Examining suitable solutions to optimize energy consumption in wireless sensor networks using memetic algorithm

Number of pages: 96 File Format: word File Code: 32056
Year: 2016 University Degree: Master's degree Category: Electrical Engineering
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    Dissertation for Master's Degree

    Trend: Power Electronics

    Abstract

    One ??of the important design challenges in wireless sensor networks (WSN) is to extend the lifetime of the system (node), while maintaining the quality of service. Acceptance for applications achieved. Extending the life of the node is directly related to reducing energy consumption. In WSN, each sensor node works with battery power, and in most cases, especially in remote and hostile environments, it is not easy to recharge and replace. Due to the limited capabilities of sensor nodes, it is usually desirable that the WSN should be expanded with high density and therefore redundancy can be used to increase and optimize the network lifetime. In this thesis, we first examine the researched patterns with the aim of increasing the lifetime of wireless sensor networks, then we present an effective algorithm for lifetime optimization and self-stabilization to enhance the lifetime of wireless sensor networks. Our algorithm seeks to create resistance by maintaining the necessary set of operating nodes and replacing damaged nodes if needed. We present some theoretical and simulation results that fully demonstrate the usefulness of the proposed algorithm.

    Keywords: lifetime optimization, sensor networks, self-stabilizing reliability algorithm, Weibel distribution

    Chapter One

    general

    1-1- Introduction

    A wireless sensor network [1] (WSN) consists of a large number of sensor nodes that are densely distributed around the desired physical phenomenon. These networks provide at least the computational possibility and some sensory tools to sense parameters such as temperature, light, vibration, sound, radiation, humidity, etc. have  The evaluation parameters of wireless sensor networks (WSN) are:

    Lifetime

    Coverage range

    Cost and ease of use

    Response time: real-time applications

    Accuracy: environmental applications

    Security

    Effective sampling rate

    Despite the numerous capabilities these nodes have, but because their energy is supplied by batteries with limited power, their lifespan will be limited. In fact, the energy limitation of the nodes and the lifetime of the network is one of the important challenges on the way of these networks. Among the various factors of energy consumption, data routing is considered one of the most important factors. In this thesis, relying on the topic of reducing energy consumption and increasing the lifespan of wireless sensor networks, we will explain and examine these challenges. Small and relatively cheap sensors that communicate with each other through a wireless network. These networks, which are called wireless sensor networks, have become a suitable tool for extracting data from the surrounding environment and monitoring environmental events, and their applications in domestic, industrial and military fields are increasing day by day. Wireless sensor networks are a collection of small sensor nodes that have the ability to monitor and sense their surroundings and send the sensed data to a main station.  The limited energy available in the nodes is the basic challenge of sensor networks, which affects the survival of the network. On the other hand, due to the presence of a large number of sensors in the network or the impossibility of accessing them, replacing or charging the sensors' batteries is not practical. For this reason, providing methods for optimal energy consumption that will ultimately increase the life of the network is strongly felt.Previous researches have shown that by organizing network nodes in clusters, it is possible to increase the energy efficiency and increase the life of the network. In most researches, the time elapsed until the death of the first or last node of the network is called network life. 1-3- Importance and necessity of research Wireless sensor networks, which usually contain hundreds or even thousands of inexpensive sensor nodes, are an ideal solution for various monitoring and surveillance applications, including traffic control, health care, environmental monitoring, battlefield surveillance, etc.  Considering the limitations of sensor nodes in terms of energy resources, the unattended expansion of sensor nodes in the operational environment, as well as the nature of applications of wireless sensor networks, establishing security in these networks is an important and at the same time difficult issue. Since the care of sensor nodes has a close relationship with their lifespan and the lifespan of sensor networks is usually short and the reason is the limitation of power supply energy, providing suitable structural models and providing management methods and power-aware algorithms with the aim of increasing the lifespan of sensor networks are among the important research topics.  In this thesis, we examine these appropriate solutions and algorithms.

    1-4- Research objectives

    This research was formed in order to achieve the following goals:

    1-4-1- Main objective

    Identify and review effective solutions to optimize energy consumption using Memetic Algorithm.

    1-4-2 - Sub-goals

    1- Identifying effective solutions to increase the lifetime of the network as a result of balancing energy consumption.

    2- Investigating the importance of optimal energy consumption in wireless sensor networks.

    1-5 research questions

    1-5-1- The main question

    How is it possible to optimize energy consumption using the memetic algorithm?

    1-5-2- Sub questions

    1- What is the most effective result of balancing energy consumption in the wireless network?

    2- How does congestion control increase the lifespan of a wireless sensor network?

    1-6- Research hypotheses

    1-6-1- Main hypothesis

    Congestion control in the network will result in balancing the energy consumption, in which case we will see an increase in the network lifespan and optimization of energy consumption.

    1-6-2- Sub-hypotheses

    1- Creating a balance in energy consumption leads to longer network life.

    2- Congestion control in wireless sensor networks by reducing energy consumption leads to the longevity of wireless sensor networks.

    1-7- Definitions Terms

    1-7-1-Definition of network life

    The time elapsed until the death of the first or last node of the network is called network life.

    1-7-2- Definition of memetic algorithm

    Memetic algorithm is a search strategy among a set of optimization factors that is Competition or cooperation are placed together. In the memetic algorithm, we have a set of solutions to solve the problem. In computer networks, when there are many packets in a part of the subnet, the performance decreases. This situation is called crowding.

    1-8- Research design and data analysis method

    Given that the purpose of the research is to investigate effective methods to optimize energy consumption using the memetic algorithm, it is a field study and a review of related articles in this field. For this purpose, various sites including Elsevier and Springer are searched.

    Since this research is based on the issue of minimizing energy consumption, the software of the article has been used for data analysis.

  • Contents & References of Examining suitable solutions to optimize energy consumption in wireless sensor networks using memetic algorithm

    List:

     

    Abstract 1

    Chapter 1 Generalities 2

    1-1- Introduction 3

    1-2- Statement of the problem 4

    1-3- Importance and necessity of research 4

    1-4- Research goals. 5

    1-4-1- main objective 5

    1-4-2 - secondary objectives 5

    1-5 research questions 5

    1-5-1- main question 5

    1-5-2- secondary questions 5

    1-6- research hypotheses 5

    1-6-1- main hypothesis 5

    1-6-2- Sub-hypotheses 6

    1-7- Definitions of terms 6

    1-7-1- Definition of network life 6

    1-7-2- Definition of memetic algorithm 6

    1-7-3- Definition of congestion in the network 6

    1-8- Research design and data analysis method 6

    Chapter Two Literature and Research Background 7

    2-1 History of Wireless Sensor Networks 8

    2-2- General Features of Wireless Sensor Networks (WSN) 13

    2-2-1 Communication Structure of Sensor Networks 14

    2-2-2 Design Factors 14

    2-2-3 Failure Tolerance 14

    2-2-4 Expandability 15

    2-2-5 Production cost 15

    2-3- Hardware features 15

    2-4 Unique features of a wireless sensor network (WSN) 17

    2-5 Applications of wireless sensor networks 18

    2-5-1 Creating security 18

    2-5-2 Environment and Living Organisms 19

    2-5-3 Industry 19

    2-5-4 Traffic Control 19

    2-6 Challenges of Wireless Sensor Networks 20

    2-7 Discussable Concepts and Research in Wireless Sensor Networks 23

    2-7-1 Hardware Bottlenecks 23

    2-7-2 Topology 23

    2-7-3 reliability 24

    2-7-4 scalability 24

    2-7-5 cost price 25

    2-7-6 environmental conditions 25

    2-7-7 communication media 25

    2-7-8 power consumption of nodes 25

    2-8 concept of routing in Wireless sensor networks 26

    9-2 routing challenges in wireless sensor networks 28

    Chapter 3 congestion control and proposed methods for routing in wireless sensor networks 33

    3-1 Introduction 34

    3-2 Congestion in the network 34

    3-3 Congestion control 35

    3-4 Difference between control Congestion and Flow Control 36

    3-5 General Principles in Flow Control 36

    3-6 Congestion Prevention Policies 37

    3-7 Routing Methods 38

    3-7-1 Sending Flood Method 38

    3-7-2 Clustering-Based Methods 41

    3-7-3 Chain-Based Method 46

    3-7-4 methods based on the residual energy of each node (aware of energy) 48

    4th chapter of simulation 51

    4-1 introduction 52

    4-2 basic principles and sensing model 54

    4-3 proposed algorithm 55

    4-4 analysis of distribution of future lifetimes 56

    4-5 Node wake-up rate 58

    4-6 Problem formulation 60

    4-7 Self-stabilizing algorithm 61

    4-8 Self-stabilizing proofs 61

    4-9 Theory analysis: message complexity analysis 62

    4-10 Reliability analysis 65

    4-11 Overview of protocols 4-11-1 PEAS algorithm 67

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Examining suitable solutions to optimize energy consumption in wireless sensor networks using memetic algorithm