[1. Abraham, A., R. Buyya, B. Nath. Nature’s Heuristics for Scheduling Jobs on Computational Grids. - In: Proc. of IEEE International Conference on Advanced Computing and Communications, 2000, pp. 1-8.]Search in Google Scholar
[2. Ada, R., R. Kaur. - International Journal of Advanced Research in Computer Science and Software Engineering. - Ijarcsse, Vol. 3, 2013, No 3, pp. 665-668.]Search in Google Scholar
[3. Assunção, M. D., R. N. Calheiros, S. Bianchi, M. A. S. Netto, R. Buyya. Big Data Computing and Clouds: Trends and Future Directions. - Journal of Parallel and Distributed Computing, 2015, 79-80, pp. 3-15.10.1016/j.jpdc.2014.08.003]Search in Google Scholar
[4. Bardhan, S., D. Menasc. The Anatomy of Mapreduce Jobs, Scheduling, and Performance Challenges. - In: Proc. of Computer Measurement Group, 2013.]Search in Google Scholar
[5. Bardhan, S., D. Menascé. Queuing Network Models to Predict the Completion Time of the Map Phase of Map Reduce Jobs, 2012.]Search in Google Scholar
[6. Bu, Y., B. Howe, M. D. Ernst. Ha Loop : Efficient Iterative Data Processing on Large Clusters. - Proceedings of the VLDB Endowment, Vol. 3, 2010, No 1-2, pp. 285-296.10.14778/1920841.1920881]Search in Google Scholar
[7. Casavant, T. L., J. G. Kuhl. A Taxonomy of Scheduling in General-Purpose Distributed Computing Systems. - IEEE Transactions on Software Engineering, Vol. 14, 1988, No 2, pp. 141-154.10.1109/32.4634]Search in Google Scholar
[8. Coulouris, G., J. Dollimore, T. Kindberg. Distributed Systems: Concepts and Design. - Computer, Vol. 4, 2012.]Search in Google Scholar
[9. Dabhi, V. K., H. B. Prajapati. Soft Computing Based Intelligent Grid Architecture. - In: Proc. of International Conference on Computer and Communication Engineering (ICCCE’08), Global Links for Human Development, 13-15 May 2008, pp. 574-577.]Search in Google Scholar
[10. Davis, R. I., A. Burns. A Survey of Hard Real-Time Scheduling for Multiprocessor Systems. - ACM Computing Surveys, Vol. 43, 2011, No 4, pp. 1-44.10.1145/1978802.1978814]Search in Google Scholar
[11. Dittrich, J., J.-A. Quiané-Ruiz, A. Jindal, Y. Kargin, V. Sett y, J. Schad. Hadoop++: Makinga Yellow Elephant Run Likea Cheetah (Without it Even Noticing). - Proceedings of the VLDB Endowment, Vol. 3, 2010, No 1-2, pp. 515-529.10.14778/1920841.1920908]Search in Google Scholar
[12. Dong, F., S. G. Akl. Scheduling Algorithms for Grid Computing : State of the Art and Open Problems. - Components, Vol. 202, 2006, No 4, pp. 1-55.]Search in Google Scholar
[13. Doulkeridis, C., K. Nørvåg. A Survey of Large-Scale Analytical Query Processing in Map Reduce. - VLDB Journal, Vol. 23, 2014, No 3, pp. 355-380.10.1007/s00778-013-0319-9]Search in Google Scholar
[14. Ekanayake, J., H. Li, B. Zhang, T. Gunarathne, S. Bae, J. Qiu, G. Fox. Twister : A Runtime for Iterative Map Reduce. - In: Proc. of 19th ACM International Symposium on High Performance Distributed Computing, HPDC’10, 2010, pp. 810-818.]Search in Google Scholar
[15. Hadoop Fair Scheduler Design Document, 2010, pp. 1-11]Search in Google Scholar
[16. He, C., Y. Lu, D. Swanson. Matchmaking: A New Map Reduce Scheduling Technique. - In: Proc. of 3rd IEEE International Conference on Cloud Computing Technology and Science, Cloud Com’2011, 2011, pp. 40-47.]Search in Google Scholar
[17. Herodotou, H., S. Babu. Profiling, What-if Analysis, and Cost-Based Optimization of Map Reduce Programs. - PVLDB: Proceedings of the VLDB Endowment, Vol. 4, 2011, No 11, pp. 1111-1122.10.14778/3402707.3402746]Search in Google Scholar
[18. Herodotou, H., F. Dong, S. Babu. Mapreduce Programming and Costbased Optimization? Crossing this Chasm with Starfish. - Proceedings of the VLDB Endowment, Vol. 4, 2011, No 12, pp. 1446-1449.10.14778/3402755.3402792]Search in Google Scholar
[19. Jahani, E., M. J. Cafarella, C. Ré. Automatic Optimization for Map Reduce Programs. - Proceedings of the VLDB Endowment, Vol. 4, 2011, No 6, pp. 385-396.10.14778/1978665.1978670]Search in Google Scholar
[20. Gautam, J. V., H. B. Prajapati, V. K. Dabhi, S. Chaudhary. A Survey on Job Scheduling Algorithms in Big Data Processing. - In: Proc. of IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT’15), Coimbatore, 2015, pp. 1-11.10.1109/ICECCT.2015.7226035]Search in Google Scholar
[21. Kc, K., K. Anyanwu. Scheduling Hadoop Jobs to Meet Deadlines. - In: Proc. of 2nd IEEE International Conference on Cloud Computing Technology and Science (Cloud Com’10), 2010, pp. 388-392.10.1109/CloudCom.2010.97]Search in Google Scholar
[22. Kwon, Y., M. Balazinska, B. Howe, J. Rolia. Skew Tune: Mitigating Skew in Mapreduce Applications. - In: Proc. of 2012 ACM SIGMOD International Conference on Management of Data, 2012, pp. 25-36.]Search in Google Scholar
[23. Lee, K. H., Y. J. Lee, H. Choi, Y. D. Chung, B. Moon. Parallel Data Processing with Map Reduce: A Survey. - SIGMOD Record, Vol. 40, 2011, No 4, pp. 11-20.10.1145/2094114.2094118]Search in Google Scholar
[24. Liao, Xinyi, et al. An Enforcement of Real Time Scheduling in Spark Streaming. - In: Proc. of Green Computing Conference and Sustainable Computing Conference IEEE, 2015, pp. 1-6.]Search in Google Scholar
[25. Lim, H., H. Herodotou, S. Babu. Stubby: A Transformation-Based Optimizer for Map Reduce Workflows. - Proceedings of the VLDB Endowment, Vol. 5, 2012, No 11, pp. 1196-1207.10.14778/2350229.2350239]Search in Google Scholar
[26. Lin, Y., D. Agrawa l, C. Chen, B. C. Ooi, S. Wu. Llama: Leveraging Columnar Storage for Scalable Join Processing in the Map Reduce Framework. - In: Proc. of 2011 International Conference on Management of Data (SIGMOD’11), 2011, pp. 961-972.]Search in Google Scholar
[27. Prajapati, H. B., V. A. Shah. Scheduling in Grid Computing Environment. - In: Proc. of 4th International Conference on Advanced Computing & Communication Technologies, 2014, pp. 315-324.10.1109/ACCT.2014.32]Search in Google Scholar
[28. Rao, B. T., L. S. S. Reddy. Survey on Improved Scheduling in Hadoop Map Reduce in Cloud Environments. - International Journal of Computer Applications, Vol. 34, 2012, No 9, pp. 29-33.]Search in Google Scholar
[29. Rasooli, A., D. G. Down. A Hybrid Scheduling Approach for Scalable Heterogeneous Hadoop Systems. - In: Proc. of 2012 SC Companion: High Performance Computing, Networking Storage and Analysis (SCC’2012), 2012, pp. 1284-1291.]Search in Google Scholar
[30. Sakr, S., A. Liu, A. G. Fayoumi. The Family of Map Reduce and Large-Scale Data Processing Systems. - ACM Computing Surveys, Vol. 46, 2013, No 1, pp. 1-44.10.1145/2522968.2522979]Search in Google Scholar
[31. International Journal of Advanced Research, Vol. 3, 2013, No 5, pp. 875-878.]Search in Google Scholar
[32. Suthaharan, S. Big Data Classification: Problems and Challenges in Network Intrusion Prediction with Machine Learning. - Performance Evaluation Review, Vol. 41, 2014, No 4, pp. 70-73.10.1145/2627534.2627557]Search in Google Scholar
[33. Verma, A., L. Cherkasova, R. Campbell. ARIA: Automatic Resource Inference and Allocation for Map Reduce Environments. - In: Proc. of 8th ACM International Conference on Autonomic Computing, 2011, pp. 235-244.]Search in Google Scholar
[34. Wang, C. Journal of Computers, Vol. 8, 2013, No 3. ]Search in Google Scholar
[35. Wolf, J., A. Balmin, D. Rajan, K. Hildrum, R. Khandekar, S. Parekh, R. Vernica. CIRCUMFLEX: A Scheduling Optimizer for Map Reduce Workloads with Shared Scans. - ACM SIGOPS Operating Systems Review, Vol. 46, 2012, No 1.10.1145/2146382.2146388]Search in Google Scholar
[36. Yang, Zhiw Ei, et al. Adaptive Task Scheduling Strategy for Heterogeneous Spark Cluster. - Computer Engineering, 2016.]Search in Google Scholar
[37. Yong, M., N. Garegrat, S. Mohan. Towardsa Resource Aware Scheduler in hadoop. - In: Proc. of ICWS, 2009, pp. 1-10.]Search in Google Scholar
[38. Yoo, D., K. M. Sim. A Comparative Review of Job Scheduling for Map Reduce. - In: IEEE International Conference on Cloud Computing and Intelligence Systems, 2011, pp. 353-358.10.1109/CCIS.2011.6045089]Search in Google Scholar
[39. Zaharia, M., D. Borthakur, J. Sen Sarma, K. Elmeleegy, S. Shenker, I. Stoica. Delay Scheduling: A Simple Technique for Achieving Locality and Fairness in Cluster Scheduling. - In: Proc. of 5th European Conference on Computer Systems, 2010, pp. 265-278.]Search in Google Scholar
[40. Zaharia, M., A. Konwinski, A. Joseph, R. Katz, I. Stoica. Improving Map Reduce Performance in Heterogeneous Environments. - Osdi, 2008, pp. 29-42.]Search in Google Scholar
[41. Zhang, Y., Q. Gao, L. Gao, C. Wang. i Map Reduce: A Distributed Computing Framework for Iterative Computation. - Journal of Grid Computing, Vol. 10, 2012, No 1, pp. 47-68. 10.1007/s10723-012-9204-9]Search in Google Scholar