Analysing and evaluating topology structure of online application in Big Data stream computing environment Online publication date: Mon, 08-Aug-2016
by Rui Huang; Dawei Sun
International Journal of Wireless and Mobile Computing (IJWMC), Vol. 10, No. 4, 2016
Abstract: Stream computing systems process high-rate incoming data sources in dynamic environments and generate real-time results. A critical problem in stream processing is the difficulty in devising an optimal strategy for configuring topology structure. That is due to the inability to predict or adapt to the dynamics of the data flow intensity and the computing platform's workload. Therefore, the best strategy should rely on the real-time statistics of performance and workload to achieve self-adaptation. In this paper, we first analyse the impact of application topology structures in Storm on performance and resource utilisation efficiency. From the metrics of stream processing application and environment, we derive some effective optimisation rules towards designing an online reconfiguration strategy. Our evaluation of the experimental results reveals the intricacies in searching the configuration parameters space and shows that a strategy based on our rules can substantially improve performance as well as achieve high resource utilisation efficiency.
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