Analysis of a metropolitan-area wireless network
MobiCom '99 Proceedings of the 5th annual ACM/IEEE international conference on Mobile computing and networking
Analysis of a local-area wireless network
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
Distributed fair scheduling in a wireless LAN
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
Analysis of a campus-wide wireless network
Proceedings of the 8th annual international conference on Mobile computing and networking
Quality of service schemes for IEEE 802.11 wireless LANs: an evaluation
Mobile Networks and Applications
Investigation of the IEEE 802.11 Medium Access Control (MAC) Sublayer Functions
INFOCOM '97 Proceedings of the INFOCOM '97. Sixteenth Annual Joint Conference of the IEEE Computer and Communications Societies. Driving the Information Revolution
Improving protocol capacity with model-based frame scheduling in IEEE 802.11-operated WLANs
Proceedings of the 9th annual international conference on Mobile computing and networking
DIRAC: a software-based wireless router system
Proceedings of the 9th annual international conference on Mobile computing and networking
Revealing bullying patterns in multi-agent systems
Journal of Systems and Software
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In a wireless LAN environment, clients tend to associate with the nearest access point (AP) which usually provides the strongest signal. However, this does not guarantee that users will receive the best quality of service (QoS) if the population sharing the network capacity were not considered. In other words, within the same access point, the more the population is, the less bandwidth each user will share, and the worse the quality of service will be. In this paper, we proposed an anticipative agent assistance (AAA) which is an agent-based metric for evaluating and managing the resource information 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 achieves: (1) reduce the transmission delay, (2) increase the throughput, (3) improve the network utilization, (4) accommodate more users to access the networks, and (5) achieve load-balancing. Our metric is implementation feasible in various IEEE WLAN environments.