Performance enhancement of offloading and task scheduling using hybridization of immune with particle swarm optimization algorithm

Abstract

With the development of cloud computing, a computing resource might be provided, and then people will be able to lower the amount of calculation required on mobile systems to save available energy. As a result, mobile cloud computing helps mobile users stores energy by processing the tasks to the cloud. Conversely, though, the effort and expenditure to transfer a big volume of data across a low-resourced network will require a significant quantity of energy. The technique of offloading computation is applied where computations can be moved to an offloading platform from a mobile device that has limited computational resources. newlineTo reduce resource constraints on devices, computing offloading techniques are offered, in the hope that complex calculation works can be moved to powerful machines. Instead of reducing the execution time of devices, task scheduling and offloading is simpler that results in a lot of power consumption. Though current offloading studies does not address the energy usage that goes into transporting data, other offloading technologies that do incorporate this usage are being tested in the lab. All of the offloading strategies are geared towards reducing the amount of local CPU resources needed to carry out a task to reduce energy spent on processing newline