论文标题

移动边缘计算中资源分配的全面实用功能

A Comprehensive Utility Function for Resource Allocation in Mobile Edge Computing

论文作者

Ali, Zaiwar, Khaf, Sadia, Abba, Ziaul Haq, Abbas, Ghulam, Jiao, Lei, Irshad, Amna, Kwak, Kyung Sup, Bilal, Muhammad

论文摘要

在移动边缘计算(MEC)中,重要的挑战之一是应将哪种移动边缘服务器(MES)的资源分配给哪种用户设备(UE)。现有的资源分配方案仅将CPU视为请求的资源,并将MYS的实用程序视为一个随机变量或仅取决于所请求的CPU。本文介绍了MEC中资源分配的新型综合效用函数。实用程序功能考虑了UE卸载到MES的应用的异质性质。所提出的实用程序功能考虑了所有重要参数,包括CPU,RAM,硬盘空间,所需的时间和距离,以计算MYS的更现实的效用值。此外,我们通过考虑我们提出的效用函数来改进一些通用算法,用于MEC和云计算中的资源分配。我们将这些资源分配方案的改进版本称为综合资源分配方案。对UE请求进行建模,以表示UE要求的资源数量以及UE要求这些资源的时间。实用程序函数取决于UE请求以及UES和MES之间的距离,并且是不同类型的UE请求之间比较的现实手段。选择(或选择)具有最佳资源的最佳MES是一项具有挑战性的任务。我们表明,如果CPU是唯一考虑的资源,则MES资源分配是亚最佳选择。通过考虑其他资源,即RAM,磁盘空间,请求时间和公用事业函数的距离,我们在服务率,实用程序和MES能源消耗方面证明了资源分配算法的改进。

In mobile edge computing (MEC), one of the important challenges is how much resources of which mobile edge server (MES) should be allocated to which user equipment (UE). The existing resource allocation schemes only consider CPU as the requested resource and assume utility for MESs as either a random variable or dependent on the requested CPU only. This paper presents a novel comprehensive utility function for resource allocation in MEC. The utility function considers the heterogeneous nature of applications that a UE offloads to MES. The proposed utility function considers all important parameters, including CPU, RAM, hard disk space, required time, and distance, to calculate a more realistic utility value for MESs. Moreover, we improve upon some general algorithms, used for resource allocation in MEC and cloud computing, by considering our proposed utility function. We name the improved versions of these resource allocation schemes as comprehensive resource allocation schemes. The UE requests are modeled to represent the amount of resources requested by the UE as well as the time for which the UE has requested these resources. The utility function depends upon the UE requests and the distance between UEs and MES, and serves as a realistic means of comparison between different types of UE requests. Choosing (or selecting) an optimal MES with the optimal amount of resources to be allocated to each UE request is a challenging task. We show that MES resource allocation is sub-optimal if CPU is the only resource considered. By taking into account the other resources, i.e., RAM, disk space, request time, and distance in the utility function, we demonstrate improvement in the resource allocation algorithms in terms of service rate, utility, and MES energy consumption.

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