Adaptive Call Admission Control Based on Enhanced Genetic Algorithm in Wireless/Mobile Network

An adaptive threshold-based call admission control (CAC) scheme used in wireless/mobile network for multi-class services is proposed. In the scheme, each class' CAC thresholds are solved through establishing a reward-penalty model which tries to maximize network's revenue in terms of each class's average new call arrival rate and average handoff call arrival rate, the reward or penalty when network accepts or rejects one class's call etc. To guarantee the real time running of CAC algorithm, an enhanced genetic algorithm is designed. Analyses show that the CAC thresholds indeed change adaptively with the average call arrival rate. The performance comparison between the proposed scheme and mobile IP reservation (MIR) scheme shows that with the increase of average call arrival rate, the average new call blocking probability (CBP) and the average handoff dropping probability (HDP) within 2000 simulation intervals of the proposed scheme are confined to lower levels, and they show approximatively periodical trends of first rise and then decline. While these two performance metrics of MIR always increase. At last, the analysis shows the proposed scheme outperforms MIR in terms of network's revenue