Effective Strategy Identification for Parallel Job Execution Job Partitioning, Requirement Gathering and Allocation Strategies
DOI:
https://doi.org/10.26438/ijcse/v7i1.192197Keywords:
Parallel and distributed computing, execution speed, starvationAbstract
Parallel and distributed computing becomes critical in the heavy workload environment. In such situations, job partitioning becomes need of the hour. Smaller junks known as task has limited complexity and hence overall execution speed increased considerably as these allotted to the processors. In case of parallel computing, there exist several distinct tasks that may belong to single or multiple jobs having resource requirements. Assigning resources to tasks need strategies to reduce execution time and prevent starvation. This literature put a light on strategies used to allocate resources optimally to tasks meant to execute on distributed environment. Highlights of distinct literature presented through parameters in the form of comparative table so that useful feature can be extracted for future enhancements.
References
[1] A. Vasudevan, “Static Task Partitioning Techniques for Parallel Applications on Heterogeneous Processors,” Trinity Coll. dublin, no. December, 2015.
[2] N. Saranya and R. C. Hansdah, “Dynamic partitioning based scheduling of real-time tasks in multicore processors,” Proc. - 2015 IEEE 18th Int. Symp. Real-Time Distrib. Comput. ISORC 2015, pp. 190–197, 2015.
[3] M. Y. Alzahrani, “Discovering Sequential Patterns from Medical Datasets,” 2016.
[4] S. Alamanda, S. Pabboju, and N. Gugulothu, “An Approach to Mine Time Interval Based Weighted Sequential Patterns in Sequence Databases,” 2017 13th Int. Conf. Signal-Image Technol. Internet-Based Syst., pp. 29–34, 2017.
[5] F. Ahmed, “A Simple Acute Myocardial Infarction ( Heart Attack ) Prediction System Using Clinical Data and Data Mining Techniques,” pp. 22–24, 2017.
[6] S. Abbasghorbani and R. Tavoli, “Survey on Sequential Pattern Mining Algorithms,” 2015 2nd Int. Conf. Knowledge-Based Eng. Innov., pp. 1153–1164, 2015.
[7] N. Béchet, P. Cellier, T. Charnois, B. Cremilleux, and M. C. Jaulent, “Sequential pattern mining to discover relations between genes and rare diseases,” Proc. - IEEE Symp. Comput. Med. Syst., 2012.
[8] C. J. Chen, T. W. Pai, S. S. Lin, C. C. Yeh, M. H. Liu, and C. H. Wang, “Application of PrefixSpan Algorithms for Disease Pattern Analysis,” Proc. - 2016 Int. Comput. Symp. ICS 2016, pp. 274–278, 2017.
[9] Y. CHENG, Y.-F. Lin, K.-H. Chiang, and V. Tseng, “Mining Sequential Risk Patterns from Large-Scale Clinical Databases for Early Assessment of Chronic Diseases: A Case Study on Chronic Obstructive Pulmonary Disease,” IEEE J. Biomed. Heal. Informatics, pp. 1–1, 2017.
[10] B. R. M. Eenan, “Non-homogeneous Markov models for sequential pattern mining of healthcare data,” IEEE, pp. 327–344, 2009.
[11] J. Wei, Y. Yin, and F. Liu, “Multi-model LPV approach to CSTR system identification with stochastic scheduling variable,” Proc. - 2015 Chinese Autom. Congr. CAC 2015, pp. 303–307, 2016.
[12] Y. Sun and P. Jiang, “A Novel Bottleneck Identification Based Differential Evolution Algorithm for Scheduling Complex Manufacturing Lines,” Proc. - 2016 3rd Int. Conf. Inf. Sci. Control Eng. ICISCE 2016, pp. 774–778, 2016.
[13] J. Dai, B. Hu, L. Zhu, H. Han, and J. Liu, “Research on dynamic resource allocation with cooperation strategy in cloud computing,” 2012 3rd Int. Conf. Syst. Sci. Eng. Des. Manuf. Informatiz. ICSEM 2012, vol. 1, pp. 193–196, 2012.
[14] A. Mohtasham, R. Filipe, and J. Barreto, “FRAME: Fair resource allocation in multi-process environments,” Proc. Int. Conf. Parallel Distrib. Syst. - ICPADS, vol. 2016-January, pp. 601–608, 2016.
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