Maximizing Ad-Hoc network lifetime Yael Ochbaum Orit Varsano Supervised by Michael Segal.

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Presentation transcript:

Maximizing Ad-Hoc network lifetime Yael Ochbaum Orit Varsano Supervised by Michael Segal

Introduction 1 Problem definition 2 Project objectives 3 Algorithm presentation 4 5 Future Work CONTENTS

Ad-Hoc Network Characteristics  Collection of Independent nodes positioned in the plane  Nodes within range of each other communicate in peer to peer fashion  Nodes not in direct range communicate via intermediate nodes  No base station  No fixed infrastructure

Motivation Rescue operations Emergency scenarios Nature disastersMedical emergencies Fighting

The project objective  Sequence of nodes  Each node has one broadcast message to transmit to all other nodes

Constraints :  Each node is equipped with battery of limited power  The battery is not rechargeable since the nodes deployment  The battery charge is reduced after each transmission, depending on the transmission distance

The Project’s Goal Maximizing the number of successful broadcast transmissions while satisfying the battery constraints. The problem is considered as NP hard Text

Investigate and implement a heuristic algorithm which maximizes the number of successful broadcast message propagation while satisfying the battery constraints. Our Goal

Network life time The time from network initialization to the first node failure due to battery depletion

System Model  N wireless nodes positioned in a Euclidean plane  Each node is equipped with : omni directional antenna

Characteristic of Omni directional antenna System Model Every transmission by a node is received by all nodes that lie within its communication range

Broadcast Incremental Power (BIP)  Starts from the source and builds a minimum energy tree  Adds the cheapest from the set of uncovered nodes.  Either adds a new edge or increases an old one

Text Broadcast Incremental Power Checks the cheapest to connect from the source (0) Node 4: increment cost: C

Broadcast Incremental Power Checks from all uncovered nodes (3,7,9) the cheapest to connect to any Of the covered (0,4) Node 7. Connecting from 0 incremental cost : c07 – c

Broadcast Incremental Power Checks from all uncovered nodes (3,5,9) the cheapest to connect to any of the covered (0,4,7 ) Node 9: Connecting from 4, incremental cost : c49. Connecting from 0 incremental cost: c09-c07. Connecting from 7, incremental cost c

Broadcast Incremental Power Note : Edges point to connected nodes, don’t represent actual links. The links are represented by circles

The Node’s Function relaypassive Node

 Each node has a threshold value it can not pass.  Node which it’s battery charge reaches this threshold can not serve as a relay on the next session Our Improvement

The topologies we explore Mesh Full Graph Random Graph

Preliminary Results

Future Work  BIP is a centralized algorithm, which requires a global knowledge of the topology of the network.  We explore the local variation of the BIP algorithm.  In the local variation the node knowledge of the topology is limited only to k (any) hops from it