Gamified incentive sharing mechanism of edge computing among edge service providers

被引:3
作者
Du, Helen S. [1 ,2 ]
Lin, Yixun [1 ]
Zhang, Fenghua [1 ,2 ,3 ]
Zhang, Depeng [1 ,2 ]
机构
[1] Guangdong Univ Technol, Sch Management, Guangzhou 510520, Peoples R China
[2] GHM Greater Bay Area Brand Strategy Res Ctr, Guangzhou 510520, Peoples R China
[3] Guangdong Univ Technol, Sch Management, 161 Tianhe Rd, Guangzhou 510520, Guangdong, Peoples R China
基金
中国国家自然科学基金;
关键词
Edge computing; Throughput; Gamified mechanism; Process sharing; System efficiency; RESOURCE-ALLOCATION; EFFICIENCY; GAMIFICATION; MAXIMIZATION; DESIGN;
D O I
10.1016/j.jclepro.2022.134168
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Edge computing is important for the efficiency of an entire system. It makes the Internet of Things technologies more sustainable and improves users' experience and satisfaction. Generally, owing to the heterogeneity of edge servers, computing resources are unbalanced, resulting in energy wastage. Existing studies, however, have only focused on incentive mechanisms for edge collaboration; therefore, the willingness of edge servers to share re-sources needs further exploration. Furthermore, few studies have considered more than one edge service pro-vider (ESP) in the incentive mechanism, which is unsustainable for selfish ESPs to optimize their computing resource allocation process. To deal with this issue, a gamified process is introduced into edge computing. Then, a system throughput maximization problem is proposed to utilize idle resources through gamification-based edge cooperation. This is proven to be a non-deterministic polynomial-time hard problem. To resolve this problem, a greedy algorithm is proposed. The experimental results demonstrate that the proposed algorithm improves the throughput by ranges of [36.9%, 87.2%] and [10.0%, 13.1%] when compared with that from no gamification and an existing greedy algorithm, respectively, when considering the influential factors. The proposed gamified mechanism helps to improve system efficiency by reducing idle computing resources and motivating ESPs to process share during production, which further enhances the smart utilization of limited global resources.
引用
收藏
页数:11
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