PeAOA: A Novel Pelican Addax Optimization-based Task Scheduling for Workflow Applications in DVFS-enabled Cloud

In recent years, cloud computing has been extensively used for executing workflow applications, and with this increased adoption, maintaining a tradeoff between energy efficiency and performance remains crucial.Though Dynamic Voltage and Frequency Scaling (DVFS) is found to be an effective tool in decreasing the energy consumption at the processor, it may lead to missed deadlines if not integrated with an efficient task scheduling framework.Hence, this research designs a novel Pelican Addax Optimization Algorithm (PeAOA) framework for task scheduling in the DVFS-enabled cloud.At first, task scheduling is performed according to the Triplet rank model based on bandwidth, compatibility, and execution time.This task scheduling process may not be optimal, so task rescheduling is performed by using PeAOA, considering the energy consumption.Further, due to the precedence constraints between tasks, spare time slots may exist among every pair of neighboring tasks on non-critical workflow paths.To fully take advantage of these spare time slots, a reliability-aware DVFS algorithm is applied.Experimental evaluation shows that PeAOA attained the minimum execution time, energy consumption, and makespan of 2.989 sec, 10265 J, and 1.687, and maximum reliability and memory of 0.947 and 10.5 MB using DVFS simulator for real workflows energy aware management in green cloud computing database.