Efficient task scheduling in heterogeneous computing environments is imperative for optimizing resource utilization and minimizing task completion times. In this study, we conducted a comprehensive benchmarking analysis to evaluate the performance of four scheduling algorithms First Come, First-Served (FCFS), FCFS with No Queuing (FCFS-NQ), Minimum Expected Completion Time (MECT), and Minimum Expected Execution Time (MEET) across varying workload scenarios. We defined three workload scenarios: low, medium, and high, each representing different levels of computational demands. Through rigorous experimentation and analysis, we assessed the effectiveness of each algorithm in terms of total completion percentage, energy consumption, wasted energy, and energy per completion. Our findings highlight the strengths and limitations of each algorithm, with MECT and MEET emerging as robust contenders, dynamically prioritizing tasks based on comprehensive estimates of completion and execution times. Furthermore, MECT and MEET exhibit superior energy efficiency compared to FCFS and FCFS-NQ, underscoring their suitability for resource-constrained environments. This study provides valuable insights into the efficacy of task scheduling algorithms in heterogeneous computing environments, enabling informed decision-making to enhance resource allocation, minimize task completion times, and improve energy efficiency

翻译：在异构计算环境中，高效的任务调度对于优化资源利用和缩短任务完成时间至关重要。本研究通过全面的基准测试分析，评估了四种调度算法——先来先服务（FCFS）、无排队先来先服务（FCFS-NQ）、最小预期完成时间（MECT）和最小预期执行时间（MEET）——在不同工作负载场景下的性能表现。我们定义了低、中、高三种工作负载场景，分别代表不同级别的计算需求。通过严格的实验与分析，我们从总完成百分比、能耗、浪费能量以及单位完成能耗四个维度评估了各算法的有效性。研究结果揭示了每种算法的优势与局限：MECT和MEET作为稳健的候选算法，能够基于完成时间和执行时间的综合估计动态进行任务优先级排序。此外，与FCFS和FCFS-NQ相比，MECT和MEET展现出更优的能效表现，凸显其适用于资源受限环境。本研究为异构计算环境中任务调度算法的有效性提供了重要见解，有助于在资源分配优化、任务完成时间最小化和能效提升方面做出科学决策。