Dynamically mapping tasks with priorities and multiple deadlines in a heterogeneous environment

  • Authors:

  • Jong-Kook Kim;Sameer Shivle;Howard Jay Siegel;Anthony A. Maciejewski;Tracy D. Braun;Myron Schneider;Sonja Tideman;Ramakrishna Chitta;Raheleh B. Dilmaghani;Rohit Joshi;Aditya Kaul;Ashish Sharma;Siddhartha Sripada;Praveen Vangari;Siva Sankar Yellampalli

  • Affiliations:

  • Samsung SDS, IT R & D Center, 159-9 Gumi-Dong Bundang-Gu Seongnam-Si, Gyeonggi-Do, South Korea;Electrical and Computer Engineering Department, Colorado State University, Fort Collins, CO 80523-1373, USA;Electrical and Computer Engineering Department, Colorado State University, Fort Collins, CO 80523-1373, USA and Computer Science Department, Colorado State University, Fort Collins, CO 80523-1373, ...;Electrical and Computer Engineering Department, Colorado State University, Fort Collins, CO 80523-1373, USA;Electrical and Computer Engineering Department, Colorado State University, Fort Collins, CO 80523-1373, USA;Electrical and Computer Engineering Department, Colorado State University, Fort Collins, CO 80523-1373, USA and Agilent Technologies, Loveland, CO 80537, USA;Computer Science Department, Colorado State University, Fort Collins, CO 80523-1373, USA;Computer Science Department, Colorado State University, Fort Collins, CO 80523-1373, USA;Electrical and Computer Engineering Department, Colorado State University, Fort Collins, CO 80523-1373, USA;Electrical and Computer Engineering Department, Colorado State University, Fort Collins, CO 80523-1373, USA;Electrical and Computer Engineering Department, Colorado State University, Fort Collins, CO 80523-1373, USA;Electrical and Computer Engineering Department, Colorado State University, Fort Collins, CO 80523-1373, USA;Electrical and Computer Engineering Department, Colorado State University, Fort Collins, CO 80523-1373, USA;Electrical and Computer Engineering Department, Colorado State University, Fort Collins, CO 80523-1373, USA;Electrical and Computer Engineering School, Louisiana State University, Baton Rouge, LA 70802, USA

  • Venue:
  • Journal of Parallel and Distributed Computing
  • Year:
  • 2007

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Abstract

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.