Performability analysis: measures, an algorithm, and a case study

The behavior of the multiprocessor system is described as a continuous Markov chain, and a reward rate (performance measure) is associated with each state. The distribution of performability is evaluated for analytical models of a multiprocessor system using a polynomial-time algorithm that obtains...

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Bibliographic Details
Published inIEEE transactions on computers Vol. 37; no. 4; pp. 406 - 417
Main Authors Smith, R.M., Trivedi, K.S., Ramesh, A.V.
Format Journal Article
LanguageEnglish
Published New York, NY IEEE 01.04.1988
Institute of Electrical and Electronics Engineers
Subjects
Algorithm design and analysis
Applied sciences
Availability
Computer aided software engineering
Computer science; control theory; systems
Computer systems performance. Reliability
Distributed computing
Exact sciences and technology
Fault tolerant systems
Multiprocessing systems
Performance analysis
Performance evaluation
Software
Steady-state
Switches
Availability
Case study
Multiprocessor
Fault tolerance
Performance analysis
Markov model
Computer system
Reliability
Algorithm
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Summary:The behavior of the multiprocessor system is described as a continuous Markov chain, and a reward rate (performance measure) is associated with each state. The distribution of performability is evaluated for analytical models of a multiprocessor system using a polynomial-time algorithm that obtains the distribution of performability for repairable, as well as nonrepairable, systems with heterogeneous components with a substantial speedup over earlier work. Numerical results indicate that distributions of cumulative performance measures over finite intervals reveal behavior of multiprocessor systems not indicates by either steady-state or expected values alone.< >
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0018-9340
1557-9956
DOI:10.1109/12.2184