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A metric and mixed-integer-programming-based approach for resource allocation in dynamic real-time systems

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dc.contributor.authorSiegel, Howard Jay, author
dc.contributor.authorMaciejewski, Anthony A., author
dc.contributor.authorKim, Jong-Kook, author
dc.contributor.authorAli, Shoukat, author
dc.contributor.authorPrasanna Kumar, V. K., author
dc.contributor.authorGundala, Shriram Bhargava, author
dc.contributor.authorYu, Yang, author
dc.contributor.authorGertphol, Sethavidh, author
dc.contributor.authorIEEE, publisher
dc.date.accessioned2007-01-03T04:37:42Z
dc.date.available2007-01-03T04:37:42Z
dc.date.issued2002
dc.description.abstractDynamic real-time systems such as embedded systems operate in environments in which several parameters vary at run time. These systems must satisfy several performance requirements. Resource allocation on these systems becomes challenging because variations of run-time parameters may cause violations of the performance requirements. Performance violations result in the need for dynamic re-allocation, which is a costly operation. In this paper, a method for allocating resources such that the allocation can sustain the system in the light of a continuously changing environment is developed. We introduce a novel performance metric called MAIL (maximum allowable increase in load) to capture the effectiveness of a resource allocation. Given a resource allocation, MAIL quantifies the amount of additional load that can be sustained by the system without any performance violations. A Mixed-Integer-Programming-based approach (MIP) is developed to determine a resource allocation that has the highest MAIL value. Using simulations, several sets of experiments are conducted to evaluate our heuristics in various scenarios of machine and task heterogeneities. The performance of MIP is compared with three other heuristics: Integer-Programming based, Greedy, and classic Min-Min. Our results show that MIP performs signifantly better when compared with the other heuristics.
dc.description.sponsorshipThis research was supported by the DARPA/ITO Quorum Program through the Office of Naval Research under Grant No. N00014-00-1-0599.
dc.format.mediumborn digital
dc.format.mediumproceedings (reports)
dc.identifier.bibliographicCitationGertphol, Sethavidh, et al., A Metric and Mixed-Integer-Programming-Based Approach for Resource Allocation in Dynamic Real-Time Systems, Proceedings: International Parallel and Distributed Processing Symposium, April 15-19, 2002, Ft. Lauderdale, Florida: 10 p.
dc.identifier.urihttp://hdl.handle.net/10217/2449
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartofFaculty Publications
dc.rights©2002 IEEE.
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.subjectdistributed processing
dc.subjectinteger programming
dc.subjectreal-time systems
dc.subjectresource allocation
dc.subjectsoftware metrics
dc.subjectsoftware performance evaluation
dc.titleA metric and mixed-integer-programming-based approach for resource allocation in dynamic real-time systems
dc.typeText

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