Abstract
Task scheduling is an essential aspect of parallel processing system. This problem assumes fully connected processors and ignores contention on the communication links. However, as arbitrary processor network (APN), communication contention has a strong influence on the execution time of a parallel application. In this paper, we propose genetic algorithms with fuzzy routing to face with link contention. In fuzzy routing algorithm, we consider speed of links and also busy time of intermediate links. To evaluate our method, we generate random DAGs with different Sparsity value based on Bernoulli distribution and compare our method with genetic algorithm and classic routing algorithm and also with BSA (bubble scheduling and allocation) method that is a well-known algorithm in this field. Experimental results show our method (GA with fuzzy routing) is able to find a scheduling with lower makespan than GA with classic routing and also BSA.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Tang, X.Y., Li, K.L., Padua, D.: Communication contention in APN list scheduling algorithm. Science in China Series F: Information Sciences 52, 59–69 (2009)
Kwok, Y., Ahmad, I.: Link Contention-Constrained Scheduling and Mapping of Tasks and Messages to a Network of Heterogeneous Processors. In: Cluster Computing, pp. 113–124 (2000)
Sinnen, O.: Task scheduling for parallel systems. JohnWiley & Sons-Interscience (2007)
Sinnen, O., Sousa, L.A., Sandnes, F.E.: Toward a realistic task scheduling model. IEEE Trans. Parallel and Distributed Systems 17, 263–275 (2006)
Cheng, S.-C., Shiau, D.-F., Huang, Y.-M., Lin, Y.-T.: Dynamic hard-real-time scheduling using genetic algorithm for multiprocessor task with resource and timing constraints. Expert Systems with Applications 36, 852–860 (2009)
Yoo, M.: Real-time task scheduling by multiobjective genetic algorithm. Systems & Software 82, 619–628 (2009)
Shin, K., Cha, M., Jang, M., Jung, J., Yoon, W., Choi, S.: Task scheduling algorithm using minimized duplications in homogeneous systems. Parallel and Distributed Computing 68, 1146–1156 (2008)
Yoo, M., Gen, M.: Scheduling algorithm for real-time tasks using multiobjective hybrid genetic algorithm in heterogeneous multiprocessors system. The Journal of Computers & Operations Research 34, 3084–3098 (2007)
Kwok, Y.K., Ahmad, I.: Benchmarking and comparison of the task graph scheduling algorithms. Parallel and Distributed Computing 59, 381–422 (1999)
Alkaya, A.F., Topcuoglu, H.R.: A task scheduling algorithm for arbitrarily-connected processors with awareness of link contention. Cluster Computing 9, 417–431 (2006)
Zomaya, A.Y., Teh, Y.-H.: Observations on Using Genetic Algorithms for Dynamic Load-Balancing. IEEE Trans. Parallel and Distributed Systems 12, 899–911 (2001)
Page, A.J., Naughton, T.J.: Dynamic task scheduling using genetic algorithms for heterogeneous distributed computing. In: Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2005 (2005)
Oliver, I.M., Smith, D.J., Holland, J.: A study of permutation crossover operators on the traveling salesman problem. In: Second International Conference on Genetic Algorithms on Genetic Algorithms and Their Application, pp. 224–230. Lawrence Erlbaum Associates, Inc. (1987)
Al-Sharaeh, S., Wells, B.E.: A Comparison of Heuristics for List Schedules using The Box-method and P-method for Random Digraph Generation. In: Proceedings of the 28th Southeastern Symposium on System Theory, pp. 467–471 (1996)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Sedaghat, N., Tabatabaee-Yazdi, H., Akbarzadeh-T, MR. (2011). Realistic Task Scheduling with Contention Awareness Genetic Algorithm by Fuzzy Routing in Arbitrary Heterogeneous Multiprocessor Systems. In: Wang, Y., Li, T. (eds) Knowledge Engineering and Management. Advances in Intelligent and Soft Computing, vol 123. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25661-5_18
Download citation
DOI: https://doi.org/10.1007/978-3-642-25661-5_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-25660-8
Online ISBN: 978-3-642-25661-5
eBook Packages: EngineeringEngineering (R0)