Cloud-assisted context-aware vehicular cyber-physical system for PHEVs in smart grid

Neeraj Kumar, Mukesh Singh, Sherali Zeadally, Joel J.P.C. Rodrigues, Seungmin Rho

Research output: Contribution to journalArticlepeer-review

22 Scopus citations


Plug-in Hybrid Electric Vehicles (PHEVs) can be one of the cost-effective options of modern intelligent transportation systems in smart grid (SG) which can balance the demand and supply by temporarily storing the electrical energy in their batteries. In this paper, we propose a new context-aware layered architecture for demand side management using vehicular cyber-physical system (VCPS) with cloud support. We have used the concept of Bayesian coalition game and learning automata for an intelligent context-aware data collection and processing using a new payoff function for the players in the coalition game. In the proposed scheme, vehicles are assumed as the players which sense the SG environment during their mobility and collect information from it. The players in the game perform actions such as alert generation, and information dissemination. For each action, players receive a feedback from the environment according to which they update their action probability vector. The performance of the proposed scheme shows that there is a reduction in energy shortage by 30%, and information processing delay of 10%-15%. In addition, there is an increase of 15% in energy sold back to the grid using the proposed scheme. The results obtained demonstrate the effectiveness of the proposed scheme.

Original languageEnglish
Pages (from-to)140-151
Number of pages12
JournalIEEE Systems Journal
Issue number1
StatePublished - Mar 2017


  • Learning automata (LA)
  • learning rate
  • mobile cloud
  • Vehicular Cyber-physical Systems (VCPS)

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Information Systems
  • Computer Science Applications
  • Computer Networks and Communications
  • Electrical and Electronic Engineering


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