Profitable Task Allocation in Mobile Cloud Computing

TL;DR

This paper introduces a game theoretic auction-based framework for task offloading in mobile cloud computing, significantly reducing job completion times while ensuring truthful participation and minimizing auction overheads.

Contribution

It presents a novel auction mechanism that incentivizes truthful reporting of capabilities and costs, and adapts to node mobility through dynamic auction scheduling.

Findings

Job completion time improved by 2-5 times compared to local execution.

The auction mechanism ensures truthful reporting and benefits participating nodes.

Adaptive auction scheduling reduces overheads and handles mobility effectively.

Abstract

We propose a game theoretic framework for task allocation in mobile cloud computing that corresponds to offloading of compute tasks to a group of nearby mobile devices. Specifically, in our framework, a distributor node holds a multidimensional auction for allocating the tasks of a job among nearby mobile nodes based on their computational capabilities and also the cost of computation at these nodes, with the goal of reducing the overall job completion time. Our proposed auction also has the desired incentive compatibility property that ensures that mobile devices truthfully reveal their capabilities and costs and that those devices benefit from the task allocation. To deal with node mobility, we perform multiple auctions over adaptive time intervals. We develop a heuristic approach to dynamically find the best time intervals between auctions to minimize unnecessary auctions and the accompanying overheads. We evaluate our framework and methods using both real world and synthetic mobility traces. Our evaluation results show that our game theoretic framework improves the job completion time by a factor of 2-5 in comparison to the time taken for executing the job locally, while minimizing the number of auctions and the accompanying overheads. Our approach is also profitable for the nearby nodes that execute the distributor's tasks with these nodes receiving a compensation higher than their actual costs.