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Power Efficient Scheduling Scheme based on PSO for Real Time Systems
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 111 - Number 4 |
| Year of Publication: 2015 |
| Authors: Medhat H A Awadalla |
10.5120/19526-1157
|
Medhat H A Awadalla . Power Efficient Scheduling Scheme based on PSO for Real Time Systems. International Journal of Computer Applications. 111, 4 ( February 2015), 24-30. DOI=10.5120/19526-1157
Abstract
Power efficient design of real-time embedded systems based on multi-processors becomes more important as system functionality is increasingly realized through heuristic approaches. This paper targets energy-efficient scheduling of tasks over multiple processors, where tasks share a common deadline. It addresses the problem of energy-aware static partitioning of periodic real time tasks on heterogeneous multiprocessor platforms. A modified Particle Swarm Optimization variant based on priority assignment and min-min algorithms for task partitioning is proposed. The proposed approach aims to minimize the overall energy consumption, meanwhile avoid deadline violations. An energy-aware cost function is proposed to be considered in the proposed approach. Extensive simulated experiments and comparisons with related approaches are conducted in order to validate the effectiveness of the proposed technique. The achieved results demonstrate that the proposed partitioning scheme significantly outperforms in terms of the number of executed iterations to accomplish a specific task in addition to the energy savings.
References
- Dawei, L. and Wu, J. , (2012). Task Partitioning Upon Energy-Aware Scheduling for Frame-Based Tasks on Heterogeneous Multiprocessor Platforms. 41st Int. Conf. on Parallel Processing, pp. 430 – 439.
- Kong, F. Yi, W. and Deng, Q. (2012). Energy-Efficient Scheduling of Real-Time Tasks on Cluster-Based Multicores. In DATE'11, pp. 1-6.
- Chen, J. -J. and Thiele, L. (2009). Task partitioning and platform synthesis for energy efficiency. In the 15th IEEE Int. Conf. on Embedded and Real-Time Computing Systems and Applications, pp. 393-402.
- Texas Instruments (TI), OMAP™ Mobile Processors. Available at: http://www. ti. com/general/docs/gencontent. tsp?content Id=46946 [last accessed 15/2/2012].
- Abdelhalim, M. B. (2008). Task assignment for Heterogeneous Multiprocessors using Re-Excited Particle Swarm Optimization. In 2008 Int. Conf. on Computer and Electrical Engineering, pp. 23-27.
- Aydin, H. and Yang, Q. (2003). Energy-Aware Partitioning for Multiprocessor Real-Time Systems. In IPDPS, pp. 1- 9.
- Cong J. and Yuan B. , Energy-efficient scheduling on heterogeneous multi-core architectures. In ISLPED '12 Proceedings of the 2012 ACM/IEEE international symposium on Low power electronics and design, 2012, pp. 345-350.
- Chitlur N. , (2012) QuickIA: Exploring heterogeneous architectures on real prototypes. HPCA '12, pp. 1–8.
- Baruah, S. (2004). Partitioning real-time tasks among heterogeneous multiprocessors. ICPP, Montreal, Quebec, Canada, pp. 467-474.
- Braun, T. D. , Siegel, H. J. , Beck, N. , Boloni, L. L. Maheswaran, M. Reuther, A. I. , Robertson, J. P. , Theys, M. D. , Yao, B. , Hensgen, D. and Freund, R. F. (2001). A Comparison of Eleven Static Heuristics for Mapping a Class of Independent Tasks onto Heterogeneous Distributed Computing Systems. Journal of Parallel and Distributed Computing, vol. 61, 2001, pp. 810-837.
- Chen, H. and Cheng, A. M. K. (2005). Applying Ant Colony Optimization to the partitioned scheduling problem for heterogeneous multiprocessors. ACM SIGBED Review, Vol. 2 , No. 2, 2005, pp. 11-14.
- Visalakshi, P. and Sivanandam, S. N. (2009). Dynamic Task Scheduling with Load Balancing using Hybrid Particle Swarm Optimization. Int. J. Open Problems Compt. Math, Vol. 2, No. 3, pp. 475 – 48.
- Abdullah E. , Shalan M. , Awadalla M. , Saad E. M. (2014). Energy-efficient task allocation techniques for asymmetric multiprocessor embedded systems. ACM Transactions on Embedded Computing Systems (Impact Factor: 1. 18).
- Saad, E. M. , Awadalla, M. A. , Shalan, M. , and Elewi, A. 2012. Energy-Aware Task Partitioning on Heterogeneous Multiprocessor Platforms. IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 2, No 1, ISSN (Online): 1694-0814, Pp. 176-183.
- Omidi, A. and Rahmani, A. M. (2009). Multiprocessor Independent Tasks Scheduling Using A Novel Heuristic PSO Algorithm. pp. 369 – 373.
- Chen, J. and Kuo, C. (2007). Energy-efficient scheduling for real time systems on dynamic voltage scaling (DVS) platforms. 13th IEEE Int. Conf. , RTCSA, pp. 28-38.
- Koufaty, D. Reddy, D. and Hahn, S. (2010). Bias Scheduling in Heterogeneous Multicore Architectures. In Proceedings of the 5th ACM European Conference on Computer Systems (EuroSys), pp. 125 - 138.
- Higashino, W. Capretz, M. A. M. and Toledo, M. B. F. (2014). Evaluation of Particle Swarm Optimization Applied to Grid Scheduling. Proc. Of 23rd IEEE WETICE Conf. , Parma, Italy, pp. 1-6.
- Chou Q. , Ge D, and Zhang R. , (2014). PSO Based Optimization of Testing and Maintenance Cost in NPPs. Hindawi Publishing Corporation Science and Technology of Nuclear Installations, Volume 2014, pp. 1-9.
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