Optimized Deployment Plans for Platform As a Service Clouds

Benjamin Byholm, Ivan Porres Paltor

Research output: Chapter in Book/Conference proceedingConference contributionScientificpeer-review

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Abstract

We approximately solve the problem of computing deployment plans of multiple cloud services with soft real-time constraints. We recognize that this is a generalized bin packing problem with fragmentable items. We formalize the problem domain and develop an autonomous deployment planning system with soft real-time constraints. The system incorporates a genetic algorithm with quadratic worst-case time complexity for approximately solving the packing problem, providing a service deployment plan with an optimal number of servers and an approximately optimal number of service instances.

Original languageUndefined/Unknown
Title of host publicationUCC '17 Companion : Proceedings of the10th International Conference on Utility and Cloud Computing
EditorsGeoffrey Fox, Yong Chen
PublisherACM
Pages41–46
ISBN (Print)978-1-4503-5195-9
DOIs
Publication statusPublished - 2017
MoE publication typeA4 Article in a conference publication
EventIEEE/ACM International Conference on Utility and Cloud Computing (UCC) - 10th International Conference on Utility and Cloud Computing (UCC '17)
Duration: 5 Dec 20178 Dec 2017

Conference

ConferenceIEEE/ACM International Conference on Utility and Cloud Computing (UCC)
Period05/12/1708/12/17

Keywords

  • cloud computing

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