Request Dispatching for Minimizing Service Response Time in Edge Cloud Systems

Hongyue Wu, Shuiguang Deng, Wei Li, S. Khan, Jianwei Yin, Albert Y. Zomaya
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引用次数: 13

Abstract

The emerging of mobile edge computing has significantly reduced the response time and Internet risk of service invocations. However, due to the distributed architecture and limited resources, balancing the load between edge servers to minimize the overall response time has become a critical objective for mobile edge computing. This problem is generally related to two aspects, request dispatching and service scheduling. To address this issue, we proposed a novel heuristic method called GASD (combined Genetic algorithm and simulated Annealing algorithm for Service request Dispatching). It tackles the problem by jointly conducting request dispatching and service scheduling. In addition, a solution combination algorithm is applied to reduce the computation complexity of the method. The experimental results show that the GASD method can achieve much lower overall response time than the compared methods. Moreover, the execution time of GASD is in a low order of magnitude and the algorithm performs excellent scalability as the experimental scale increases.
边缘云系统中最小化服务响应时间的请求调度
移动边缘计算的出现大大降低了服务调用的响应时间和互联网风险。然而,由于分布式架构和有限的资源,平衡边缘服务器之间的负载以最小化总体响应时间已经成为移动边缘计算的关键目标。这个问题一般涉及到请求调度和服务调度两个方面。为了解决这个问题,我们提出了一种新的启发式方法GASD(结合遗传算法和模拟退火算法的服务请求调度)。它通过联合进行请求调度和服务调度来解决这个问题。此外,采用解组合算法降低了该方法的计算复杂度。实验结果表明,GASD方法的总体响应时间明显低于对比方法。此外,GASD的执行时间很低,随着实验规模的增加,算法具有良好的可扩展性。
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