Residential College | false |
Status | 已發表Published |
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 Name | 16th IEEE International Conference on Mobility, Sensing and Networking (MSN) |
Source Publication | Proceedings - 2020 16th International Conference on Mobility, Sensing and Networking, MSN 2020 |
Pages | 113-120 |
Conference Date | 17-19 December 2020 |
Conference Place | Tokyo, Japan |
Publisher | IEEE |
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. |
Keyword | Computation Outsourcing Mobile-edge Computing Multi-site Offloading Queueing Networks |
DOI | 10.1109/MSN50589.2020.00033 |
URL | View the original |
Indexed By | CPCI-S |
Language | 英語English |
WOS Research Area | Computer Science ; Engineering ; Telecommunications |
WOS Subject | Computer Science, Information Systems ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic ; Telecommunications |
WOS ID | WOS:000682965600016 |
Scopus ID | 2-s2.0-85104598254 |
Fulltext Access | |
Citation statistics | |
Document Type | Conference paper |
Collection | DEPARTMENT 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 Author | Huaming Wu |
Affiliation | 1.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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