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Resource availability-aware advance reservation for parallel jobs with deadlines

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Abstract

Advance reservation is important to guarantee the quality of services of jobs by allowing exclusive access to resources over a defined time interval on resources. It is a challenge for the scheduler to organize available resources efficiently and to allocate them for parallel advance reservation jobs with deadline constraint appropriately. This paper provides a slot-based data structure to organize available resources of multiprocessor systems in a way that enables efficient search and update operations and formulates a suite of scheduling policies to allocate resources for dynamically arriving advance reservation requests. The performance of the scheduling algorithms were investigated by simulations with different job sizes and durations, system loads, and scheduling flexibilities. Simulation results show that job sizes and durations, system load and the flexibility of scheduling will impact the performance metrics of all the scheduling algorithms, and the \(\textit{PE}\; \textit{Worst Fit}\) algorithm becomes the best algorithm for the scheduler with the highest acceptance rate of advance reservation requests, and the jobs with the \(\textit{First Fit}\) algorithm experience the lowest average slowdown. The data structure and scheduling policies can be used to organize and allocate resources for parallel advance reservation jobs with deadline constraint in large-scale computing systems.

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Acknowledgments

This research is supported in part by the Natural Science Foundation of China under Grant Number 60663009, the Training Programme Foundation for Young Key Teachers of Yunnan University, and the Research Foundation of Yunnan University under Grant Number 2009F30Q. Also we would like to thank the reviewers for their valuable suggestions and comments on this paper.

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Authors and Affiliations

  1. School of Information Science and Engineering, Yunnan University, Kunming,  650091, China

    Bo Li, Yijian Pei & Hao Wu

  2. School of Electrical and Information Engineering, Wuhan Institute of Technology, Wuhan,  430073, China

    Bin Shen

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  1. Bo Li
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  2. Yijian Pei
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  3. Hao Wu
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  4. Bin Shen
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Correspondence to Bo Li.

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Li, B., Pei, Y., Wu, H. et al. Resource availability-aware advance reservation for parallel jobs with deadlines. J Supercomput 68, 798–819 (2014). https://doi.org/10.1007/s11227-013-1067-8

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