Adaptive Workload Management for Enhanced Function Performance in Serverless Computing

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dc.contributor.authorBirajdar, P.A.
dc.contributor.authorHarsha, V.
dc.contributor.authorSatpathy, A.
dc.contributor.authorAddya, S.K.
dc.date.accessioned2026-02-06T06:33:14Z
dc.date.issued2025
dc.description.abstractServerless computing streamlines application deployment by removing the need for infrastructure management, but fluctuating workloads make resource allocation challenging. To solve this, we propose an adaptive workload manager that intelligently balances workloads, optimizes resource use, and adapts to changes with auto-scaling, ensuring efficient and reliable serverless performance. Preliminary experiments demonstrate an ≈ 0.6X% and 2X% improvement in execution time and resource utilization compared to the First-Come-First-Serve (FCFS) scheduling algorithm. © 2025 Copyright held by the owner/author(s).
dc.identifier.citationICDCN 2025 - Proceedings of the 26th International Conference on Distributed Computing and Networking, 2025, Vol., , p. 276-277
dc.identifier.urihttps://doi.org/10.1145/3700838.3703657
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/28523
dc.publisherAssociation for Computing Machinery, Inc
dc.subjectAuto-scaling
dc.subjectLoad Balancing
dc.subjectScheduling
dc.subjectServerless Computing
dc.titleAdaptive Workload Management for Enhanced Function Performance in Serverless Computing

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