Imprecise task schedule optimization

Chantana Chantrapornchai; Sissades Tongsima; Edwin H.M. Sha

Imprecise task schedule optimization

Chantana Chantrapornchai^*
, Sissades Tongsima
, Edwin H.M. Sha

^*Corresponding author for this work

University of Notre Dame

Research output: Contribution to conference › Paper › peer-review

8 Scopus citations

Abstract

Considerable research has been done in order to schedule tasks to a multiple processing systems. Some of the computation time of these tasks may, however, be imprecise due to the nature of the problem. In this paper, an imprecise task graph is used to model the problem where each node represents a task associated with its computation time. An algorithm, called rotation scheduling, is extended to handle the imprecise task scheduling and fuzzy arithmetic is used to estimate the size of a schedule. The goal of the algorithm is to give the optimized schedule as much as possible. The experiments showing the effectiveness of this approach are also presented.

Original language	English
Pages	1265-1270
Number of pages	6
State	Published - 1997
Externally published	Yes
Event	Proceedings of the 1997 6th IEEE International Conference on Fussy Systems, FUZZ-IEEE'97. Part 1 (of 3) - Barcelona, Spain Duration: 1 Jul 1997 → 5 Jul 1997

Conference

Conference	Proceedings of the 1997 6th IEEE International Conference on Fussy Systems, FUZZ-IEEE'97. Part 1 (of 3)
City	Barcelona, Spain
Period	1/07/97 → 5/07/97

Cite this

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title = "Imprecise task schedule optimization",

abstract = "Considerable research has been done in order to schedule tasks to a multiple processing systems. Some of the computation time of these tasks may, however, be imprecise due to the nature of the problem. In this paper, an imprecise task graph is used to model the problem where each node represents a task associated with its computation time. An algorithm, called rotation scheduling, is extended to handle the imprecise task scheduling and fuzzy arithmetic is used to estimate the size of a schedule. The goal of the algorithm is to give the optimized schedule as much as possible. The experiments showing the effectiveness of this approach are also presented.",

author = "Chantana Chantrapornchai and Sissades Tongsima and Sha, \{Edwin H.M.\}",

year = "1997",

language = "英语",

pages = "1265--1270",

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T1 - Imprecise task schedule optimization

AU - Chantrapornchai, Chantana

AU - Tongsima, Sissades

AU - Sha, Edwin H.M.

PY - 1997

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N2 - Considerable research has been done in order to schedule tasks to a multiple processing systems. Some of the computation time of these tasks may, however, be imprecise due to the nature of the problem. In this paper, an imprecise task graph is used to model the problem where each node represents a task associated with its computation time. An algorithm, called rotation scheduling, is extended to handle the imprecise task scheduling and fuzzy arithmetic is used to estimate the size of a schedule. The goal of the algorithm is to give the optimized schedule as much as possible. The experiments showing the effectiveness of this approach are also presented.

AB - Considerable research has been done in order to schedule tasks to a multiple processing systems. Some of the computation time of these tasks may, however, be imprecise due to the nature of the problem. In this paper, an imprecise task graph is used to model the problem where each node represents a task associated with its computation time. An algorithm, called rotation scheduling, is extended to handle the imprecise task scheduling and fuzzy arithmetic is used to estimate the size of a schedule. The goal of the algorithm is to give the optimized schedule as much as possible. The experiments showing the effectiveness of this approach are also presented.

UR - https://www.scopus.com/pages/publications/0030661032

M3 - 论文

AN - SCOPUS:0030661032

SP - 1265

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T2 - Proceedings of the 1997 6th IEEE International Conference on Fussy Systems, FUZZ-IEEE'97. Part 1 (of 3)

Y2 - 1 July 1997 through 5 July 1997

ER -

Imprecise task schedule optimization

Abstract

Conference

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