An autonomous compensation game to facilitate peer data exchange in crowdsensing

X. Yan, Fan Ye, Yuanyuan Yang, Xiaotie Deng
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引用次数: 4

Abstract

The rapid penetration of mobile devices has provided ample opportunities for mobile devices to exchange sensing data on a peer basis without any centralized backend. In this paper, we design a peer based data exchanging model, where relay nodes move to certain locations to connect data providers and consumers to facilitate data delivery. Both relays and data providers can gain rewards from consumers who are willing to pay for the data. We first prove the problem of relay node assignment is NP-hard, and provide a centralized optimal method to decide which relay nodes goes to which location with an approximation ratio. Then we define an autonomous compensation game to allow relays make individual decisions without any central authority. We derive a sufficient and necessary condition for the existence of Nash equilibrium. We analyze and compare this distributed game to the centralized social optimal solution, and show that the game incurs small bounded social costs, and efficient under various network sizes, numbers of providers, consumers, and device mobility.
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一个自主补偿游戏,以促进群体感知中的对等数据交换
移动设备的迅速普及为移动设备在对等基础上交换传感数据提供了充足的机会,而无需任何集中的后端。在本文中,我们设计了一个基于对等的数据交换模型,其中中继节点移动到特定位置以连接数据提供者和消费者以促进数据传递。中继者和数据提供者都可以从愿意为数据付费的消费者那里获得奖励。我们首先证明了中继节点分配问题是np困难的,并提供了一种集中式最优方法,以近似比率决定哪些中继节点到哪些位置。然后,我们定义了一个自主补偿博弈,允许继电器在没有任何中央权威的情况下做出个人决定。给出了纳什均衡存在的一个充要条件。我们将这种分布式博弈与集中式社会最优解决方案进行了分析和比较,结果表明,在各种网络规模、供应商数量、消费者数量和设备移动性下,这种博弈产生的有限社会成本很小,而且效率很高。
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