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Journal of Applied Sciences

Year: 2013 | Volume: 13 | Issue: 9 | Page No.: 1551-1557
DOI: 10.3923/jas.2013.1551.1557
Networked Intelligent Sensor System Load Balance Based on Pp-gmcp Algorithm
Yuebin Zhou, Guixiong Liu and Haibing Zhu

Abstract: In order to solve the networked intelligent sensor system load balance problem and improve service response speed, a load balance realization method based on Probabilistic Preferred Grey Markov Chain Prediction (PP-GMCP) algorithm is proposed. This method real-time monitors Network Capable Application Processor (NCAP) load status, combines residual correction and grey Markov chain prediction, effectively predicts NCAP load capacity. A load balance simulation platform based on OPNET is constructed to validate algorithm performance. The test shows that the PP-GMCP algorithm effectively improves the service request processing speed, compared to weighted round robin and least connection scheduling its average service response delay reduces 11.1 and 25.1%, respectively, the NCAP load fluctuation range is the smallest and obtains better load balance effect.

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How to cite this article
Yuebin Zhou, Guixiong Liu and Haibing Zhu, 2013. Networked Intelligent Sensor System Load Balance Based on Pp-gmcp Algorithm. Journal of Applied Sciences, 13: 1551-1557.

Keywords: OPNET simulation, grey prediction, load balance and Intelligent sensor

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