algorithms exploit the low mobility and abundant

bandwidth, while coping with the severe energy constraint and the requirement for network scalability.

THANK YOU..

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