Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.690857
Title: Intelligent routing algorithm for mobile Internet Protocol Television
Author: Abubakar, Babangida Albaba
ISNI:       0000 0004 5915 7539
Awarding Body: University of Brighton
Current Institution: University of Brighton
Date of Award: 2016
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Abstract:
Network bandwidth and server capacity are gradually becoming overloaded due to the high demand and rapid evolution of high quality multimedia services over the Internet. Internet Protocol Television (IPTV) is among the multimedia services that demand more of network and server resources, especially with the emergence of Mobile IPTV. It is imperative for the service providers to maintain good quality management services in order to satisfy their clients. To guarantee the required quality of service (QoS) and quality of experience (QoE) in IPTV, the server must have the required capacity and resources to serve all the clients’ requests. The flexibility of IPTV services which provide users with the ability to stream multimedia content at anytime and anywhere they want, makes the demand for video-on-demand (VoD) services higher. However, the server bandwidth capacity is limited, and as such the numerous requests from the clients may exhaust all the available bandwidth depending on the number of requests at a given time, which may lead to the poor QoS and QoE. In this research, a new algorithm called Intelligent Routing Algorithm for Mobile IPTV (IRA-MIPTV) is proposed. The algorithm combined features and advantages of Internet Protocol (IP), Mobile Ad hoc Network (MANET) characteristics and Content Delivery Network (CDN) based network architecture to improve on the QoS and QoE in mobile IPTV. The proposed algorithm is aimed at reducing total dependency on the server by the mobile nodes. The algorithm intelligently learns the best server or client to serve an incoming service request depending on the available server capacity and the number of requests received at a point in time. The routing decision is made by the Designated Server (DS) that selects and reroutes a request to the most appropriate server or client. The novelty of this research work can simply be identified as the designing, developing and evaluating an Intelligent Routing Algorithm for mobile ITPV (IRA-MIPTV) that intelligently learns and select a reflective server or client to serve a particular service request on behalf of the server during high service demand. The selection depends on the server available bandwidth, load and proximity. The proposed algorithm also dynamically adjusts to server failure by assigning the role of designated server to the backup server and re-elect another backup server to guarantee service delivery at all times. To validate the effectiveness of the proposed algorithm, different simulation tests were conducted using OPNET/Riverbed Modeler 18.0. A typical IPTV network, where packets are delivered over IP, and the proposed algorithm were modelled and incorporated into the Modeler. For the study to reflect more on real situations, live video programme was streamed using VLC media player. The packet’s size and packet inter-arrival time data were collected and used in the simulation’s environment. After conducting a series of simulation tests, the results showed that the proposed algorithm outperforms the normal IPTV system in server load reduction, high throughput and low amount of end-to-end delay, as well as adaptability and robustness. The results also showed that the efficiency of the proposed algorithm increases as the number of clients increase. It also confirmed that the algorithm reduces the server overload during high service request periods by using clients to serve some of the incoming service requests on behalf of the server. The algorithm produced low server and network load, low end-to-end delay, high throughput, adaptability and robustness.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.690857  DOI: Not available
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