ABSTRACT
A Mobile Ad hoc Network (MANET) is a network consisting of a set of mobile nodes capable of communicating with each other without base station. For Quality of Service (QoS) to be maintained, MANET must run consistently without power interruption. Also, the wireless network situation of MANET had made the QoS unpredictability less guaranteed and highly susceptible to errors.
MANETs are wireless networks that run usually on battery power. The power supplied by the battery is limited and tends to run out after a period of time. This poses a serious challenge for the nodes in MANETs. One major characteristic of the node is availability i.e., it should always be to receive and transmit communication to other nodes. If a node goes down, communication breaks down and the communication is disrupted. The availability of the nodes has an overall impact on the Quality of Service (QoS) that MANETs give. Once the nodes are not available when they are needed or if a node goes down while a communication is going on, thereby affecting the communication, the MANET is said to be unreliable, unpredictable and the QoS is said to be low tries to resolve the power challenge faced when using MANETs. The QoS of MANETs can only improve if the networks are working at their optimal capacity. This research would also cover current solutions for fixing the power problem and their effectiveness and also parts they are failing to address.
This research work proposed an energy efficient QoS enhancement scheme for mobile ad hoc network. The algorithm is inspired by particle swamp optimization technique with heuristic algorithm. QoS parameters that have been taken into consideration are throughput, delay, packet loss, and bandwidth utilisation.OPNET simulator has been used to evaluate the proposed concept.
Simulation results show that the packet increases from 20 to 1500 and the vehicular speed increases from 330v/h to 1300v/h. Hence, this result produces better result than the existing schemes.
The study concluded that three agents, namely message selection agent, message forwarding agent, and QoS factor calculating agent, have been introduced to govern and optimise the whole message transmission scheme. Through this method, a significant improvement in QoS factor can be achieved in comparison with the existing schemes.
Keywords: Mobile Ad Hoc Network, Nodes, Quality of Service(QoS), Hybrid Protocol, Packet loss,
delay, loss, jitter, bandwidth, battery power, throughput, OPNET.
Word Count: 295
TABLE OF CONTENTS
Content Page
Title Page i
Certification ii
Dedication iii
Acknowledgements iv
Abstract v
Table of Contents vi
List of Table vii
List of Figures viii
Abbreviations ix
CHAPTER ONE: INTRODUCTION
- Background to the Study 1
- Statement of the Problem 4
- Objective of the Study 5
- Motivation 5
- Research Question 5
- Significance of the Study 5
- Scope of the Study 6
1.8Operational Definition of Terms 6
CHAPTER TWO: REVIEW OF LITERATURE
2.0 Introduction 7
2.1 Generalities and Challenges in Adhoc Network 7
2.2 Applications of Adhoc Network 7
2.2.1 Data Communication in Adhoc network 8
2.2.2 Routing in Adhoc Network 9
2.2.2.1 Table Driven Protocol 9
2.2.2.2 On Demand Routing Protocol 9
2.2.2.3 Hybrid or Mixed Routing Protocol 10
Content Page
2.2.2.4 Unicast Routing Protocols 11
2.2.2.5 Multicast Routing Protocols 11
2.3 Challenges in Adhoc Network 11
2.4 Connection Stability in Wireless Adhoc Network 12
2.5 Quality of Service 13
2.5.1 Quality of Service in MANET 14
2.5.2 Factors influencing Quality of Service of Wireless Network 15
2.5.3 Quality of Service Routing 16
2.6 Major Challenges in MANET 17
2.7 Insect Societies to Network Protocols 18
2.8 Swarm Intelligence 18
2.9 Energy Efficiency in MANET 19
2.10 Application of MANET 20
2.11 Protocol Techniques for MANET 21
2.11.1 Routing Protocols for Mobile Adhoc Network 21
2.12 Various Techniques at different levels 23
2.12.1 Techniques employed in Power Reduction at the Physical Layer 24
2.12.2 Techniques at the Link Layer 24
2.12.3 Techniques at the Transport Layer 25
2.12.4 Techniques employed at the Medium Access Control Layer 25
2.12.5 Techniques applied at the Network Layer 26
2.12.6 Techniques at the Middleware and Application Layers 28
2.12.7 Other Approaches 28
2.13 Review of Works 37
CHAPTER THREE: METHODOLOGY
3.0Overview 49
3.1 Determination of Power Consumption Modes 49
3.2 Simulation Approach for Energy Conservation in MANET 51
3.3 Development of Routing Algorithm 52
Content Page
3.4 Development of Hybrid Routing Protocol 55
3.4.2 Adaptive PSO 57
3.4.3 Pseudocode of distributed PSO (DPSO) 59
3.4.5 Implementation with Heuristics Algorithm 61
3.4.6 Proposed Algorithm 63
3.4.7 Improved Swarm Optimization Algorithm 64
3.4.8 Stochastic Contriction Swarm Optimization Algorithm 65
3.5 Evaluation based on Performance Metric 70
CHAPTER FOUR: DATA ANALYSIS, RESULTS AND
DISCUSSIONOF FINDINGS
4.1 Data Analysis 75
4.2 Simulation Environment 75
4.3 Simulation Setup 76
4.4 Result Presentation for the Routing Protocols 77
4.5 Result Analysis for Highest Degree Heuristic Algorithm 81
CHAPTER FIVE: SUMMARY, CONCLUSION AND
RECOMMENDATIONS
5.1 Summary 90
5.2 Conclusion 90
5.3 Recommendations 90
References 92
Appendices 95
LIST OF TABLE
Table Page
4.1The network simulation environment setup for the developed algorithm. 88
LIST OF FIGURES
Figure Page
3.1 Mapping with nature to Practical Simulations 58
3.2 Algorithm Flowchart 60
3.3 Proposed Algorithm 71
3.4 Flowchart of the Proposed Method 79
3.5 Flowchart of PSO based Keysteam Generation 81
4.1 Network Topology at start up 89
4.2 Network in run mode 89
4.3 Data send chart for Diffserve Algorithm 90
4.4 Data received chart for Diffserv Algorithm 90
4.5 Data send chart for our Algorithm 91
4.6 Data received chart for our Algorithm 91
4.7 Comparison graph showing the Improvement in QoS 92
4.8 Power Analysis of QoS for Manet at 1300v/h 93
4.9 Semi Poisson Distribution at 330v/h 94
4.10 Best points of Segmentation 95
4.11 Average PC and Latency at 330v/h 96
4.12 Average PC and Latency at 1300v/h 97
4.13 Result with Solar Power at 330v/h 98
4.14 Result with Solar Power at 1300v/h 99
4.15 Variation of Probability of Collision with PSO 100
4.16 Variation of Latency with PSO 101
ABBREVIATIONS
ABCO Artificial Bee Colony Optimization
ACO Ant Colony Optimization
AODV Adhoc On demand Distance Vector Routing
AOMOV AdhocOn Demand Multipath Distance Vector
AP Access Point
AQEC Adaptive Quorum Based Energy Conserving
ARPA Advanced Research Projects Agency
ARQ Automatic Repeat Request
BREQ Bandwidth Request
BREP Bandwidth Reply
BRP Bandwidth Reservation Protocol
CBR Constant Bit Rate
CBRP Cluster Based Routing Protocol
CGPM Communication Grounded Power Management
CHG Clustered Head Gateway Node
CQPS Consecutive Quorum Based Power Saving Protocol
CSMA Carries Sense Multiple Access
DF Distance Factor
DSDV Destination Sequence Distance Vector
DSR Dynamic Source Routing
EA Energy Aware
ECBRP Efficient Cluster Based Routing Protocol
ECMAC Energy Conserving Medium Access Control
EF Energy Factor
EPAR Efficient Power Aware Routing
EOEDR Extended Optimal Energy Drain Rate
ESSDSR Efficient Energy Saving and Survival DSR
FAR Flow Augmentation Routing
FEC Forward Error Correction
FERA Fair end to end Bandwidth Allocation
FSR Fisheye State Routing
GA Genetic Algorithm
GP Genetic Programming
HARP Hybrid Adhoc Routing Protocol
HQS Hyper Quorum System
IEEE Institute of Electrical and Electronic Engineers
IP Internet Protocol
NC Network Centrality
NIC Network Interface Card
LAMP Location Aware MAC Protocol
LAN Local Area Network
LARI Location Aided Routing Protocol
LEAR Localized Energy Aware Routing
MAC Medium of Access Control
MANET Mobile Adhoc Network
MDR Minimum Drain Rate
MESDSR Modified Energy Saving Dynamic Source Routing
MTPR Minimum Transmission Power Routing
NCBPE Normalized Current Best Performance
NS-2 Network Simulator-2
ODMRP On Demand Multicast Routing Protocol
OFAA Optimal Fully Adaptive Asynchronous
OLSR Optimized Link State Routing
OMM Online Maximum Minimum
PAMAS Power Aware Multi Access
PBRP Priority Based Bandwidth Reservation Protocol
PDP Partial Dominant Prunning
PE Power Equilibrium
PSO Particle Swarm Optimization
QoS Quality of Service
RF Radio Frequency
RIP Routing Information Protocol
SAGE Semi Automatic Ground Environment
SHARP Sharp Hybrid Adaptive Routing Protocol
SI Swarm Intelligence
SIR Signal to Interference Ratio
SP Signomial Programming
SPPSO Small Population PSO
SVM Static Virtual Machine
TAODV Tactical On Demand Distance Vector
TCP Transmission Control Protocol
TF Traffic Factor
TIRREP Time Interval of RREP
TORA Temporary Ordered Routing Algorithm
VANET Vehicular Adhoc Network
WAN Wide Area Network
WLAN Wireless Local Area Network
WRP Wireless Routing Protocol
ZRP Zone Routing Protocol
CHAPTER ONE
INTRODUCTION
1.1 Background to the Study
The Mobile Adhoc Network (MANET) is a new network type which caters for the needs of the changing networking needs. It is the adhoc network of mobile devices. It is infrastructure less. Such networks may operate themselves or may be connected to the larger internet. Each device in MANET is free to move in any direction. The devices are being equipped with a router and must thus be in a position to transfer data whenever essential. The connection is, of course, wireless and the network may also be with limited range like LAN instead of connecting to the internet. The protocols to be used in MANET may differ, depending upon the capabilities of the devices, packet drop rate and other factors. There are various types of mobile adhoc networks depending on the location of these devices and the way in which they are used. Some of the popular types are (Attia, 2015):
VANET (Vehicular Ad hoc Network): This is when the devices are used to communicate between vehicles. It may also be used for communication between vehicles and roadside equipment. It can be used to transfer between newly web enabled devices on the road. IMANET: stands for internet based MANET. These are mobile ad hoc networks which link to the gateway device for the internet.
Energy-efficient broadcasting has been an attractive area of research in Mobile Ad hoc Networks (MANETs) characterized by high mobility and limited battery capacity. Probabilistic and counter-based broadcast methods are the proposed solutions suitable for high-mobility and secure MANET where the knowledge of the updated global/local topology is difficult or impossible to obtain.
In literature(Attia, 2016) several probabilistic and deterministic MANET broadcasting methods have been proposed:
1) Probabilistic methods do not require explicit neighbour information and comprise probability-based flooding, counter-based flooding, and area-based flooding. Probability-based flooding is similar to simple flooding except that nodes rebroadcast messages with probability p. Counter-based flooding exploits the fact that node local density is directed proportional to the number of received packets within a given interval. During a waiting delay, a node counts the number of times it receives the same message and then it decides if the message should be rebroadcasted. In area based flooding, each node selects its farther neighbour to retransmit broadcast messages. These kinds of methods are generally efficient but require the knowledge of the neighbour positions.
2) In deterministic methods, topological knowledge is obtained by periodically exchanging control messages among node’s neighbours. This approach and the type of exchanged information are generally scenario-dependent. Examples are clustering methods where nodes are grouped into small clusters each one managed by a particular node called cluster-head which has the task of retransmitting broadcast messages, geographic methods where forwarding decisions exploit the availability of accurate topological information such as distance, speed and direction of the neighbours, self-pruning methods where nodes use the history of encountered nodes before delivering messages.
MANET routing protocols based on the measure of the relative importance of a node within its cluster, named Network Centrality (NC), have been recently proposed in the literature. Although several works have explored the capacity of a node to receive and diffuse information based on different NC definition (e.g., degree, closeness, betweenness, and Eigenvector Centrality), they require complete knowledge of the network topology thus limiting the applicability of these protocols to fixed networks or to scenarios where the instant topology should be computed in a centralized fashion (Bai, 2003).
A mobile ad hoc network (MANET) is a self-configuring self-organizing network that does not require any infrastructure (Belding-Royer, 2012). Wireless nodes relay packets across the network making data transfer possible with other nodes. Quality of Service (QoS) is crucial in running a MANET. The Medium of Access Control (MAC) is an imperative condition for QoS provision. It is difficult to guarantee QoS in a MANET as it is a wireless network and like all other wireless networks, it is very unpredictable and highly susceptible to errors (Camp, 2011). Despite all this, it is possible to improve the QoS of a MANET through various techniques.
MANETs were initially created for disaster, emergencies and military use. But applications of MANETs for commercial ventures such as teleconferencing, home networking, embedded computing, electronic classrooms and so on are viable. Because the nodes used are mobile and there is no infrastructure used, power consumption is a major setback for MANETs. The main source of power for MANETs is battery power. The routing protocols in the network determine how much power will be consumed. Sending traffic in MANETs through the shortest path that uses minimum transmission energy and the nodes used have low residual power would maximize lifetimes of MANETs (Delgado, 2012).
Wireless Ad hoc network has no routers. Each node act as an intermediate node for other node and intermediate node forwards data towards destination node. An intermediate node is also a sender for other nodes and acts as a router in the network. For this network to run smoothly, an uninterrupted power supply needs to be available at all times. This is particularly difficult to maintain at any given time as power interruptions and outages never ceases. MANETS work through a transmission signal where source nodes connect to other nodes in the network. Power transmissions affect how long it will take for one node to sense and connect with another. Power transmission needs to be steady otherwise the signal strength will weaken and the range of transmission will decline (Farkas, 2016). This will in turn make users question or degrade the reliability of MANETs. Solving the power challenge is, therefore, paramount if we are to guarantee the QoS of MANETs.
Quality of Service(QoS) is crucial in running a MANET. The medium of access control (MAC) is an imperative condition for QoS provision. It is difficult to guarantee QoS in a MANET as it is a wireless network and like all other wireless networks, it is very unpredictable and highly susceptible to errors (Gerharz, 2013). Despite all this it is possible to improve the QoS of a MANET through various techniques.Solving the power challenge will not only make MANETs more reliable but will also improve the QoS in them. Improve power will mean better transmission in the network thus improving communication between nodes. Conserving power is crucial for the nodes due to the limited sources of energy for MANETs. Since battery power is what is used in MANETs, different levels of energy can disrupt communication activities thus reducing the efficiency of the network. Since the nodes do not work with a central station, depending on the activity taking place, each node may act as a router or host thus demanding more energy consumption (Han, 2010).
Wireless network can be deployed either in infrastructure mode or in Ad hoc mode. In an Infrastructure mode, mobile stations communicate with each other with the help of Base Station or Access Point (AP). It is similar to star topology of wired network. This Access Point makes communication easier between the nodes. In an Ad hoc mode there is no access point or base station that helps in communication between nodes. All nodes in wireless Ad hoc network directly communicate with each other in peer-to-peer fashion. The topology of wireless Ad hoc network is dynamic in nature therefore routes are changed frequently (Hong, 2009). Nodes in MANETs consume energy the power saving techniques in use are conserving power at mobile node, conserving power by use of power management technique, minimized power aware routing protocol and by controlling transmission power (Hong, 2014).
1.2 Statement of the Problem
A mobile ad hoc network is a network consisting of set of mobiles node capable of communicating with each other without base station. For Quality of Service (QoS) to be maintained, MANET must run consistently without power interruption. Also, the wireless network situation of MANET had made the QoS unpredictability less guaranteed and highly susceptible to errors.
MANETs are wireless networks that run usually on battery power. The power supplied by the battery is limited and tends to run out after a period of time. This poses a serious challenge for the nodes in MANETs. One major characteristic of the node is availability i.e., it should always be to receive and transmit communication to other nodes. If a node goes down, communication breaks down and the communication is disrupted. The availability of the nodes has an overall impact on the Quality of Service (QoS) that MANETs give. Once the nodes are not available when they are needed or if a node goes down while a communication is going on, thereby affecting the communication, the MANET is said to be unreliable, unpredictable and the QoS is said to be low.
Insufficient amount of power available to the nodes of the MANET makes it to be unreliable as it drain the routing models in the network medium. The major factors, which affect the data transmission of an Ad hoc network, are battery power, bandwidth, delay, speed, type of data and cost. The data transfer rates in a wireless Ad hoc network are not static but are dynamic. The availability of these resources at any node, either during data transmission or forwarding of data to other node is not certain. The resources available at any node are in scarce. Battery power is one of the major factors in a wireless Ad hoc network. A node can transmit data to a longer distance only if it has sufficient battery power. Area covered by a node in an Ad hoc network plays an important role during data transmission. Power constraints are constraints in a wireless network arise due to battery powered nodes which cannot be recharged on line. This becomes a bigger issue in mobile ad hoc networks as each node is acting as both an end system and a router at the same time, and for the purpose, additional energy is required to forward packets.
1.3 Objective of the Study
The main objective of this study is to conserve the battery life of mobile nodes by implementing one of the energy efficient techniques with the existing efficient routing protocols to increase life time of network and reduces network failure and energy. The specific objectives are:
- propose a new enhanced energy efficient routing protocol which is power aware and efficient for MANETs;
- compare the newly proposed protocol with a hybrid routing protocol (Swamp optimization techniques) and highest degree Heuristic Algorithm to improve power efficiency and
- Implement the developed algorithms in MATLAB environment.
1.4 Motivation
Without power, any mobile device will become useless. Battery power is a limited resource, and it is expected that battery technology is not likely to progress as fast as computing and communication technologies do. Hence, how to lengthen the lifetime of batteries is an important issue, especially for MANET, which is all supported by batteries.
1.5 Research Questions
How can a new enhanced energy efficient routing protocol that is power aware
and efficient for MANETs be implemented?
How can the new protocol be compared with a hybrid protocol?
How can the developed algorithm be implemented?
1.6 Significance of the Study
The study is significant as it tries to resolve the power challenge faced when using MANETs. The QoS of MANETs can only improve if the networks are working at their optimal capacity. This research would also cover current solutions for fixing the power problem and their effectiveness and also parts they are failing to address.
1.7 Scope of the Study
The scope is on QoS of MANETs and how power challenges can be solved. It would cover the effects the power disruptions have on QoS of MANETs. It would also consider already existing solutions to the challenge including the pros and cons of these solutions. It covers how the different types of MANETs and how each is affected by power shortages and gives a comparison as to which type is most affected and which is least affected. It could cover possible improvements that can be made to MANETs to try improving their functionality in relation to being able to detect other nodes even on weak signals. It would also cover duration it takes to fix power disruptions and whether this duration can be minimized without compromising the rectifications being done. Artificial Bee Colony Optimisation (ABCO) technique would be used. In this proposed scheme, QoS parameters that have been taken into consideration are throughput, delay, packet loss, and bandwidth utilisation. Here, three agents, namely message selection agent, message forwarding agent, and QoS factor calculating agent, have been introduced to govern and optimise the whole message transmission scheme. Through this method, a significant improvement in QoS factor can be achieved in comparison with the existing schemes. OPNET simulator has been used to evaluate the proposed concept.
1.8 Operational Definition of Terms
Artificial Bee Colony Optimization: An optimization algorithm in computer science and engineering based on the intelligent foraging behavior of honey bee swarm.
Mobile Ad Hoc Network (MANET): A wireless, dynamic, autonomous, infrastructure-less network of heterogeneous mobile hosts.
Network Topology: The physical arrangement of the hosts in the network.
QoS Metrics: Used to quantitatively measure the quality of service of a network and the network services that are often considered are error rates, bandwidth, throughput, transmission delay, availability, jitter, etc.
Quality of Service (QoS): Of a computer network is the overall performance of the network, especially in terms of the users’ perspective.
OPNET: A paid network simulator by Scalable Network Technologies used to simulate both wired and wireless networks.
Routing: The process of selecting optimum paths in the network.
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