Collaborative Coded Computation Offloading: An All-pay Auction Approach

TL;DR

This paper introduces an all-pay auction mechanism to incentivize edge devices in coded distributed computing, improving task participation and efficiency in IoT data processing.

Contribution

It proposes a novel auction-based incentive scheme for coded computation offloading, aligning edge device participation with cloud server utility.

Findings

Edge devices allocate more CPU power with multiple rewards.

The auction incentivizes higher participation in coded computation.

Simulation confirms improved resource allocation and task completion.

Abstract

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.