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The optimisation and performance evaluation of routing protocols in cognitive radio based wireless mesh networks

Thesis (MSc.) -- University of Limpopo, 2017 / The notion of ubiquitous computing, Internet of things (IoT), big data, cloud computing and other emerging technologies has brougt forward the innovative paradigms and incredible developments in wireless communication technologies. The Wireless Mesh Networks (WMNs) technology has recently emerged as the promising high speed wireless technology to provide the last mile broadband Internet access and deliver flexible and integrated wireless communication solutions. The WMNs has the potential to enable people living in rural, peri-urban areas and small businesses to interconnect their networks and share the affordable Internet connectivity. The recent multimedia applications developed, such as voice over Internet protocol (VoIP), online gaming, cloud storage, instant messaging applications, and video sharing applications require high speed communication media and networks. These applications have witnessed enormous growth in the recent decade and continue to enhance communication amongst the users. Hence, the WMNs must have adequate capacity to support high bandwidth and real-time and multimedia applications.
While the wireless communications networks are dependent on the radio frequency (RF) spectrum, the traditional wireless technologies utilise the RF spectrum bands inefficiently, resulting in sporadic and underutilisation of the RF spectrum. This inefficient usage of RF spectrum calls for novel techniques to leverage the available RF spectrum amongst different players in the wireless communication arena. There have been developments on integration of the WMNs with cognitive ratios to allow unlicensed users of RF spectrum to operate in the licensed portions of spectrum bands. This integration will provide the required bandwidth to support the required high speed broadband communication infrastructure.
In this dissertation, we focus our research on the routing layer in a multi-hop wireless network environment. We addressed the routing challenges in both the WMNs and the cognitive radio based wireless mesh networks (CR-WMNs). The primary focus was to identify the routing protocols most suitable for the dynamic WMN environment. Once identified, the routing protocol was then ported to the CR-WMN environment to evaluate its performance given all the dynamics of cognitive radio environment.
We further proposed the routing protocol called the extended weighted cumulative expected transmission time (xWCETT) routing protocol for the CR-WMNs. The design of our proposed xWCETT routing protocol is based on the multi-radio multi-channel architecture as it gives the base framework matching the cognitive radio environment. The xWCETT integrates features from the Ad-hoc On-demand Distance Vector (AODV) routing protocol and the weighted cumulative expected transmission time (WCETT) routing metric. The xWCETT was implemented using the Cognitive Radio Cognitive Network (CRCN) patch ported in network simulator (NS2) to incorporate the shared and dynamic spectrum access features. We compared the performance of our proposed xWCETT routing protocol with the AODV, dynamic source routing (DSR), the optimised link source routing (OLSR), Destination Sequences Distance Vector (DSDV), and the CRCN-WCETT routing protocols. The extensive simulation and numerical results show that the proposed xWCETT protocol obtained on average, around 10% better performance results in the CR-WNNs as compared to its routing counterparts. The comparative analysis and evaluation was performed in terms of the average end-to-end latency, throughput, jitter, packet delivery ratio, as well as the normalised routing load. The performance results obtained indicates that the proposed xWCETT routing protocol is a promising routing solution for dynamic CR-WMNs environment. / National Research Foundation (NRF)
Date January 2017
CreatorsKola, Lesiba Morries
ContributorsMthulisi, V.
Source SetsSouth African National ETD Portal
Detected LanguageEnglish
Formatxviii, 93 leaves
RelationAdobe Acrobat Reader

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