A Task Offloading Solution for Internet of Vehicles Using Combination Auction Matching Model Based on Mobile Edge Computing

Abstract

From a global perspective, an Internet of Vehicles task offloading solution based on mobile edge computing is proposed, which satisfies the application requirements (high reliability) strictly. The average time for completing a task can be minimized with the reasonable task offloading solution. Firstly, we model the wireless network, the transmission time and the movement of vehicles. Besides, heterogeneous wireless network architecture is adopted, data centers are deployed at Small-cell Base Stations, Macro-cell Base Stations and Internet. Then considering the limitedness, heterogeneity and task diversity of resources, we utilize matching model based on combination auction to design the offloading model. Furthermore, the multi-round sequential combination auction mechanism is proposed, which equals the matching problem to the multi-dimensional grouping knapsack problem and uses dynamic programming to get the optimal match. This solution is based on virtual machine technology and voltage scaling technology in the task execution time model. Moreover, the computing resources can be measured by CPU frequency. We propose an optimization problem for the shortest average task completion time with limited resources. Finally, the effects of these parameters (such as the number of tasks per unit time, the amount of data offloaded and the number of CPU cycles) on the task execution efficiency are analyzed and compared with other algorithms by simulation experiments. Compared to existing schemes, simulation results show that the proposed algorithm can reduce system overhead and shorten task execution time effectively. INDEX TERMS Internet of Vehicles, task offloading, heterogeneous wireless network architecture, mobile edge computing, combination auction, channel gain.

Applications of Auction and Mechanism Design in Edge Computing: A Survey

“…Although EC is an efficient solution for processing computing intensive and latency-sensitive tasks of edge devices, the limited resources of edge servers restrict its application and development. As a popular trading form, auction can efficiently allocate resources while satisfying the heterogeneous requirements of both SPs and SRs [38], [41], [52], [74], [106], [141]. Thus, it has attracted a lot of research interests recently.…”

“…Then, the problem is to determine the winners and the price that each winner needs to pay. To solve this problem, some optimization algorithms can be applied, e.g., dynamic programming (DP) [44], [47], [51], [52], greedy algorithm [38], [42], [61] and graph neural networks [159].…”

“…In recent years, considerable attentions have been focused on combinatorial auction to deal with combinatorial allocation problems [? ], [37], [38], [41], [42], [44], [47], [52], [56], [61], [65], [66]. As shown in Table II, we summarize the above-mentioned work in terms of the issue, objective, market structure (i.e., seller, buyer, auctioneer, commodity), scenarios and advantages.…”

“…In order to improve task offloading efficiency in terms of tasks execution time, the authors in [52] described the task offloading problem as a multi-round sequential combination auction by considering mobile vehicles and macro-cell/smallcell base station (MBS/SBS) to be the buyers and sellers, respectively. The mobile devices have heterogeneous resource requirements and the MBS/SBS deploy various service nodes with limited wireless and computing resources.…”

“…Similar to [44], [47], [51], [52], the authors in [56] took economic properties, users' QoS and resource allocation efficiency into account to design a combinatorial auction mechanism based on a dynamic resource allocation model. The model is composed of fog nodes, i.e., sellers, each of which owns heterogeneous computing resources (contains CPU and memory resource) and is deployed around buyers, MDs, i.e., buyers, which need to offload heterogeneous tasks to fog nodes, and a trustworthy third party, i.e., an auctioneer, which administrates the auction process.…”