Adaptive Multicore Task Scheduling with Dynamic Voltage and Frequency Scaling for Reduced Energy Consumption
DOI:
https://doi.org/10.5281/zenodo.20393551Keywords:
Power Optimization, Energy-Efficient Task Scheduling, Dynamic Voltage and Frequency Scaling (DVFS), Workload Management, Multicore ProcessorsAbstract
Dynamic Voltage and Frequency Scaling (DVFS) is a successful method to save energy in multi-core systems. However, if heterogeneous tasks having varying number of computations and time requirements are given to different cores, it is a big challenge to run those tasks on time with minimum energy consumption. If these tasks are not scheduled correctly, they can result in higher energy consumption, loss of resources, and compromised system performance. To overcome the aforementioned challenges, a task scheduling framework for multicore processor systems with DVFS is proposed in this work. The proposed architecture is based on an Adaptive DVFS control along with a central scheduling mechanism. First, tasks are analyzed as they are received to determine the time constraints and resources needed. The DVFS mechanism dynamically modifies the operating voltage and frequency of the processing cores depending on the processor configuration in order to provide energy efficient execution. The proposed scheduling strategy then distributes the tasks to the appropriate processor cores for efficient execution. The scheduling problem is modeled as an optimization problem which minimizes the total amount of energy used while meeting a task's deadlines. Moreover, the proposed approach consumes less queuing delay, which enhances the scheduling efficiency and reduces the execution latency. Experimental and comparative analysis results show that the proposed framework has higher energy efficiency and task scheduling effectiveness than the previous ones.
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