Optimal and approximate approaches for selecting proxy agents in mobile IP based network backbones

• Published in: Journal of parallel and distributed computing Vol. 64; no. 4; pp. 554 - 568
• Main Authors: Kamal, Ahmed, El-Rewini, Hesham, Ul-Mustafa, Raza
• Format: Journal Article
• Language: English
• Published: San Diego, CA Elsevier Inc 01.04.2004; Elsevier
• Subjects: Access methods and protocols, osi model; Applied sciences; Exact sciences and technology; Radiocommunications; Telecommunications; Telecommunications and information theory; Teleprocessing networks. Isdn; Cluster analysis; Mobile radiocommunication; Cost minimization; Internet protocol; Communication network; Multiagent system; Genetic algorithm; Optimal solution; Minimax method; Simulated annealing; Mobile host; Computer server; Mobile computing; Mathematical programming
• ISSN: 0743-7315; 1096-0848
• DOI: 10.1016/j.jpdc.2004.01.005

In a mobile environment, each mobile host should have a home agent on its home network that maintains a registry of the current location of the mobile host. This registry is normally updated every time a mobile host moves from one subnet to another. We study the tradeoff between the cost of updating the registry and the cost of searching for a mobile host while it is away from home. Using a set of special agents, called proxy agents, which implement a two-tier update process, the cost of updates could be reduced; however, the search cost might increase. We study different approaches to identify a set of proxy agents that minimizes the cost of search. In this paper, we use mathematical programming to obtain optimal solutions to the problem. We consider two situations: the cost of search measured by the sum of all search message costs, and the cost of search measured by the maximum cost of such messages. For these two respective cases we formulate the minimization of the cost of search as Min-Sum and Min-Max problems. For large networks in which the optimization problem may be intractable, we study three different approximate approaches: (1) clustering, (2) genetic algorithms, and (3) simulated annealing. Results of a large set of experiments are presented.