Convergence Prediction of Mobile Nodes for Energy Transaction in 5G Network

In a smart city paradigm, fossil-fuel-powered vehicles (internal combustion engine vehicles), hybrid vehicles (such as locomotives), and Electric Vehicles (EV) coexist. Surplus energy (such as regenerative energy) from fossils fuel-powered Vehicles also can act as Mobile Distributed Generators (DG) There can be two conditions under which surplus energy can be discharged from a Mobile DG to a consumer. Mobile DG can deliver surplus energy to a stationary roadside Nano/Microgrid (Vehicle to Grid - V2G). The Mobile DG can also deliver it directly to a mobile EV (Vehicle to Vehicle - V2V), which desperately needs recharge in order to continue its journey. In the later condition, as both energy supplier and consumer nodes are mobile, it is mandatory to bring them at a common spatiotemporal location for efficient energy transactions. In this paper we propose a fog based novel mechanism supported by 5G systems where the interoperability amongst “Resource Producers” like DG and “Consumers” like EV, has been considered whereeither or both stakeholders can be mobile. The dynamic convergence of both consumer and producer is calculated by the proposed algorithm and the best possible meeting point is detected for resource transaction.