论文标题

协作编码计算卸载:全付拍卖方法

Collaborative Coded Computation Offloading: An All-pay Auction Approach

论文作者

Ng, Jer Shyuan, Lim, Wei Yang Bryan, Garg, Sahil, Xiong, Zehui, Niyato, Dusit, Guizani, Mohsen, Leung, Cyril

论文摘要

由于增强的感应功能和物联网(IoT)设备的增加,众包应用程序收集的数据量迅速增加,因此云服务器不再能够单独处理大型数据集。鉴于边缘设备的计算功能提高,鉴于它允许以分布式方式执行计算任务,同时减轻散乱的效果,因此编码的分布式计算已成为一种有前途的方法,这通常是长期完成整体完成时间。具体而言,通过使用多项式代码,仅需要一部分设备的计算结果来重建最终结果。但是,边缘设备没有动力完成计算任务。在本文中,我们提出了全付拍卖,以激励边缘设备参与编码的计算任务。在此拍卖中,边缘设备的投标是由其中央处理单元(CPU)功率分配给计算任务的代表。所有边缘设备都会提交出价,无论他们在拍卖中获胜还是输。全付拍卖旨在通过确定向获奖者的奖励分配来最大化云服务器的实用性。仿真结果表明,当提供多个奖励而不是单个奖励时,激励边缘设备分配更多的CPU功率。

As the amount of data collected for crowdsensing applications increases rapidly due to improved sensing capabilities and the increasing number of Internet of Things (IoT) devices, the cloud server is no longer able to handle the large-scale datasets individually. Given the improved computational capabilities of the edge devices, coded distributed computing has become a promising approach given that it allows computation tasks to be carried out in a distributed manner while mitigating straggler effects, which often account for the long overall completion times. Specifically, by using polynomial codes, computed results from only a subset of devices are needed to reconstruct the final result. However, there is no incentive for the edge devices to complete the computation tasks. In this paper, we present an all-pay auction to incentivize the edge devices to participate in the coded computation tasks. In this auction, the bids of the edge devices are represented by the allocation of their Central Processing Unit (CPU) power to the computation tasks. All edge devices submit their bids regardless of whether they win or lose in the auction. The all-pay auction is designed to maximize the utility of the cloud server by determining the reward allocation to the winners. Simulation results show that the edge devices are incentivized to allocate more CPU power when multiple rewards are offered instead of a single reward.

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