The use of mobile communication networks has increased rapidly in the last two decades. This growth is expected to continue at a high rate in the foreseeable future. Consequently, issues such as network scalability and overload/congestion control cannot be overlooked and must be taken into account in the design and operation of these networks. Scalability is the ability of the network to accommodate an increasing number of users, more and diversified services, expanding geographical coverage, etc., while maintaining high availability of network resources and preserving quality of service requirements. In the design process of a large network and its underlying protocols, several alternatives may be proposed to allow for scalable solutions. In the presence of a large number of potential active users, overload at parts of the network is likely to occur, at least occasionally, during busy hours or due to some unexpected events. In the absence of proper control to help avoid overloads and to quickly dissipate them when they occur, congestion may persist for extended periods of time, leading to unacceptable delays and high blocking rate of service requests. Therefore, it is crucial that the network be equipped with algorithms to protect critical network entities from becoming overloaded; i.e., congestion control algorithms. The first main focus of this thesis is network scalability. A methodology for the modeling and quantitative analysis of scalability is introduced and applied for the evaluation of a prototype Broadband Intelligent Network (B-IN) that has been developed in the European ACTS projects "INSIGNIA" and "EXODUS". The second main focus of this thesis is network congestion control. Novel congestion control algorithms are proposed for the same B-IN prototype developed in the ACTS projects "INSIGNIA" and "EXODUS". Important qualitative criteria are identified for the evaluation of these algorithms, and extensive performance experimentation is carried out to demonstrate their effectiveness and superiority in comparison with other known congestion control solutions.
|Award date||12 Jun 2002|
|Place of Publication||Enschede|
|Publication status||Published - 12 Jun 2002|