A brief review of scheduling algorithms of Map Reduce model using Hadoop

Scheduling has been an active area of research in computing systems since their inception. Hadoop framework has become very much popular and most widely used in distributed data processing. Hadoop has become a central platform to store big data through its Hadoop Distributed File System (HDFS) as well as to run analytics on this stored big data using its MapReduce component. The main objective is to study MapReduce framework, MapReduce model, scheduling in hadoop, various scheduling algorithms and various optimization techniques in job scheduling. Scheduling algorithms of MapReduce model using hadoop vary with design and behaviour, and are used for handling many issues like data locality, awareness with resource, energy and time.

[1]  Xiangming Dai,et al.  Scheduling for response time in Hadoop MapReduce , 2016, 2016 IEEE International Conference on Communications (ICC).

[2]  Michael Lang,et al.  Overcoming Hadoop Scaling Limitations through Distributed Task Execution , 2015, 2015 IEEE International Conference on Cluster Computing.

[3]  Limin Xiao,et al.  A Load-Driven Task Scheduler with Adaptive DSC for MapReduce , 2011, 2011 IEEE/ACM International Conference on Green Computing and Communications.

[4]  Yaser Jararweh,et al.  Multi-threading based Map Reduce tasks scheduling , 2014, 2014 5th International Conference on Information and Communication Systems (ICICS).

[5]  Wentong Cai,et al.  Hadoop Job Scheduling with Dynamic Task Splitting , 2015, 2015 International Conference on Cloud Computing Research and Innovation (ICCCRI).

[6]  Yuan Zhou,et al.  Preemptive Hadoop Jobs Scheduling under a Deadline , 2012, 2012 Eighth International Conference on Semantics, Knowledge and Grids.

[7]  Kemafor Anyanwu,et al.  Scheduling Hadoop Jobs to Meet Deadlines , 2010, 2010 IEEE Second International Conference on Cloud Computing Technology and Science.

[8]  M. Divya,et al.  Workload characteristics and resource aware Hadoop scheduler , 2015, 2015 IEEE 2nd International Conference on Recent Trends in Information Systems (ReTIS).