Nature inspired computational offloading in fog-cloud of things ecosystem for smart city applications

Abstract

Studies leading to optimization of resources and applications in the fog-cloud of things ecosystems have gained importance. This is because these studies form the basis upon which improved performance of Internet of Things(IoT) infrastructure can be realized. In this study, we explore heuristic approach that permits offloading to optimal offsite fog by developing modified dynamic PSO(mDyPSO) mechanism. We compared our results with the traditional simple PSO(SiPSO). Our simulation results show that mDyPSO out performs SiPSO in terms of application latency, network usage and energy utilization. We note that our mDyPSO offloading mechanism improves network performance up to one third. We conclude that mDyPSO mechanism performs well in fluctuating topology. This further proves that considering multiple computational parameters to modify PSO yield better offloading Results.