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Author: search.filters.author.Birajdar, P.A.Subject: search.filters.subject.Matching theory

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    DCRDA: deadline-constrained function scheduling in serverless-cloud platform
    (Springer, 2025) Birajdar, P.A.; Meena, D.; Satpathy, A.; Addya, S.K.
    The serverless computing model frees developers from operational and management tasks, allowing them to focus solely on business logic. This paper addresses the computationally challenging function-container-virtual machine (VM) scheduling problem, especially under stringent deadline constraints. We propose a two-stage holistic scheduling framework called DCRDA targeting deadline-constrained function scheduling. In the first stage, the function-to-container scheduling is modeled as a one-to-one matching game and solved using the classical Deferred Acceptance Algorithm (DAA). The second stage addresses the container-to-VM assignment, modeled as a many-to-one matching problem, and solved using a variant of the DAA, the Revised-Deferred Acceptance Algorithm (RDA), to account for heterogeneous resource demands. Since matching-based strategies require agent preferences, a Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) ranking mechanism is employed to prioritize alternatives based on execution time, deadlines, and resource demands. The primary goal of DCRDA is to maximize the success ratio (SR), defined as the ratio of functions executed within the deadline to the total functions. Extensive test-bed validations over commercial providers such as Amazon EC2 show that the proposed framework significantly improves the success ratio compared to baseline approaches. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.