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CoOMO: Cost-efficient computation outsourcing with multi-site offloading for mobile-edge services
Tianhui Meng1; Huaming Wu2; Zhihao Shang3; Yubin Zhao1; Cheng-Zhong Xu4
2020-12
Conference Name16th IEEE International Conference on Mobility, Sensing and Networking (MSN)
Source PublicationProceedings - 2020 16th International Conference on Mobility, Sensing and Networking, MSN 2020
Pages113-120
Conference Date17-19 December 2020
Conference PlaceTokyo, Japan
PublisherIEEE
Abstract

Mobile phones and tablets are becoming the primary platform of choice. However, these systems still suffer from limited battery and computation resources. A popular technique in mobile edge systems is computing outsourcing that augments the capabilities of mobile systems by migrating heavy workloads to resourceful clouds located at the edges of cellular networks. In the multi-site scenario, it is possible for mobile devices to save more time and energy by offloading to several cloud service providers. One of the most important challenges is how to choose servers to offload the jobs. In this paper, we consider a multi-site decision problem. We present a scheme to determine the proper assignment probabilities in a two-site mobile-edge computing system. We propose an open queueing network model for an offloading system with two servers and put forward performance metrics used for evaluating the system. Then in the specific scenario of a mobile chess game, where the data transmission is small but the computation jobs are relatively heavy, we conduct offloading experiments to obtain the model parameters. Given the parameters as arrival rates and service rates, we calculate the optimal probability to assign jobs to offload or locally execute and the optimal probabilities to choose different cloud servers. The analysis results confirm that our multi-site offloading scheme is beneficial in terms of response time and energy usage. In addition, sensitivity analysis has been conducted with respect to the system arrival rate to investigate wider implications of the change of parameter values.

KeywordComputation Outsourcing Mobile-edge Computing Multi-site Offloading Queueing Networks
DOI10.1109/MSN50589.2020.00033
URLView the original
Indexed ByCPCI-S
Language英語English
WOS Research AreaComputer Science ; Engineering ; Telecommunications
WOS SubjectComputer Science, Information Systems ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic ; Telecommunications
WOS IDWOS:000682965600016
Scopus ID2-s2.0-85104598254
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Citation statistics
Document TypeConference paper
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Faculty of Science and Technology
THE STATE KEY LABORATORY OF INTERNET OF THINGS FOR SMART CITY (UNIVERSITY OF MACAU)
Corresponding AuthorHuaming Wu
Affiliation1.Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
2.Tianjin University, Tianjin, China
3.Freie Universität Berlin, Berlin, Germany
4.University of Macau,State Key Lab of IoTSC,Dept. of Computer and Information Science,Macao
Recommended Citation
GB/T 7714
Tianhui Meng,Huaming Wu,Zhihao Shang,et al. CoOMO: Cost-efficient computation outsourcing with multi-site offloading for mobile-edge services[C]:IEEE, 2020, 113-120.
APA Tianhui Meng., Huaming Wu., Zhihao Shang., Yubin Zhao., & Cheng-Zhong Xu (2020). CoOMO: Cost-efficient computation outsourcing with multi-site offloading for mobile-edge services. Proceedings - 2020 16th International Conference on Mobility, Sensing and Networking, MSN 2020, 113-120.
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