Incentive Mechanism for Cloud Service Offloading in Edge–Cloud Computing Environment
Edge computing refers to provision storage and computation resources at the network edge, closer to end users than the remote cloud. In such edge–cloud computing environments, many cloud providers intend to offload cloud services to the edge nodes to offer high-quality services for data-intensive an...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-05-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/13/10/1685 |
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| author | Chendie Yao Junjie Xie Zhong Liu |
| author_facet | Chendie Yao Junjie Xie Zhong Liu |
| author_sort | Chendie Yao |
| collection | DOAJ |
| description | Edge computing refers to provision storage and computation resources at the network edge, closer to end users than the remote cloud. In such edge–cloud computing environments, many cloud providers intend to offload cloud services to the edge nodes to offer high-quality services for data-intensive and latency-sensitive applications. The major obstacle is that edge nodes are rarely willing to offer resources voluntarily without any rewards. To this end, this paper proposes an efficient incentive mechanism for edge–cloud computing environments using Stackelberg game theory to motivate more edge nodes to host offloaded cloud services. We analyze the properties of the game model and present a solution to compute the unique Stackelberg Equilibrium (SE) of the nonlinear model. On this basis, we propose an efficient polynomial-time algorithm to find the SE. Moreover, we discuss the adaptation of our incentive mechanism to dynamic node joining or departing. Performance evaluations compare our incentive mechanism with three benchmarks and a state-of-the-art mechanism. The results indicate that our incentive mechanism can effectively motivate both the edge nodes and the remote cloud to participate in the edge–cloud environment, achieving maximum resource utilization with minimal rewards while remaining robust in dynamic situations. |
| format | Article |
| id | doaj-art-3c44708be0ad4d52999191dd047f2d96 |
| institution | OA Journals |
| issn | 2227-7390 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj-art-3c44708be0ad4d52999191dd047f2d962025-08-20T02:33:55ZengMDPI AGMathematics2227-73902025-05-011310168510.3390/math13101685Incentive Mechanism for Cloud Service Offloading in Edge–Cloud Computing EnvironmentChendie Yao0Junjie Xie1Zhong Liu2Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, Changsha 410073, ChinaScience and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, Changsha 410073, ChinaScience and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, Changsha 410073, ChinaEdge computing refers to provision storage and computation resources at the network edge, closer to end users than the remote cloud. In such edge–cloud computing environments, many cloud providers intend to offload cloud services to the edge nodes to offer high-quality services for data-intensive and latency-sensitive applications. The major obstacle is that edge nodes are rarely willing to offer resources voluntarily without any rewards. To this end, this paper proposes an efficient incentive mechanism for edge–cloud computing environments using Stackelberg game theory to motivate more edge nodes to host offloaded cloud services. We analyze the properties of the game model and present a solution to compute the unique Stackelberg Equilibrium (SE) of the nonlinear model. On this basis, we propose an efficient polynomial-time algorithm to find the SE. Moreover, we discuss the adaptation of our incentive mechanism to dynamic node joining or departing. Performance evaluations compare our incentive mechanism with three benchmarks and a state-of-the-art mechanism. The results indicate that our incentive mechanism can effectively motivate both the edge nodes and the remote cloud to participate in the edge–cloud environment, achieving maximum resource utilization with minimal rewards while remaining robust in dynamic situations.https://www.mdpi.com/2227-7390/13/10/1685incentive mechanismedge–cloud computingoffloaded cloud serviceStackelberg game |
| spellingShingle | Chendie Yao Junjie Xie Zhong Liu Incentive Mechanism for Cloud Service Offloading in Edge–Cloud Computing Environment Mathematics incentive mechanism edge–cloud computing offloaded cloud service Stackelberg game |
| title | Incentive Mechanism for Cloud Service Offloading in Edge–Cloud Computing Environment |
| title_full | Incentive Mechanism for Cloud Service Offloading in Edge–Cloud Computing Environment |
| title_fullStr | Incentive Mechanism for Cloud Service Offloading in Edge–Cloud Computing Environment |
| title_full_unstemmed | Incentive Mechanism for Cloud Service Offloading in Edge–Cloud Computing Environment |
| title_short | Incentive Mechanism for Cloud Service Offloading in Edge–Cloud Computing Environment |
| title_sort | incentive mechanism for cloud service offloading in edge cloud computing environment |
| topic | incentive mechanism edge–cloud computing offloaded cloud service Stackelberg game |
| url | https://www.mdpi.com/2227-7390/13/10/1685 |
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