Abstract
Internet of Vehicles(IoV) is a leading technology of the present era. It has gained huge attention with respect to its implementation in wide variety of domains ranging from traffic safety to infotainment applications. However, IoV can also be extended to healthcare domain, where the patients can be provided healthcare services on-the-fly. We extend this novel concept in this paper and refer it as "Healthcare services on-the-fly". The concept of game theory has been used among the vehicles to access the healthcare services while traveling. The vehicles act as players in the game and tend to form and split coalitions to access these services. Learning automata (LA) act as the players for interaction with the environment and take appropriate actions based on reward and penalty. Apart from this, VirtualMachine(VM) scheduling algorithm for efficient utilization of resources at cloud level has also been formulated. A stochastic reward net (SRN)-based model isused to represent the coalition formation and splitting with respect to availability of resources at cloud level. The performance of the proposed scheme is evaluated using various performance evaluation metrics. The results obtained prove the effectiveness of the proposed scheme in comparison to the best, first, and random fit schemes. (C) 2015 Chongqing University of Posts and Telecommunications. Production and Hosting by Elsevier B.V.