Intro; Contents; About the Authors; List of Figures; List of Tables; 1 Introduction; 1.1 Introduction; 1.1.1 Differences Between Cellular and Ad Hoc; 1.1.2 Applications of Ad Hoc Wireless Networks; 1.1.3 Technical Challenges in MANET; 1.2 Motivation; 1.3 Aims and Objectives; 1.4 Contributions; 1.5 Book Structure; 2 Time Series Analysis; 2.1 Introduction to Time Series; 2.2 Objectives of Time Series Analysis; 2.3 A General Approach to Time Series Modelling; 2.3.1 Autoregressive Process; 2.4 Time Series Analysis and MANET; 3 Preliminaries; 3.1 Introduction to Mobile Ad Hoc Networks.
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3.2 Routing Protocols3.3 Mobility Models; 3.3.1 Random Walk Mobility; 3.3.2 Gauss-Markov Mobility Model (GM); 3.3.3 Manhattan Grid Mobility Model (MHG); 3.3.4 Random Way Point (RWP) Mobility Model; 3.3.5 Random Direction Model; 3.3.6 Reference Point Group Mobility (RPGM) Model; 3.4 Clustering; 3.5 Works Related to MANET Parameters; 4 Neighbour Counts Modelling; 4.1 Introduction; 4.2 Motivation; 4.3 Modelling; 4.4 Experiments and Results; 4.4.1 Analysis for Varying Speed and a Fixed Sampling Rate; 4.4.2 Analysis for Constant Speed and Varying Sampling Rate.
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4.4.3 Analysis for Varying Speed and Varying Sampling Rate4.4.4 Analysis for Varying Transmission Range; 4.4.5 Comparison for Different Mobility Patterns; 4.5 Discussion; 5 Link Load Modelling; 5.1 Introduction; 5.2 Motivation; 5.3 Modelling; 5.4 Experiments and Results; 5.4.1 Analysis for Gauss-Markov Mobility Model; 5.4.2 Analysis for Manhattan Grid Mobility Model; 5.4.3 Analysis for Reference Point Group Mobility Model; 5.4.4 Analysis for Random Way Point Mobility Model; 5.5 Discussion; 6 Path Length Modelling; 6.1 Introduction; 6.2 Motivation; 6.3 Modelling; 6.4 Experiments and Results.
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6.4.1 Analysis Under Gauss-Markov Mobility Model6.4.2 Analysis Under Manhattan Grid Mobility Model; 6.4.3 Analysis Under Reference Point Group Mobility Model; 6.4.4 Analysis Under Random Way Point Mobility Model; 6.5 Discussion; 7 Clustering Modelling; 7.1 Introduction; 7.2 Motivation; 7.3 Modelling; 7.4 Experiments and Results; 7.4.1 The Effect of Mobility Model and Speed on Number of Clusters; 7.4.2 The Effect of Mobility Model and Speed on Cluster Head Changes; 7.4.3 The Effect of Mobility and Speed on Node Weights; 7.5 Weight Prediction; 8 Delay Modelling and Prediction; 8.1 Introduction.
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8.2 Literature Status8.3 Motivation; 8.4 Artificial Neural Network Model for Delay; 8.5 Experiments and Results; 8.5.1 Analysis of Gauss-Markov Mobility Model; 8.5.2 Analysis of Manhattan Grid Mobility Model; 8.5.3 Analysis of Random Way Point Mobility Model; 8.6 Discussion; 8.7 Fuzzy Time Series Model for Delay; 8.8 Modelling; 8.8.1 Regression Model; 8.8.2 Fuzzy Time Series Model; 8.8.3 Weighted Model; 8.9 Experiments and Results; 8.9.1 Analysis of Gauss-Markov Mobility; 8.9.2 Analysis of Manhattan Grid Mobility; 8.9.3 Analysis of RPGM Mobility; 8.9.4 Analysis of RWP Mobility.
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SUMMARY OR ABSTRACT
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This book identifies the time-dependent network parameters: neighbour count, link load, path length, cluster count and delay, and presents a first-of-its-kind discussion on temporal parameters in mobile ad hoc networks. Frequent topology changes and multiple link failures occur in mobile ad hoc network due to arbitrary and random movement of nodes. This dynamic environment challenges the delivery of data and makes it essential to find better models for network parameters that are shifting with time. The parameters identified are put into the framework of time series because of their temporal characteristic, and when they are modelled using time series framework they exhibit a sound fit with Autoregressive AR(p) models of order p. The order p is evaluated for each fitted model and found to lie between one and three. The book also analyses the dependence of end-to-end delay of ad hoc network on various external factors such as the number of nodes, routing protocol, mobility models and path length and develops two prediction models. The book will be useful for researchers and professionals alike.