Mobility-Aware and Delay-Sensitive Service Provisioning in Mobile Edge-Cloud Networks

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

15 Scopus Citations
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Detail(s)

Original languageEnglish
Pages (from-to)196-210
Journal / PublicationIEEE Transactions on Mobile Computing
Volume21
Issue number1
Online published2 Jul 2020
Publication statusPublished - 1 Jan 2022

Abstract

Mobile edge computing (MEC) has emerged as a promising technology to push the cloud frontier to the network edge, provisioning network services in proximity of mobile users. Serving users at edge clouds can reduce service latency, lower operational cost, and improve network resource availability. Along with the MEC technology, network function virtualization (NFV) is another promising technique that implements various network service functions as pieces of software in cloudlets (servers or clusters of servers). Providing virtualized network service for mobile users can improve user service experience, simplify network service deployment, and ease network resource management. However, mobile users move in networks arbitrarily, and different users usually request different services with different resource demands and delay requirements. It thus poses a great challenge to providing reliable and seamless virtualized network services for mobile users in an MEC network while meeting their individual delay requirements, subject to resource capacities on the network. In this paper, we focus on the provisioning of virtualized network function services for mobile users in MEC that takes into account user mobility and service delay requirements. We first formulate two novel optimization problems of user service request admissions with the aims to maximize the accumulative network utility and accumulative network throughput for a given time horizon, respectively. We then devise a constant approximation algorithm for the utility maximization problem. We also develop an online algorithm for the accumulative throughput maximization problem. We finally evaluate the performance of the proposed algorithms through experimental simulations. Experimental results demonstrate that the proposed algorithms are promising.

Research Area(s)

  • approximation and online algorithms, cloudlets or edge-clouds, delay-sensitive request admission, Mobile Edge computing, network function virtualization, optimization problems, resource allocations and provisioning in MEC, user mobility, utility gain maximization, virtualized service provisioning, VNF instance deployment