TY - JOUR
T1 - Path Selection for Seamless Service Migration in Vehicular Edge Computing
AU - Xu, Jinliang
AU - Ma, Xiao
AU - Zhou, Ao
AU - Duan, Qiang
AU - Wang, Shangguang
N1 - Funding Information:
Manuscript received February 16, 2020; revised April 27, 2020; accepted June 2, 2020. Date of publication June 5, 2020; date of current version September 15, 2020. This work was supported in part by the National Natural Science Foundation of China under Grant 61922017 and Grant 61902036, in part by the Funds for Creative Research Groups of China under Grant 61921003, and in part by the China Postdoctoral Science Foundation under Grant 2019M650589. (Corresponding author: Xiao Ma.) Jinliang Xu, Xiao Ma, Ao Zhou, and Shangguang Wang are with the State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China (e-mail: jlxu@bupt.edu.cn; maxiao18@bupt.edu.cn; aozhou@bupt.edu.cn; sgwang@bupt.edu.cn).
PY - 2020/9
Y1 - 2020/9
N2 - Mobile-edge computing provisions computing and storage resources by deploying edge servers (ESs) at the edge of the network to support ultralow delay and high bandwidth services. To ensure QoS of latency-sensitive services in vehicular networks, service migration is required to migrate data of the ongoing services to the closest ES seamlessly when users move across different ESs. To achieve seamless service migration, path selection is proposed to obtain one or more paths (consisting of several switches and ESs) to transfer service data. We focus on the following problems about path selection: 1) where to implement path selection? 2) how to coordinate interests of mobile users (i.e., vehicles) and network providers since they have conflicting interests during path selection? and 3) how to ensure seamless service migration during the migration of vehicles? To address the above problems, this article investigates path selection for seamless service migration. We propose a path-selection algorithm to jointly optimize both interests of the network plane (i.e., the cost for network providers) and service plane (i.e., QoE of users). We first formulate it as a multiobjective optimization problem and further prove theoretically that the proposed algorithm can give a weakly Pareto-optimal solution. Moreover, to improve the scalability of the proposed algorithm, a distance-based filter strategy is designed to eliminate undesired switches in advance. We conduct experiments on two synthesized data sets and the results validate the effectiveness of the proposed algorithm.
AB - Mobile-edge computing provisions computing and storage resources by deploying edge servers (ESs) at the edge of the network to support ultralow delay and high bandwidth services. To ensure QoS of latency-sensitive services in vehicular networks, service migration is required to migrate data of the ongoing services to the closest ES seamlessly when users move across different ESs. To achieve seamless service migration, path selection is proposed to obtain one or more paths (consisting of several switches and ESs) to transfer service data. We focus on the following problems about path selection: 1) where to implement path selection? 2) how to coordinate interests of mobile users (i.e., vehicles) and network providers since they have conflicting interests during path selection? and 3) how to ensure seamless service migration during the migration of vehicles? To address the above problems, this article investigates path selection for seamless service migration. We propose a path-selection algorithm to jointly optimize both interests of the network plane (i.e., the cost for network providers) and service plane (i.e., QoE of users). We first formulate it as a multiobjective optimization problem and further prove theoretically that the proposed algorithm can give a weakly Pareto-optimal solution. Moreover, to improve the scalability of the proposed algorithm, a distance-based filter strategy is designed to eliminate undesired switches in advance. We conduct experiments on two synthesized data sets and the results validate the effectiveness of the proposed algorithm.
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U2 - 10.1109/JIOT.2020.3000300
DO - 10.1109/JIOT.2020.3000300
M3 - Article
AN - SCOPUS:85092178294
VL - 7
SP - 9040
EP - 9049
JO - IEEE Internet of Things Journal
JF - IEEE Internet of Things Journal
SN - 2327-4662
IS - 9
M1 - 9109315
ER -