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Incentive Mechanism for Edge Cloud Profit Maximization in Mobile Edge Computing

机译:移动边缘计算中边缘云利润最大化的激励机制

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Mobile edge computing (MEC) has become a promising technique to accommodate demands of resource-constrained mobile devices by offloading the task onto edge clouds nearby. However, most existing works only focus on whether or where a task is offloaded but ignore the motivation of the edge cloud to offer service. To stimulate service provisioning by edge clouds, it is essential to design an incentive mechanism that charges mobile devices and rewards edge clouds. In this paper, we utilize market-based pricing model to establish a relationship between the resources provided by edge clouds and the price paid by the mobile devices in a non-competitive environment. Furthermore, we design a profit maximization multi-round auction (PMMRA) mechanism for the resource trading between edge clouds as sellers and mobile devices as buyers in a competitive environment. The mechanism can effectively determine the price paid by the buyers to use the resources provided by the sellers and make the corresponding match between edge clouds and mobile devices. Finally, numerical results show that proposed mechanism outperforms other existing algorithms in maximizing the profits of resource providers.
机译:通过将任务转移到附近的边缘云上,移动边缘计算(MEC)已成为一种有前途的技术来满足资源受限的移动设备的需求。但是,大多数现有作品仅关注任务是否被卸载或在何处被卸载,而忽略了边缘云提供服务的动机。为了刺激边缘云提供服务,必须设计一种激励机制,向移动设备收费并奖励边缘云。在本文中,我们利用基于市场的定价模型在非竞争环境中建立边缘云提供的资源与移动设备支付的价格之间的关系。此外,我们设计了一种利润最大化的多轮拍卖(PMMRA)机制,用于在竞争环境中作为卖方的边缘云与作为买方的移动设备之间的资源交易。该机制可以有效地确定买方为使用卖方提供的资源而付出的价格,并在边缘云和移动设备之间进行相应的匹配。最后,数值结果表明,在最大化资源提供者的利润方面,所提出的机制优于其他现有算法。

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