A Review of Reliable and Efficient Task Offloading Strategies on Fog Computing Model for IOT Based Applications
TL;DR
This review work is intended to prepare a concise shade of efficient task offloading strategies in the field of fog-embedded IOT systems by classifying the available methods as heuristics, game-theoretic, hybrid approaches and machine learning paradigms.
Abstract
In comparison to traditional centralized cloud method ability of the edifice of inception of Internet of Things (IOT) has demanded the enhancement in the demand for computing environment having less latency, efficiency in energy consumption, performance reliability that has far ahead. These requirements are consolidated by fog computing through shifting of distributed computation near to network edge, wherein which among IOT devices, fog nodes and could hubs workload balancing is the key vital task. In view of maintaining both efficiency and reliability is still a challenge while managing diverse resources and device mobility. This review work is intended to prepare a concise shade of efficient task offloading strategies in the field of fog-embedded IOT systems by classifying the available methods as heuristics, game-theoretic, hybrid approaches and machine learning paradigms. The review meticulously analyzes the latency and Quality of Service (QoS) performance metrics parallely examines the reliability enhancing techniques like fault tolerance and load balancing. To assist development of the scalable, intelligent methods it marks the future research directions at the end.