A Load Balancing Mechanism Using Bloom Filter in Storm System

When membership queries are evaluated in a set, the performance can be improved by a Bloom filter which is a space-efficient probabilistic data structure. According to its space-efficient character, Bloom Filter presented to address the load balancing problem for streaming media information in Storm system which is free and open source distributed real time computation system. This method increases the server cluster availability by balancing the workloads among the servers within a cluster. Additionally, it improves real time system Storm efficiently in saving the data transmission time and reducing the calculation complexity.

[1]  Sabu M. Thampi,et al.  Improving Hadoop Performance in Handling Small Files , 2011, ACC.

[2]  Hairong Kuang,et al.  The Hadoop Distributed File System , 2010, 2010 IEEE 26th Symposium on Mass Storage Systems and Technologies (MSST).

[3]  Sanjay Ghemawat,et al.  MapReduce: Simplified Data Processing on Large Clusters , 2004, OSDI.

[4]  Wei Liu,et al.  Design of an I/O balancing file system on Web server clusters , 2000, Proceedings 2000. International Workshop on Parallel Processing.

[5]  Yu-Chang Chao,et al.  Load Rebalancing for Distributed File Systems in Clouds , 2013, IEEE Transactions on Parallel and Distributed Systems.

[6]  Burton H. Bloom,et al.  Space/time trade-offs in hash coding with allowable errors , 1970, CACM.

[7]  Limin Xiao,et al.  A dynamic and adaptive load balancing strategy for parallel file system with large-scale I/O servers , 2012, J. Parallel Distributed Comput..