CARaM: Coordinated Adaptive Replica Management for Charging Stations

Abstract

With an exponential increase in the penetration of electric vehicles in modern smart communities, the dependency on traditional fuel is decreasing from the last few years. However, to find an optimal and available place for charging of electric vehicles is still one of the challenging tasks. To address this issue, this paper proposes a technique to find the solution for coordinated charging using available infrastructures such as ZigBee network, remote sensors and street lights. The proposed solution is to use street lights as intelligent agents and connect them to a ZigBee network to the cloud database. Street lights are considered as base stations to send information regarding the status of a charging station (CS) to the database using the ZigBee network. An Algorithm Coordinated Adaptive Replica Management (CARaM) for CS is designed which is based on Iterative Deepening Depth First Search that uses the aforementioned information for the availability of CS in a geographical region. The nodes (CS) are stored in Binary Tree for fast retrieval of the information. The proposed solution has been evaluated and compared to other existing algorithms such as Breadth-first search and Depth-first search algorithms. The results obtained clearly demonstrate the superiority of the proposed solution with respect to the parameters such as overhead generated and less storage which are important variables.