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首页> 外文会议>International conference on algorithms and architectures for parallel processing >COUSTIC: Combinatorial Double Auction for Crowd Sensing Task Assignment in Device-to-Device Clouds
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COUSTIC: Combinatorial Double Auction for Crowd Sensing Task Assignment in Device-to-Device Clouds

机译：COUSTIC：针对设备到设备云中的人群感知任务分配的组合两次拍卖

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摘要

With the emerging technologies of Internet of Things (IOTs), the capabilities of mobile devices have increased tremendously. However, in the big data era, to complete tasks on one device is still challenging. As an emerging technology, crowdsourcing utilizing crowds of devices to facilitate large scale sensing tasks has gaining more and more research attention. Most of existing works either assume devices are willing to cooperate utilizing centralized mechanisms or design incentive algorithms using double auctions. There are two cases that may not practical to deal with, one is a lack of centralized controller for the former, the other is not suitable for the seller device's resource constrained for the later. In this paper, we propose a truthful incentive mechanism with combinatorial double auction for crowd sensing task assignment in device-to-device (D2D) clouds, where a single mobile device with intensive sensing task can hire a group of idle neighboring devices. With this new mechanism, time critical sensing tasks can be handled in time with a distributed nature. We prove that the proposed mechanism is truthful, individual rational, budget balance and computational efficient.
机译：随着物联网（IOT）的新兴技术，移动设备的功能已大大提高。但是，在大数据时代，在一台设备上完成任务仍然具有挑战性。作为一种新兴技术，利用大量设备进行大规模传感任务的众包已经越来越受到研究的关注。现有的大多数作品要么假设设备愿意利用集中机制进行协作，要么使用双重拍卖来设计激励算法。有两种情况可能不切实际，一种是前者缺乏集中控制器，另一种是不适合后者所限制的卖方设备资源。在本文中，我们为设备对设备（D2D）云中的人群感知任务分配提出了一种具有组合双拍卖的真实激励机制，其中具有密集感知任务的单个移动设备可以雇用一组空闲的邻近设备。使用这种新机制，可以及时处理具有时间紧急性的感知任务，并且具有分布式特性。我们证明了所提出的机制是真实，个人理性，预算平衡和计算效率高的。

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