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A topology-based scaling mechanism for Apache Storm
- Source :
- International Journal of Network Management. 27:e1933
- Publication Year :
- 2016
- Publisher :
- Wiley, 2016.
-
Abstract
- Summary As more and more well-known companies, such as Twitter, Yahoo, and Alibaba, start to focus on real-time big data applications, how to build a platform for processing real-time data becomes an important issue. Among all the real-time processing systems, Apache Storm is the most well-known and representative open-source, distributed, real-time computation system. In Storm, the computation is implemented by a topology such as a graph where nodes are operators and edges represent the data flows between operators. In big data processing and analysis systems, scalability is an important issue. Storm provides rebalance mechanism for its scalability property, which can adjust the parallelism of a running topology. However, there are some drawbacks in rebalance command, such as resource usage restriction and topology execution suspension. In this paper, we propose a topology-based scaling mechanism for Apache Storm. When a topology is overloaded, it scales by adjusting the number of the cloned topologies or replaced by another new topology with more tasks. When scaling by topology-based mechanism, it eliminates resource usage restriction and execution suspension in the topology, and the procedure is automatically launched. The experimental results show that our topology-based scaling mechanism can improve the scaling performance of Storm. Copyright © 2016 John Wiley & Sons, Ltd.
- Subjects :
- Computer Networks and Communications
Computer science
business.industry
Computation
Big data
Logical topology
020206 networking & telecommunications
Topology (electrical circuits)
02 engineering and technology
Network topology
Topology
Computer Science Applications
Resource (project management)
020204 information systems
Scalability
0202 electrical engineering, electronic engineering, information engineering
Graph (abstract data type)
business
Subjects
Details
- ISSN :
- 10557148
- Volume :
- 27
- Database :
- OpenAIRE
- Journal :
- International Journal of Network Management
- Accession number :
- edsair.doi...........5cf51f4ff541760bec149f81d7b6e279