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Efficient Resource Scheduling for Distributed Infrastructures using Negotiation Capabilities
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.ORCID iD: 0000-0002-3123-3478
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.ORCID iD: 0000-0003-0302-6276
2023 (English)In: 2023 IEEE 16th International Conference on Cloud Computing (CLOUD), Institute of Electrical and Electronics Engineers (IEEE), 2023, p. 486-492Conference paper, Published paper (Refereed)
Abstract [en]

The information explosion drives enterprises and individuals to rent cloud computing infrastructure for their applications in the cloud. However, the agreements between cloud computing providers and clients are often inefficient. We propose an agent-based auto-negotiation system for resource scheduling using fuzzy logic. Our method completes a one-to-one auto-negotiation process and generates optimal offers for providers and clients. We compare the impact of different member functions, fuzzy rule sets, and negotiation scenarios on the offers to optimize the system. Our proposed method efficiently utilizes resources and offers interpretability, high flexibility, and customization. We successfully train machine learning models to replace the fuzzy negotiation system, improving processing speed. The article also highlights potential future improvements to the proposed system and machine learning models. All codes and data are available as an open source repository.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2023. p. 486-492
Series
IEEE International Conference on Cloud Computing, ISSN 2159-6182, E-ISSN 2159-6190
Keywords [en]
distributed infrastructure, cloud computing, fuzzy logic, negotiation, intelligent agent, machine learning
National Category
Computer Sciences
Research subject
Scientific Computing; Computer Science
Identifiers
URN: urn:nbn:se:uu:diva-509838DOI: 10.1109/CLOUD60044.2023.00065ISI: 001085065100055ISBN: 979-8-3503-0481-7 (electronic)ISBN: 979-8-3503-0482-4 (print)OAI: oai:DiVA.org:uu-509838DiVA, id: diva2:1790599
Conference
IEEE 16th International Conference on Cloud Computing (CLOUD), 2-8 July, 2023, Chicago, IL, USA
Projects
eSSENCE - An eScience Collaboration
Funder
Swedish National Infrastructure for Computing (SNIC)eSSENCE - An eScience CollaborationAvailable from: 2023-08-23 Created: 2023-08-23 Last updated: 2023-11-14Bibliographically approved

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Singh, PrashantToor, Salman

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