Providing Reliable Service for Parked-vehicle-assisted Mobile Edge Computing

Author:

Zhou Ao1ORCID,Ma Xiao1,Gao Siyi1,Wang Shangguang1

Affiliation:

1. State Key Laboratory of Network and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, P.R. China

Abstract

Nowadays, a growing number of computation-intensive applications appear in our daily life. Those applications make the loads of both the core network and the mobile devices, in terms of energy and bandwidth, hugely increase. Offloading computation-intensive tasks to edge cloud is proposed to address this issue. Since edge clouds have limited computation resources compared with the remote cloud, they would get over-loaded because of the heavy computation burden. Parked-vehicle-assisted mobile edge computing becomes one of the promising solutions for this problem. However, several critical issues in parked-vehicle-assisted mobile edge computing would result in low reliable edge service. The open environment would bring about uncertainty, and the data privacy is hard to ensure. In addition, different from edge cloud, each parked vehicle only has limited parking duration and can leave unexpectedly for personal reasons. Moreover, edge cloud and vehicle adopt different execution models of computation and communication. The heterogeneous environment may result in negative effect on cooperativeness. Ignoring those issues can result in substantial performance degradation. To tackle this challenge and explore the benefits of parked-vehicle-assisted offloading, we study the task offloading and resource-allocation problem by fully considering the above issues. First, we propose a resource-management scheme to address the privacy issue. Second, we review the execution model of computation and communication in parked-vehicle-assisted computation offloading. Then, we formulate the problem into a mixed-integer nonlinear programming. The problem is hard to tackle due to its non-convex nature, which means that the time complexity of finding global optimal solution is unaffordable. Finally, we decompose the original problem into two sub-problems with lower complexity, and related algorithms are given to deal with the sub-problems. Simulation results demonstrate the effectiveness of the proposed solution.

Funder

National Key R&D Program of China

NSFC

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. EV-Assisted Computing for Energy Cost Saving at Edge Data Centers;IEEE Transactions on Mobile Computing;2024-09

2. A Block-Structured Optimization Approach for Data Sensing and Computing in Vehicle-Assisted Edge Computing Networks;IEEE Sensors Journal;2024-01-01

3. UNION: Fault-tolerant Cooperative Computing in Opportunistic Mobile Edge Cloud;ACM Transactions on Internet Technology;2023-11-17

4. Offloading Utility Optimization in Parked Vehicular Edge Computing;2023 14th International Conference on Information and Communication Technology Convergence (ICTC);2023-10-11

5. Partial Computation Offloading in Parked Vehicle-Assisted Multi-Access Edge Computing: A Game-Theoretic Approach;IEEE Transactions on Vehicular Technology;2022-09

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3