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Decao Mao

dblp:148/5132 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 1992
—ORCID · none

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

Systems, architecture and hardware · 1Applied, interdisciplinary, general and emerging computing · 1

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.

Theoretical computer science
1 paper
Approximation and online algorithms · 100%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Embedded and real-time systems · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Approximation and online algorithms › online algorithms
competitive analysis
0.011991
On the competitiveness of on-line real-time task scheduling · RTSS 1991
Approximation and online algorithms › online algorithms
online scheduling
0.011991
On the competitiveness of on-line real-time task scheduling · RTSS 1991
Embedded and real-time systems › real-time scheduling
online real-time scheduling
0.011991
On the competitiveness of on-line real-time task scheduling · RTSS 1991
Embedded and real-time systems
real-time scheduling
0.011991
On the competitiveness of on-line real-time task scheduling · RTSS 1991

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

competitive analysis · 0.0
YearPublicationVenuePosition
1992 On the Competitiveness of On-Line Real-Time Task Scheduling
Sanjoy Baruah, Gilad Koren, Decao Mao, Bud Mishra, Arvind Raghunathan, Louis E. Rosier, Dennis E. Shasha, Fuxing Wang
Real Time Syst.3
1991 On the competitiveness of on-line real-time task scheduling
abstract
The authors study the performance of online algorithms in environments where no value is obtained for the partial execution of a request. They prove that no online scheduling algorithm can have a competitive factor greater than 0.25 times the optimal. They further refine this bound by considering the effect of the loading factor. Other models of task systems (for example, tasks systems consisting of many types of task requests), are considered. Similar upper bounds on the competitive factor that can be made by online scheduling algorithms in these environments are proved. It is shown that the performance bound of 0.25 is tight by means of a simple online uniprocessor scheduling algorithm has a competitive factor of 1/4. The authors extend the discussion to systems with dual processors. They show that the upper bound for the dual-processor online scheduling problem is 1/2 if all tasks have the same value density. This bound is tight if the tasks all also have zero laxity.>
Sanjoy Baruah, Gilad Koren, Decao Mao, Bud Mishra, Arvind Raghunathan, Louis E. Rosier, Dennis E. Shasha, Fuxing Wang
RTSS3