Abstract
With the fast development of Mobile Internet, data traffic generated by end devices is anticipated to witness substantial growth in the future years. However, processing tasks locally will cause latency due to the limited resources of the end devices. Edge-cloud collaboration, an effective solution for latency-sensitive applications, is attracting greater attention from both industry and academia. It combines the advantages of the cloud center with abundant computing resources and edge nodes with low-latency capabilities. In this paper, we propose a two-stage task offloading framework with edge-cloud collaboration to assist end devices processing latency-sensitive tasks either on the edge servers or in the cloud center. As for homogeneous task offloading, in the first stage, the competitive end devices offload tasks to the edge gateways. We formulate the selfish task offloading problem among end devices as a potential game. In the second stage, the edge nodes request resources from the cloud center to process end devices tasks due to their limited resources. Then, we consider the heterogeneous task offloading problem and use intelligent optimization algorithm to obtain the optimal offloading strategy. Simulation results show that the service prices of edge nodes influence the decisions and task offloading costs of end devices. We also verify the intelligent optimization algorithm can achieve optimal performance with low complexity and fast convergence.
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Acknowledgments
This work was supported by the National Natural Science Foundation of China under Grant No. 71971188, the Humanity and Social Science Foundation of Ministry of Education of China under Grant No. 22YJCZH086, the Hebei Natural Science Foundation under Grant Nos. G2022203003 and G2023203008, and the support Funded by Science Research Project of Hebei Education Department under Grant No. ZD2022142. We also would like to express our sincere gratitude to the editor and three anonymous reviewers for their valuable comments, which have greatly improved this paper.
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Shiyong Li received his B.Sc. degree from Qingdao University, Qingdao, his M.Sc. degree from Yanshan University, Qinhuangdao, and his Ph.D. degree from Beijing Jiaotong University, Beijing, China, in 2004, 2007 and 2011, respectively. Currently he is a full professor in the School of Economics and Management at Yanshan University. He is the (co)author of more than 60 papers in mathematics, technique, and management journals. He has been a principal investigator/co-investigator on several research projects supported by the National Natural Science Foundation of China, the National Education Committee Foundation of China, the China Postdoctoral Science Foundation, and other foundations. His research interests include cloud migration for enterprise applications, resource allocation of cloud/edge computing, information systems and electronic commerce, and economics of queues.
Wenzhe Li received her B.Sc. degree from Shandong University, Weihai in 2020 and is currently working toward the PhD degree at the School of Economics and Management, Yanshan University, Qinhuangdao, China. Her research interests include collaborative edge-cloud computing and task offloading.
Huan Liu received his B.Sc. degree from Yanbian University, Yanji in 2018 and is currently working toward the PhD degree at the School of Economics and Management, Yanshan University, Qinhuangdao, China. His research interests include edge computing and service computing.
Wei Sun received her B.Sc. degree from Hebei University, Baoding, and her Ph.D. degree from Yanshan University, Qinhuangdao, China, in 2004 and 2010, respectively. She was a visiting scholar in the Department of Logistics and Maritime Studies at Hong Kong Polytechnic University from June 2009 to April 2010. Currently she is a full professor in the School of Economics and Management at Yanshan University. She has published more than 50 papers in international leading journals in the areas of operations research, and applied mathematics. She has been involved in several projects supported by the National Natural Science Foundation of China, the National Education Committee Foundation of China, and other foundations. Her research interests include economics of queues, and queueing systems with vacations.
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Li, S., Li, W., Liu, H. et al. A Two-stage Service-oriented Task Offloading Framework with Edge-cloud Collaboration: A Game Theory Approach. J. Syst. Sci. Syst. Eng. (2024). https://doi.org/10.1007/s11518-024-5604-1
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DOI: https://doi.org/10.1007/s11518-024-5604-1