WIRELESS SENSOR NETWORKS

Rate Allocation and Network Lifetime Problems for Wireless Sensor Networks

ABBREVIATION AND CODES

NUM= Network Utility Maximization

SLP-PA= Serial LP With Parametric Analysis

NUM= Network Utility Maximization

LMM= Lexicographical Max-Min

WSN= Wireless Sensor Network

OPNET= Optimized Network Engineering Tools

GloMoSim= Global Mobile Information Systems Simulation Library

PARSEC= Parallel Simulation Environment for Complex Systems

OMNeT++= Written in C++

J-Sim= written in Java

GTSs= Guaranteed Time Slots

MOSS= Modern Operating Systems Simulators

HHR= Hop-By-Hop Reliability

HHRA= Hop-By-Hop Reliability With Acknowledgement

PA= Parametric Analysis

Abstract

The network duration and request performance are two primary, however conflicting, design objectives in wireless sensor networks. There is an essential tradeoff between network lifetime maximization and application performance maximization, latter being often correlated to rate at which application can send its data reliably in sensor networks. In this paper research study this tradeoff by investigating interactions between network lifetime maximization problem and rate allocation problem with reliable data delivery requirement. Severe bias on allocated rates of some sensor nodes may exist if only total throughput of sensor network is maximized, hence research enforce fairness on source rates of sensor nodes by invoking network utility maximization (NUM) framework. To guarantee reliable communication, research adopt hop-by-hop retransmission scheme. We formulate network lifetime maximization and fair rate allocation both as constrained maximization problems. We characterize tradeoff between them, give optimality condition, and derive partially distributed algorithm to solve problem. Furthermore, research propose an approximation of tradeoff problem using NUM framework, and derive fully distributed algorithm to solve problem.

Table of Content

Abstractii

ABBREVIATION AND CODESIV

CHAPTER 1: INTRODUCTION1

Outline of Study1

Background of research2

Rationale2

Aims3

Objectives3

Problem Statement4

Purpose4

Theoretical Frame work5

Limitation of Study5

Assumptions & Limitation6

Reliability6

Validity6

Ethical Concern7

OPNET SIMULATION10

CHAPTER 2: LITERATURE REVIEW15

Wireless Sensor Nodes15

Wireless Sensor Networks17

Related work19

Data Delivery Reliability In Sensor Networks21

System and threat model24

CHAPTER 3: METHODOLOGY26

Research Method26

Data Collection Method26

REFERENCES27

Abbreviation and Codes

NUM= Network Utility Maximization

SLP-PA= Serial LP With Parametric Analysis

NUM= Network Utility Maximization

LMM= Lexicographical Max-Min

WSN= Wireless Sensor Network

OPNET= Optimized Network Engineering Tools

GloMoSim= Global Mobile Information Systems Simulation Library

PARSEC= Parallel Simulation Environment for Complex Systems

OMNeT++= Written in C++

J-Sim= written in Java

GTSs= Guaranteed Time Slots

MOSS= Modern Operating Systems Simulators

HHR= Hop-By-Hop Reliability

HHRA= Hop-By-Hop Reliability With Acknowledgement

PA= Parametric Analysis

CHAPTER 1: INTRODUCTION

Outline of Study

Using OPNET, we have coded various WSN specific MAC protocols, protocols that dictate how packets are transmitted in networks, in order to evaluate various WSN scenarios. The goal of model was to use obtained hardware characterization to develop an energy model in OPNET which should allows evaluating efficiency of various MAC protocols and hardware technology. By knowing how much energy is available for each mote, usually 2 AA batteries, energy model accounts for how much energy motes consume which was used during in simulations to determine how many days would motes last before they deplete their batteries. The simulations are composed of 20 motes; in each simulation motes' utilize various MAC protocols under various traffic conditions. The simulations help in evaluating two things, how energy efficient motes are and how efficient various WSN MAC protocols are. The developed models, both hardware and MAC protocol models, can be used in future in evaluating new generation ...