Electric vehicles (EVs) have transformed the smart transportation sector by providing diverse energy management solutions to the smart grid. Energy trading among EVs and charging stations (CS) in a vehicle-to-grid (V2G) environment is one of the popular verticals in smart grid. However, processing the energy trading decisions at remote control centers lead to an increase in delay and network overhead. Apart from these issues, the security concerns while trading the energy in such an environment remain persistent. Therefore, to handle the aforementioned issues, this paper presents SURVIVOR: A Blockchain based Edge-as-a-Service Framework for Secure Energy Trading in software defined networking (SDN)-enabled V2G Environment. In the proposed framework, the energy trading decisions are processed closer to the location of EVs through edge nodes. Moreover, for securing the energy trading transactions, blockchain is used wherein the approver nodes are selected amongst all the present nodes on the basis of a utility function and are made responsible for validating the transactions. Once such nodes are selected, a consensus-based blockchain mechanism for secure energy trading in SDN-enabled V2G environment is presented. In this mechanism, edge nodes are responsible for generating proof-of-work puzzles. The proof-of-work is a unique hash value which is computed for each EV and the transactions for which the approver nodes compute the same proof-of-work for each EV are added in the blockchain. The complete scheme is backed by the SDN architecture to reduce the overall latency and increase the throughput of the smart transportation network. The results obtained prove that the proposed scheme is effective for trading the energy between EVs and CS while securing the underlying trading transactions using blockchain. Moreover, the communication and computation cost of the proposed scheme comes out to be small which proves that it can be used in real-world applications. The latency in the complete transportation sector is also greatly reduced by using the SDN-architecture.
This is the author’s version of a work that was accepted for publication in Computer Networks. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computer Networks, 153, 2019 DOI: 10.1016/j.comnet.2019.02.002
