TY - JOUR
T1 - Dynamically mapping tasks with priorities and multiple deadlines in a heterogeneous environment
AU - Kim, Jong Kook
AU - Shivle, Sameer
AU - Siegel, Howard Jay
AU - Maciejewski, Anthony A.
AU - Braun, Tracy D.
AU - Schneider, Myron
AU - Tideman, Sonja
AU - Chitta, Ramakrishna
AU - Dilmaghani, Raheleh B.
AU - Joshi, Rohit
AU - Kaul, Aditya
AU - Sharma, Ashish
AU - Sripada, Siddhartha
AU - Vangari, Praveen
AU - Yellampalli, Siva Sankar
N1 - Funding Information:
This research was supported by the Colorado State University George T. Abell Endowment. ∗Corresponding author. E-mail addresses: jongkook@ieee.org (J.-K. Kim), sameer.shivle@gmail.com (S. Shivle), hj@colostate.edu (H.J. Siegel), aam@colostate.edu (A.A. Maciejewski), tdbraun@yahoo.com (T.D. Braun), myron_schneider@agilent.com (M. Schneider), stidema@sandia.gov (S. Tideman), ramacmr@cs.colostate.edu(R. Chitta), rdilmaghani@ucsd.edu (R.B.Dilmaghani), aditya21@lycos.com(A.Kaul), ashish@engr.colostate.edu (A. Sharma), siddhu@engr.colostate.edu (S. Sripada), praveen@engr.colostate.edu (P. Vangari), syella1@lsu.edu (S.S. Yellampalli).
Copyright:
Copyright 2008 Elsevier B.V., All rights reserved.
PY - 2007/2
Y1 - 2007/2
N2 - In a distributed heterogeneous computing system, the resources have different capabilities and tasks have different requirements. To maximize the performance of the system, it is essential to assign the resources to tasks (match) and order the execution of tasks on each resource (schedule) to exploit the heterogeneity of the resources and tasks. Dynamic mapping (defined as matching and scheduling) is performed when the arrival of tasks is not known a priori. In the heterogeneous environment considered in this study, tasks arrive randomly, tasks are independent (i.e., no inter-task communication), and tasks have priorities and multiple soft deadlines. The value of a task is calculated based on the priority of the task and the completion time of the task with respect to its deadlines. The goal of a dynamic mapping heuristic in this research is to maximize the value accrued of completed tasks in a given interval of time. This research proposes, evaluates, and compares eight dynamic mapping heuristics. Two static mapping schemes (all arrival information of tasks are known) are designed also for comparison. The performance of the best heuristics is 84% of a calculated upper bound for the scenarios considered.
AB - In a distributed heterogeneous computing system, the resources have different capabilities and tasks have different requirements. To maximize the performance of the system, it is essential to assign the resources to tasks (match) and order the execution of tasks on each resource (schedule) to exploit the heterogeneity of the resources and tasks. Dynamic mapping (defined as matching and scheduling) is performed when the arrival of tasks is not known a priori. In the heterogeneous environment considered in this study, tasks arrive randomly, tasks are independent (i.e., no inter-task communication), and tasks have priorities and multiple soft deadlines. The value of a task is calculated based on the priority of the task and the completion time of the task with respect to its deadlines. The goal of a dynamic mapping heuristic in this research is to maximize the value accrued of completed tasks in a given interval of time. This research proposes, evaluates, and compares eight dynamic mapping heuristics. Two static mapping schemes (all arrival information of tasks are known) are designed also for comparison. The performance of the best heuristics is 84% of a calculated upper bound for the scenarios considered.
KW - Deadlines
KW - Distributed computing
KW - Dynamic mapping
KW - Heterogeneous computing
KW - Priority
KW - Resource allocation
KW - Resource management
KW - Scheduling
KW - Static mapping
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U2 - 10.1016/j.jpdc.2006.06.005
DO - 10.1016/j.jpdc.2006.06.005
M3 - Article
AN - SCOPUS:33845749587
VL - 67
SP - 154
EP - 169
JO - Journal of Parallel and Distributed Computing
JF - Journal of Parallel and Distributed Computing
SN - 0743-7315
IS - 2
ER -