Novel Power-Aware Optimization Methodology and Efficient Task Scheduling Algorithm

The performance of central processing units(CPUs)can be enhanced by integrating multiple cores into a single chip.Cpu performance can be improved by allocating the tasks using intelligent strategy.If Small tasks wait for long time or executes for long time,then CPU consumes more power.Thus,the amount of power consumed by CPUs can be reduced without increasing the frequency.Lines are used to connect cores,which are organized together to form a network called network on chips(NOCs).NOCs are mainly used in the design of processors.However,its performance can still be enhanced by reducing power consumption.The main problem lies with task scheduling,which fully utilizes the network.Here,we propose a novel randomfit algorithm for NOCs based on power-aware optimization.In this algorithm,tasks that are under the same application are mapped to the neighborhoods of the same application,whereas tasks belonging to different applications are mapped to the processor cores on the basis of a series of steps.This scheduling process is performed during the run time.Experiment results show that the proposed randomfit algorithm reduces the amount of power consumed and increases system performance based on effective scheduling.