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Methodologies for the Parallelization, Performance Evaluation and Scheduling of Applications for the Cloud-Edge Continuum

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Advanced Information Networking and Applications (AINA 2024)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 203))

Abstract

This paper outlines a project, started in October 2023, and entitled Methodologies for the Parallelization, Performance Evaluation and Scheduling of Applications for the Cloud-Edge Continuum (MPESACC), aimed at developing a holistic approach to parallelize sequential code across the Cloud-Edge Continuum. MPESACC entails the formulation of a Directive-based programming model, integration of performance analysis, bottleneck identification, scheduling, and optimization techniques for the execution of parallelized code. The proposed model, tailored for Cloud-Edge computing, involves the design of a Compiler software capable of decomposing serial codes, annotated with directives, into distributed components for remote execution. Parallelization techniques conveyed through Parallel Patterns and communication templates in the form of Code Skeletons, simplify transformations and adhere to best practices in code parallelization and distribution. The performance analysis models consider crucial aspects of the Cloud-Edge continuum, such as bandwidth, processing capacity, and energy constraints, providing essential feedback for directive and pattern selection. Scheduling considerations address resource availability and computational needs, optimizing time, energy, storage, and bandwidth constraints. Robust mathematical models support scheduling optimization to prevent task failure or idleness due to temporary resource shortages. The proposed Directives guide scheduling algorithms by providing execution constraints, ensuring informed decisions for optimal task allocation on the Cloud-Edge continuum. Throughout the project, an end-to-end example, involving procedural code, performance analysis, and optimal scheduling, will be developed to demonstrate the feasibility, applicability, and potential of the proposed approach.

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Acknowledgments

This work was partly supported by the Italian Ministry of University and Research (MUR) under the PRIN 2022 grant “Methodologies for the Parallelization, Performance Evaluation and Scheduling of Applications for the Cloud-Edge Continuum” (Master CUP: B53D23013090006, CUP: J53D23007110008, CUP: F53D23004300006) and by the European Union - Next Generation EU.

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Authors and Affiliations

  1. Università Degli Studi Della Campania “Luigi Vanvitelli”, Aversa (CE), Italy

    Antonio Esposito, Rocco Aversa, Beniamino Di Martino & Salvatore Venticinque

  2. Università Cattolica del Sacro Cuore, Milan, Italy

    Enrico Barbierato & Daniele Tessera

  3. Università di Pavia, Pavia, Italy

    Maria Carla Calzarossa, Luisa Massari, Ivan Giuseppe Mongiardo, Luca Zanussi & Rasha Zieni

Authors
  1. Antonio Esposito
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  2. Rocco Aversa
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  3. Enrico Barbierato
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  4. Maria Carla Calzarossa
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  5. Beniamino Di Martino
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  6. Luisa Massari
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  7. Ivan Giuseppe Mongiardo
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  8. Daniele Tessera
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  9. Salvatore Venticinque
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  10. Luca Zanussi
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  11. Rasha Zieni
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Corresponding author

Correspondence to Antonio Esposito .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

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© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Esposito, A. et al. (2024). Methodologies for the Parallelization, Performance Evaluation and Scheduling of Applications for the Cloud-Edge Continuum. In: Barolli, L. (eds) Advanced Information Networking and Applications. AINA 2024. Lecture Notes on Data Engineering and Communications Technologies, vol 203. Springer, Cham. https://doi.org/10.1007/978-3-031-57931-8_25

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