Memory-Aware Scheduling in Constrained Environments

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Bhavana Nare

Memory-Aware Scheduling in Constrained Environments

Authors: Bhavana Nare

Unique Paper ID: 182986
Volume: 12
Issue: no
PageNo: 66-80

Keywords: DAG Heterogeneous platform Adaptive scheduling Memory constraint.

Abstract:
This paper addresses the challenge of scheduling workflows in memory-constrained environments where tasks may exceed the available memory on processors. I propose three memory-aware HEFT-based heuristics: HEFTM-BL, HEFTM- BLC, and HEFTM-MM, designed to produce valid schedules by accounting for memory limitations. Experimental evaluations on default and memory-constrained clusters demonstrate the superiority of memory-aware heuristics over the baseline HEFT, which frequently produces invalid schedules. Among the pro- posed methods, HEFTM-MM achieves a 100% success rate for large workflows under severe memory constraints but at the cost of increased makespan and runtime. Additionally, I explore dynamic scenarios with evolving task parameters, highlighting the necessity of adaptive scheduling to prevent execution failures. The study provides a foundation for memory-efficient scheduling in static and dynamic environments and opens avenues for extending the model to handle heterogeneous bandwidths, task variability, and platform dynamics.

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Cite This Article

ISSN: 2349-6002
Volume: 12
Issue: no
PageNo: 66-80

Memory-Aware Scheduling in Constrained Environments

Available:https://ijirt.org/article?manuscript=182986

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