A Makespan and Energy-Aware Scheduling Algorithm for Workflows under Reliability Constraint on a Multiprocessor Platform
Atharva Tekawade, Suman Banerjee

TL;DR
This paper presents a scheduling algorithm for scientific workflows on multiprocessor systems that minimizes makespan and energy while satisfying reliability constraints, outperforming existing methods.
Contribution
It introduces the MERT and EAFTS algorithms for energy-aware, reliable workflow scheduling and frequency allocation, with proven mathematical validity and superior experimental performance.
Findings
MERT reduces energy by 3.12% and makespan by 14.14% on average.
EAFTS achieves 11.11% lower energy consumption in fault-tolerant scenarios.
Algorithms outperform state-of-the-art approaches in real-world workflow experiments.
Abstract
Many scientific workflows can be modeled as a Directed Acyclic Graph (henceforth mentioned as DAG) where the nodes represent individual tasks, and the directed edges represent data and control flow dependency between two tasks. Due to the large volume of data, multiprocessor systems are often used to execute these workflows. Hence, scheduling the tasks of a workflow to achieve certain goals (such as minimizing the makespan, energy, or maximizing reliability, processor utilization, etc.) remains an active area of research in embedded systems. In this paper, we propose a workflow scheduling algorithm to minimize the makespan and energy for a given reliability constraint. If the reliability constraint is higher, we further propose Energy Aware Fault Tolerant Scheduling (henceforth mentioned as EAFTS) based on active replication. Additionally, given that the allocation of task nodes to…
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Taxonomy
TopicsDistributed and Parallel Computing Systems · Cloud Computing and Resource Management · Scientific Computing and Data Management
