A Blockchain Based Matching Game for Content Sharing in Content-Centric Vehicle-to-Grid Network Scenarios

• Published in: IEEE transactions on intelligent transportation systems 2024-05, Vol.25 (5), p.4032-4048
• Main Authors: Miglani, Arzoo, Kumar, Neeraj
• Format: Article
• Language: English
• Subjects: Algorithms; Benchmarks; blind matching algorithm; Blockchains; caching; CCN; content sharing; Cryptography; Electric vehicles; Energy consumption; Ethereum; Game theory; Matching; matching theory; Network latency; Performance evaluation; proof-of-authority; Proposals; Quality of service; Reliability; Stability criteria; V2G; Vehicle-to-grid
• ISSN: 1524-9050; 1558-0016
• DOI: 10.1109/TITS.2023.3322826

In recent times, content-centric network has been evolved as one of the most popular technologies of the modern era, facilitating cache content-based data sharing, especially in vehicle-to-grid (V2G) networks. However, to get benefits from content-based caching services, it is essential to match the service providers with service requesters optimally during high mobility vehicles scenarios. Most of the existing literature proposals for this problem are based upon the centralized architecture, which may be vulnerable to congestion matching operations, with a lack of trustworthiness among nodes. Also, a content holder may spread fake information about content availability to requesters, which may affect the performance of any implemented solution in this environment. In this paper, we model the two-sided preferences of both parties (service providers and requesters) to maximize the cache content sharing using content centric network (CCN) communications. Then, we formulated a decentralized matching problem with joint transmit power of both the content providers and requesters. The framed matching game involves aspiration level and agreement functions for both the parties. Finally, a distributed blind matching algorithm (BLMA) is also proposed, which is executed by deploying a smart contract on the Ethereum network without involving an intermediate authority. Moreover, we provide the theoretical analysis on the number of successive iterations for convergence of the proposed BLMA algorithm. To verify and validate the effectiveness of the proposal, we compare it with three benchmark schemes and evaluated its performance with respect to average individual utility, latency, and energy consumption on the benchmark data sets. The results obtained show that the proposed scheme is superior in comparison to the existing state-of-the-art solutions with respect to various performance evaluation metrics.