An Agent-Based Metric for Quality of Services over Wireless Networks
In a wireless LAN environment, wireless stations with the strongest received signal can not be guaranteed to have the best quality of service if the population sharing the network capacity was not considered. In other words, within the same access point, the more the population, the less the shared bandwidth, and the worse the quality of service will be. In this paper, we proposed an anticipative agent assistance which is an agent-based metric for evaluating and managing the resource of the wireless access points, computing the potential AP list, and providing clients with resource information of APs. We also propose a novel QoS feedback mechanism which allows users to promptly adjust the service quality with AAA according to the throughput and delay requirements. We evaluate the performance of our proposed method using the ns-2 simulator. Numerical results show that AAA help reduce the transmission delay, increase the throughput, improve the network utilization, accommodate more users, and provide load-balancing