With the development of satellite communication technology, the demand for satellite resources for various communication tasks is increasingly complex. In order to further improve the utilization efficiency of satellite resources and better deal with the resource competition between different types of services, this paper proposes a satellite communication task scheduling algorithm based on genetic algorithm. By matching the satellite task scheduling problem with the utility optimization problem, and designing the chromosome coding method and genetic operator matching with this problem, the convergence performance of genetic algorithm is effectively improved. Simulation results show that the algorithm is a fast convergence and efficient satellite communication task scheduling algorithm.
Mobile edge computing (MEC) is one of the key technologies of 5G. Due to the limited computing resources of MEC server, it’s a quite hard problem for task offloading decision and resource allocation when multiple users share the resources in MEC. To solve this problem, an improved genetic algorithm is proposed, and a multi-segment chromosome structure and a mixed fitness scaling method are designed with the target of maximizing overall system benefit in terms of time delay utility. Simulation experiments show that this algorithm has good convergence and high computational efficiency.
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