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Exploring Quantum Computing Algorithms for Effective Task Scheduling in Computing Systems

Task scheduling is a critical problem within the modern underlying computing infrastructure, where resource overload causes a direct impact on the cost and time performance metrics, leading to increased latency, excessive financial cost, and overall poor throughput. Traditional scheduling algorithms are normally fixed and lack the strong exploration and exploitation processes, hence limiting their effectiveness when faced with large problems in scheduling, which are NP-hard. The current work investigates Quantum Computing (QC)-algorithms including Grover, the Variational Quantum Eigensolver (VQE) and Quantum Annealing (QA). This research work includes an extensive experiment conducted in the WorkflowSim simulator with heterogeneous task-scheduling performed with diverse Virtual Machine (VM) configurations. The performance-metrics considered for their comparison include cost and time, along with Relative Performance Index …

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