Optimizing Access Point Allocation Using Genetic Algorithmic Approach for Smart Home Environments

In recent years, high-bandwidth and low-cost wireless technologies have emerged as a competitive element, enabling the smart home environment. On the other hand, with the increasing demands for various services, the current access point allocation schemes give rise to significant challenges for a stable connection service, bandwidth and load distribution. In this paper, we present an optimal access point allocation scheme based on genetic algorithm that attempts to optimize multiple parameters, such as bandwidth, and load-balancing requirements. The proposed allocation scheme provides a set of approximately efficient solutions, which allows a wireless user to choose an access point based on its capacity and load balancing, not only regarding its signaling strength or service set identifier. The simulation results are provided to demonstrate the impact of the proposed optimization procedure on overall system performance in terms of connection distribution, load balancing and call dropping probability.

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