Robust Adaptive Metrics for Deadline Assignment in Distributed Hard Real-Time Systems
dc.contributor.author | Jonsson, Jan | en_US |
dc.contributor.author | Shin, Kang G. | en_US |
dc.date.accessioned | 2006-09-11T19:44:31Z | |
dc.date.available | 2006-09-11T19:44:31Z | |
dc.date.issued | 2002-11 | en_US |
dc.identifier.citation | Jonsson, Jan; Shin, Kang G.; (2002). "Robust Adaptive Metrics for Deadline Assignment in Distributed Hard Real-Time Systems." Real-Time Systems 23(3): 239-271. <http://hdl.handle.net/2027.42/48078> | en_US |
dc.identifier.issn | 0922-6443 | en_US |
dc.identifier.issn | 1573-1383 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/48078 | |
dc.description.abstract | Distributed real-time applications usually consist of several component tasks and must be completed by its end-to-end (E-T-E) deadline. As long as the E-T-E deadline of an application is met, the strategy used for dividing it up for component tasks does not affect the application itself. One would therefore like to “slice” each application E-T-E deadline and assign the slices to component tasks so as to maximize the schedulability of the component tasks, and hence the application. Distribution of the E-T-E deadline over component tasks is a difficult and important problem since there exists a circular dependency between deadline distribution and task assignment. We propose a new deadline-distribution scheme which has two major improvements over the best scheme known to date. It can distribute task deadlines prior to task assignment and relies on new adaptive metrics that yield significantly better performance in the presence of high resource contention. The deadline-distribution problem is formulated for distributed hard real-time systems with relaxed locality constraints, where schedulability analysis must be performed at pre-run-time, and only a subset of the tasks are constrained by pre-assignment to specific processors. Although it is applicable to any scheduling policy, the proposed deadline-distribution scheme is evaluated for a non-preemptive, time-driven scheduling policy. Using extensive simulations, we show that the proposed adaptive metrics deliver much better performance (in terms of success ratio and maximum task lateness) than their non-adaptive counterparts. In particular, the simulation results indicate that, for small systems, the adaptive metrics can improve the success ratio by as much as an order of magnitude. Moreover, the new adaptive metrics are found to exhibit very robust performance over a large variety of application and architecture scenarios. | en_US |
dc.format.extent | 1016277 bytes | |
dc.format.extent | 3115 bytes | |
dc.format.mimetype | application/pdf | |
dc.format.mimetype | text/plain | |
dc.language.iso | en_US | |
dc.publisher | Kluwer Academic Publishers; Springer Science+Business Media | en_US |
dc.subject.other | Computer Science | en_US |
dc.subject.other | Processor Architectures | en_US |
dc.subject.other | Special Purpose and Application-Based Systems | en_US |
dc.subject.other | Operating Systems | en_US |
dc.subject.other | Computing Methodologies | en_US |
dc.subject.other | Distribution of an End-to-End Deadline | en_US |
dc.subject.other | Precedence Constraints | en_US |
dc.subject.other | Relaxed Locality | en_US |
dc.subject.other | Hard-real-Time Systems | en_US |
dc.subject.other | Non-preemptive Scheduling | en_US |
dc.subject.other | Multiprocessor Systems | en_US |
dc.title | Robust Adaptive Metrics for Deadline Assignment in Distributed Hard Real-Time Systems | en_US |
dc.type | Article | en_US |
dc.subject.hlbsecondlevel | Computer Science | en_US |
dc.subject.hlbsecondlevel | Business (General) | en_US |
dc.subject.hlbsecondlevel | Management | en_US |
dc.subject.hlbsecondlevel | Economics | en_US |
dc.subject.hlbtoplevel | Business | en_US |
dc.subject.hlbtoplevel | Engineering | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Real-Time Computing Laboratory, Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, 48109-2122, USA | en_US |
dc.contributor.affiliationother | Department of Computer Engineering, Chalmers University of Technology, SE-412 96, Göteborg, Sweden | en_US |
dc.contributor.affiliationumcampus | Ann Arbor | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/48078/1/11241_2004_Article_5096705.pdf | en_US |
dc.identifier.doi | http://dx.doi.org/10.1023/A:1020279929417 | en_US |
dc.identifier.source | Real-Time Systems | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
Files in this item
Remediation of Harmful Language
The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.
Accessibility
If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.