A Comparison of Intelligent Admission Control Schemes for Next Generation Wireless Systems using Genetic Algorithms, Simulated Annealing and Tabu Search

Abstract

Mobile users will have a variety of services including high-speed data and real-time multimedia services with Next Generation Wireless Systems (NGWS). A uni¯ed and e±cient hando® management is one of the key issues for NGWS to support global roaming of mobile users among di®erent network architectures. In this paper, di®erent arti¯cial intelligence algorithms such as genetic algorithms (GAs), simulated annealing (SA) and tabu search (TS) are deployed to a uni¯ed call admission control (CAC) scheme for NGWS for performance comparisons. The schemes apply the algorithms to achieve high network utilization, minimum cost, minimum hando® latency and to guarantee QoS requirements. Performance analysis is provided to assess the e±ciency of CAC scheme using these algorithms. Simulation results show a signi¯cant improvement in hando® latencies and costs over the heuristic approach and other CAC schemes for each arti¯cial intelligence technique.