A distributed trust and reputation model for capacity enhancement in wireless networks

In order to enhance resource allocation in wireless local area networks, it is important to properly distribute the load from the overloaded access points (APs) over their neighbors. Nevertheless, malicious APs may strategically alter their behavior for concealing malicious behavior and prompting their reputation. Therefore, it is important to evaluate APs' trustworthiness. In this paper, we propose a trusted model based on an autonomic load management algorithm (ALMA) that ensure the accommodation of more user traffic and an overall network capacity improvement, by evaluating and detecting the malicious APs. Initially each APs is assigned a trust level. Using these trust levels as a guide, the source AP can then select a neighbor AP that meets the security requirements. Simulations, using VoIP traffic, show that, the performance gain in term of call blocking rate is improved by using the trust-based approach.