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B. Krishnamoorthi

dblp:98/726 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1966
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Performance modeling and evaluation · 33% Distributed systems · 33% Embedded and real-time systems · 33%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Performance modeling and evaluation
queueing models
0.011966
Time-Shared Computer Operations With Both Interarrival and Service Times Exponential · J. ACM 1966
Embedded and real-time systems › real-time scheduling › schedulability analysis
response time analysis
0.011966
Time-Shared Computer Operations With Both Interarrival and Service Times Exponential · J. ACM 1966
Distributed systems
time-sharing systems
0.011966
Time-Shared Computer Operations With Both Interarrival and Service Times Exponential · J. ACM 1966

Methods — techniques the papers use, named apart from their topics

generating functions · 0.0embedded markov chain · 0.0
YearPublicationVenuePosition
1966 Time-Shared Computer Operations With Both Interarrival and Service Times Exponential
abstract
The concept of time-shared computer operations is briefly described and a model of a time-sharing system is proposed, based on the assumption that both interarrival and service times possess an exponential distribution. Although the process described by this model is non-Markovian, an imbedded Markov chain is analyzed by exploiting the fact that the instants of completion of a “quantum” of service are regeneration points. It is shown that user congestion possesses a limiting distribution, and the method of generating functions is used to derive this distribution. The concept of cycle time is discussed and two measures of cycle time developed for a scheduling discipline employing a single queue. Finally, a number of numerical examples are presented to illustrate the effect of the system parameters upon user congestion, system response time and computer efficiency.
B. Krishnamoorthi, Roger C. Wood
J. ACM1