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James P. Huang

dblp:95/2722 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1985
—ORCID · none

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

Software engineering, systems software and programming languages · 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
Embedded and real-time systems · 46% Parallel and multicore computing · 46% Electronic design automation · 7%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Embedded and real-time systems › distributed real-time systems
distributed real-time applications
0.011985
Modeling of Software Partition for Distributed Real-Time Applications · IEEE Trans. Software Eng. 1985
Embedded and real-time systems
real-time scheduling
0.011985
Modeling of Software Partition for Distributed Real-Time Applications · IEEE Trans. Software Eng. 1985
Parallel and multicore computing
software partitioning
0.011985
Modeling of Software Partition for Distributed Real-Time Applications · IEEE Trans. Software Eng. 1985
Parallel and multicore computing
task allocation
0.011985
Modeling of Software Partition for Distributed Real-Time Applications · IEEE Trans. Software Eng. 1985
Electronic design automation › high-level synthesis
scheduling
0.011985
Modeling of Software Partition for Distributed Real-Time Applications · IEEE Trans. Software Eng. 1985

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

simulation · 0.0optimization modeling · 0.0
YearPublicationVenuePosition
1985 Modeling of Software Partition for Distributed Real-Time Applications
abstract
The issue of software partition deals with the process of mapping the given set of logical modules, which reflect the user's point of view, into a set of software tasks, which reflect the software implementor's point of view. It is shown in this paper that the software partitioning problem can be modeled as one that maximizes the efficiency in resource utilization while observing the constraints on CPU throughput, memory space available, maximally allowed task execution time, and the order of module execution. The CPU and memory constraints are implementation dependent. The maximum task execution time constraint is due to considerations on the response time performance. The constraint on module execution order is a logical one, and it is shown to have significant performance impact. It is proven that by employing the module precedence relation, which reflects the sequence of module execution, the order of module execution can be properly maintained during the software partitioning process. And thus the defined tasks can be guaranteed to be completely executable, once properly activated With completely executable tasks, the operating overhead cost and the response time delay can be minimized. The following four module precedence relations are explored: precede, succeed, parallel, and precede as well as succeed. The validity of the selected partitioning criterion of maximizing the resource utilization efficiency is also assessed through simulation experiments. The results of simulation show that performance of the selected criterion is insensitive to the application environment, as well as to the application requirements.
James P. Huang
IEEE Trans. Software Eng.1