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Tommy W. Tam

dblp:81/5581 · DBLP profile ↗
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6ranked-venue papers
0as first author
0since 2021 · last 1998
—ORCID · none

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

Systems, architecture and hardware · 3Applied, interdisciplinary, general and emerging computing · 2Theory of computation · 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.

Computer architecture, parallel and distributed computing, and storage systems
2 papers
Embedded and real-time systems · 100%
Computer networks
1 paper
Routing and switching · 87% Transport protocols and congestion control · 13%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Embedded and real-time systems
real-time scheduling
0.021990
On-Line Routing of Real-Time Messages · RTSS 1990
Minimizing Mean Flow Time with Error Constraint · RTSS 1989
Routing and switching › routing algorithms
online routing
0.011990
On-Line Routing of Real-Time Messages · RTSS 1990
Routing and switching
routing algorithms
0.011990
On-Line Routing of Real-Time Messages · RTSS 1990
Embedded and real-time systems › real-time scheduling
imprecise computation
0.011989
Minimizing Mean Flow Time with Error Constraint · RTSS 1989
Embedded and real-time systems › real-time scheduling
multiprocessor scheduling
0.011989
Minimizing Mean Flow Time with Error Constraint · RTSS 1989
Transport protocols and congestion control › real-time communication
real-time traffic
0.011990
On-Line Routing of Real-Time Messages · RTSS 1990

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

competitive analysis · 0.0pseudo-polynomial time algorithm · 0.0NP-hardness analysis · 0.0
YearPublicationVenuePosition
1998 Minimizing Mean Flow Time with Error Constraint
Joseph Y.-T. Leung, Tommy W. Tam, C. S. Wong, Gilbert H. Young
Algorithmica2
1996 On-Line Routing of Real-Time Messages
Joseph Y.-T. Leung, Tommy W. Tam, Gilbert H. Young
J. Parallel Distributed Comput.2
1995 Routing Messages with Release Time and Deadline Constraint
Joseph Y.-T. Leung, Tommy W. Tam, C. S. Wong, Gilbert H. Young
J. Parallel Distributed Comput.2
1990 On-Line Routing of Real-Time Messages
abstract
Whether it is possible to have an optimal online algorithm for unidirectional ring, out-tree, in-tree, bidirectional tree, and bidirectional ring networks is discussed. The problem is considered under various restrictions of four parameters-origin node, destination node, release time and deadline. For unidirectional ring, it is shown that no such algorithm can exist unless one of the four parameters is fixed. For out-tree, it is shown that no such algorithm can exist unless one of three parameters-origin node, destination node and release time-is fixed. For in-tree, it is shown that no such algorithm can exist unless one of three parameters-origin node, destination node and deadline-is fixed. For bidirectional tree, it is shown that no such algorithm can exist unless the origin node or the destination node is fixed. For bidirectional ring, it is shown that no such algorithm can exist unless the origin node and either the destination node or the release time are fixed.>
Joseph Y.-T. Leung, Tommy W. Tam, Gilbert H. Young
RTSS2
1990 Packing Squares into a Square
Joseph Y.-T. Leung, Tommy W. Tam, C. S. Wong, Gilbert H. Young, Francis Y. L. Chin
J. Parallel Distributed Comput.2
1989 Minimizing Mean Flow Time with Error Constraint
abstract
In a new model of task systems studied by J.W.S. Liu et al. (1987) each task is logically decomposed into two subtasks, mandatory and optional. The authors discuss preemptively scheduling this kind of task system on p>or=1 identical processors so as to minimize the mean flow time. Given a task system and an error threshold K, the goal is to find a preemptive schedule such that each task is executed in the interval of its release time and deadline, the average error is no more than K, and the mean flow time of the schedule is minimized. Such a schedule is called an optimal schedule. It is shown that the problem of finding an optimal schedule is NP-hard for each p>or=1, even if all tasks have the same ready time and deadline. For a single processor, a pseudo-polynomial time algorithm and polynomial time algorithms for various special cases of the problem are given.>
Joseph Y.-T. Leung, Tommy W. Tam, C. S. Wong, Gilbert H. Wong
RTSS2