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Mobile edge computing (MEC) is a technology deployed at the edge of mobile networks to enhance computation capabilities and reduce transmission distances. It has been extensively researched in the context of both the internet of things (IoT) and 5G communication. Recently, unmanned aerial vehicles (UAVs) have been integrated into MEC networks to create a novel architecture that utilizes line-of-sight (LOS) transmission links. In this architecture, UAVs act as relay nodes to facilitate the offloading of computing tasks from UAVs to edge computing stations (ECSs). However, the problem of creating an incentive system that guarantees the confidentiality and integrity of communication while simultaneously making it easier for UAVs and ECSs to coordinate a variety of activities remains unsolved. Consequently, this paper proposes a blockchain-based architecture for UAV-assisted MEC networks that addresses the aforementioned issues of security and privacy and investigates the problem of multi-task matching based on this architecture. A joint optimization problem is explicitly proposed to maximize both task completion rates and social welfare. Consequently, the formulated problem is decomposed into two subproblems: 1) The double auction problem, which aims to maximize societal utility and determines the winning pairs and trading price; and 2) The auction losers matching problem, which aims to increase task completion rates. Then, to identify the appropriate matching pairings and establish the trading price, a satisfaction breakeven-based double auction (SBDA) method is suggested. Sequentially, two auction losers’ second selection schemes, the shortest distance (SD) and the largest difference (LD) scheme are proposed to realize second matching to enhance the task completion rate. Finally, numerical simulations are given to show the effectiveness of the proposed mechanism. Particularly, the SBDA+LD mechanism has the best system utility and overall income compared with other schemes. |
