Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.588217
Title: Modelling and performance analysis of mobile ad hoc networks
Author: Younes, Osama
Awarding Body: University of Newcastle Upon Tyne
Current Institution: University of Newcastle upon Tyne
Date of Award: 2013
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Abstract:
Mobile Ad hoc Networks (MANETs) are becoming very attractive and useful in many kinds of communication and networking applications. This is due to their efficiency, relatively low cost, and flexibility provided by their dynamic infrastructure. Performance evaluation of mobile ad hoc networks is needed to compare various architectures of the network for their performance, study the effect of varying certain network parameters and study the interaction between various parameters that characterise the network. It can help in the design and implementation of MANETs. It is to be noted that most of the research that studies the performance of MANETs were evaluated using discrete event simulation (DES) utilising a broad band of network simulators. The principle drawback of DES models is the time and resources needed to run such models for large realistic systems, especially when results with a high accuracy are desired. In addition, studying typical problems such as the deadlock and concurrency in MANETs using DES is hard because network simulators implement the network at a low abstraction level and cannot support specifications at higher levels. Due to the advantage of quick construction and numerical analysis, analytical modelling techniques, such as stochastic Petri nets and process algebra, have been used for performance analysis of communication systems. In addition, analytical modelling is a less costly and more efficient method. It generally provides the best insight into the effects of various parameters and their interactions. Hence, analytical modelling is the method of choice for a fast and cost effective evaluation of mobile ad hoc networks. To the best of our knowledge, there is no analytical study that analyses the performance of multi-hop ad hoc networks, where mobile nodes move according to a random mobility model, in terms of the end-to-end delay and throughput. This work ii presents a novel analytical framework developed using stochastic reward nets and mathematical modelling techniques for modelling and analysis of multi-hop ad hoc networks, based on the IEEE 802.11 DCF MAC protocol, where mobile nodes move according to the random waypoint mobility model. The proposed framework is used to analysis the performance of multi-hop ad hoc networks as a function of network parameters such as the transmission range, carrier sensing range, interference range, number of nodes, network area size, packet size, and packet generation rate. The proposed framework is organized into several models to break up the complexity of modelling the complete network and make it easier to analyse each model as required. This is based on the idea of decomposition and fixed point iteration of stochastic reward nets. The proposed framework consists of a mathematical model and four stochastic reward nets models; the path analysis model, data link layer model, network layer model and transport layer model. These models are arranged in a way similar to the layers of the OSI protocol stack model. The mathematical model is used to compute the expected number of hops between any source-destination pair; and the average number of carrier sensing, hidden, and interfering nodes. The path analysis model analyses the dynamic of paths in the network due to the node mobility in terms of the path connection availability and rate of failure and repair. The data link layer model describes the behaviour of the IEEE 802.11 DCF MAC protocol. The actions in the network layer are modelled by the network layer model. The transport layer model represents the behaviour of the transport layer protocols. The proposed models are validated using extensive simulations.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.588217  DOI: Not available
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