NDLI: P-Scheduler: adaptive hierarchical scheduling in apache storm

Content Provider	ACM Digital Library
Author	Eyers, David Eskandari, Leila Huang, Zhiyi
Abstract	With ever-accelerating data creation rates in Big Data applications, there is a need for efficient stream processing engines. Apache Storm has been of interest in both academia and industry because of its real-time, distributed, scalable and reliable framework for stream processing. In this paper, we propose an adaptive hierarchical scheduler for the Storm framework, to allocate the resources more efficiently and improve performance. In our method, we consider the data transfer rate and traffic pattern between Storm's tasks and assign highly-communicating task pairs to the same computing node by dynamically employing two phases of graph partitioning. We also calculate the number of required computing nodes in the cluster based on the overall load of the application and use this information to reduce inter-node traffic. Our performance evaluation shows a significant improvement compared to the default scheduler provided by Storm, which evenly distributes the tasks across the cluster, ignoring the communication patterns between them.
Starting Page	1
Ending Page	10
Page Count	10
File Format	PDF
ISBN	9781450340427
DOI	10.1145/2843043.2843056
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-02-01
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Graph partitioning Stream processing Big data Scheduling Apache storm
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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P-Scheduler: adaptive hierarchical scheduling in apache storm