Resource pooling in vehicular fog computing
Chaogang Tang, Shixiong Xia, Qing Li, Wei Chen, Weidong Fang
Abstract
Abstract Vehicular fog computing (VFC) provisions computing services at the edge of networks by fully exploiting the idle resources of vehicle loaded computer systems. Task scheduling and resource allocation revolved around VFC have gained tremendous attention recently. Currently, most of these works in VFC have focused on response time optimization or energy reduction. Computing services are provisioned in a pay-as-you-go model and vehicles as resource contributors are stimulated by the benefits obtained by leasing these resources. How to maximize their own benefits is one of big concerns but few of current works have recognized its importance in VFC. We in this paper introduce the notion of resource pooling into VFC where the computing resources of vehicles are pooled together to jointly provision computational services in a community. A genetic algorithm based strategy is proposed to solve the optimization problem for the sake of benefit maximization. Extensive experiments have been carried out to evaluate the approach and the numeric results have demonstrated that our strategy outstands other approaches with regards to the optimization objective.