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@article{182986,
        author = {Bhavana Nare},
        title = {Memory-Aware Scheduling in Constrained Environments},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {12},
        number = {no},
        pages = {66-80},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=182986},
        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.},
        keywords = {DAG, Heterogeneous platform, Adaptive scheduling, Memory constraint.},
        month = {},
        }