Wireless Mesh Networks Based on MBPSO Algorithm to Improvement Throughput

Wireless Mesh Networks can be regarded as a type of communication technology in mesh topology in which wireless nodes interconnect with one another. Wireless Mesh Networks depending on the semi-static configuration in different paths among nodes such as PDR, E2E delay and throughput. This study summarized different types of previous heuristic algorithms in order to adapt with proper algorithm that could solve the issue. Therefore, the main objective of this study is to determine the proper methods, approaches or algorithms that should be adapted to improve the throughput. A Modified Binary Particle Swarm Optimization (MBPSO) approach was adapted to improvements the throughput. Finally, the finding shows that throughput increased by 5.79% from the previous study

Optimization of power consumption in 4G LTE networks using a novel barebones self-adaptive differential evolution algorithm

The power consumption of wireless access networks is an important issue. In this paper, the power consumption of Long Term Evolution (LTE) base stations is optimized. We consider the city of Ghent, Belgium with 75 possible LTE base station locations. We optimize the network towards two objectives: the coverage maximization and the power consumption minimization. We propose a new Barebones Self-adaptive Differential Evolution. The results of the proposed method indicate the advantages and applicability of our approach