To further reduce the delay in cellular edge computing systems, a new type of resource scheduling algorithm is proposed. Without assuming the knowledge of the statistics of user task arrival traffic, the analytical fo...To further reduce the delay in cellular edge computing systems, a new type of resource scheduling algorithm is proposed. Without assuming the knowledge of the statistics of user task arrival traffic, the analytical formulae of the communication and computing queueing delays in many-to-one multi-server cellular edge computing systems are derived by using the arriving curve and leaving curve. Based on the analytical formulae, an optimization problem of delay minimization is directly formulated, and then a novel scheduling algorithm is designed. The delay performance of the proposed algorithm is evaluated via simulation experiments. Under the considered simulation parameters, the proposed algorithm can achieve 12% less total delay, as compared to the traditional algorithms. System parameters including the weight, the amount of computing resources provided by servers, and the average user task arrival rate have impact on the percentage of delay reduction. Therefore, compared with the queue length optimization based traditional scheduling algorithms, the proposed delay optimization-based scheduling algorithm can further reduce delay.展开更多
基金The National Natural Science Foundation of China(No.61571111)
文摘To further reduce the delay in cellular edge computing systems, a new type of resource scheduling algorithm is proposed. Without assuming the knowledge of the statistics of user task arrival traffic, the analytical formulae of the communication and computing queueing delays in many-to-one multi-server cellular edge computing systems are derived by using the arriving curve and leaving curve. Based on the analytical formulae, an optimization problem of delay minimization is directly formulated, and then a novel scheduling algorithm is designed. The delay performance of the proposed algorithm is evaluated via simulation experiments. Under the considered simulation parameters, the proposed algorithm can achieve 12% less total delay, as compared to the traditional algorithms. System parameters including the weight, the amount of computing resources provided by servers, and the average user task arrival rate have impact on the percentage of delay reduction. Therefore, compared with the queue length optimization based traditional scheduling algorithms, the proposed delay optimization-based scheduling algorithm can further reduce delay.
