6533b823fe1ef96bd127f6f8
RESEARCH PRODUCT
A Comprehensive Utility Function for Resource Allocation in Mobile Edge Computing
Lei JiaoMuhammad BilalZiaul Haq AbbaSadia KhafKyung Sup KwakGhulam AbbasZaiwar AliAmna Irshadsubject
FOS: Computer and information sciencesComputer sciencemedia_common.quotation_subjectG.3Cloud computingComputer Science - Networking and Internet ArchitectureC.2.3BiomaterialsC.2.1Resource (project management)Electrical and Electronic EngineeringFunction (engineering)media_commonNetworking and Internet Architecture (cs.NI)Mobile edge computingbusiness.industryEnergy consumptionComputer Science ApplicationsTask (computing)User equipmentMechanics of MaterialsModeling and SimulationResource allocationG.3; C.2.3; C.2.1business46FxxComputer networkdescription
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.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2020-12-18 | Computers, Materials & Continua |