Resource Optimization in Computer Networks Using Differential Evolution Algorithm

The intensive development of computer networks has made the necessity of effective and intelligent resource allocation systems extremely high. Conventional optimization techniques very often fail to deal with the nonlinear relation and multiobjective trade-offs between the network resources including bandwidth, CPU allocation, memory usage, power consumption, and buffer capacity. To solve these issues, this paper outlines a Differential Evolution (DE)-based resource optimization model to computer networks. The model designed uses MATLAB to allow the dynamic interaction of network parameters and the allocation to maximize throughput and minimize the operational cost. The algorithm will make repeated adjustments to a population of solutions by using mutation, crossover and selection to arrive at an optimal resource configuration. The analysis of the simulation reveals that this algorithm provides a balanced use of the resources, and an enhanced optimization efficiency. MATLAB has been used in the simulation, visualization and quantitative assessment of the algorithm performance.