A Comprehensive Utility Function for Resource Allocation in Mobile Edge Computing

被引:7
|
作者
Ali, Zaiwar [1 ]
Khaf, Sadia [2 ]
Abbas, Ziaul Haq [2 ]
Abbas, Ghulam [3 ]
Jiao, Lei [4 ]
Irshad, Amna [2 ]
Kwak, Kyung Sup [5 ]
Bilal, Muhammad [6 ]
机构
[1] GIK Inst Engn Sci & Technol, Telecommun & Networking TeleCoN Res Lab, Topi 23640, Pakistan
[2] GIK Inst Engn Sci & Technol, Fac Elect Engn, Topi 23640, Pakistan
[3] GIK Inst Engn Sci & Technol, Fac Comp Sci & Engn, Topi 23640, Pakistan
[4] Univ Agder UiA, Dept Informat & Commun Technol, N-4898 Grimstad, Norway
[5] Inha Univ, Dept Informat & Commun Engn, Incheon 22212, South Korea
[6] Hankuk Univ Foreign Studies, Dept Comp & Elect Syst Engn, Yongin 17035, Gyeonggi Do, South Korea
来源
CMC-COMPUTERS MATERIALS & CONTINUA | 2021年 / 66卷 / 02期
基金
新加坡国家研究基金会;
关键词
Cloud computing; energy efficient resource allocation; mobile edge computing; service rate; user equipment; utility function; MACHINE PLACEMENT ALGORITHM; AWARE;
D O I
10.32604/cmc.2020.013743
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:1461 / 1477
页数:17
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