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Request Dispatching for Minimizing Service Response Time in Edge Cloud Systems

机译:请求分派以最小化边缘云系统中的服务响应时间

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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.
机译:移动边缘计算的出现极大地减少了响应时间和Internet调用服务的风险。但是,由于分布式体系结构和有限的资源,平衡边缘服务器之间的负载以最小化总体响应时间已成为移动边缘计算的关键目标。此问题通常与两个方面有关:请求分派和服务调度。为了解决这个问题,我们提出了一种新颖的启发式方法,称为GASD(用于服务请求分派的组合遗传算法和模拟退火算法)。通过联合进行请求分配和服务调度来解决该问题。另外,应用解决方案组合算法以减少该方法的计算复杂度。实验结果表明,与比较方法相比,GASD方法可以获得更低的总体响应时间。此外,GASD的执行时间处于较低的数量级,并且随着实验规模的增加,该算法具有出色的可扩展性。

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