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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Indonesian Journal of Electrical Engineering and Computer Science
Cao Jie
Lanzhou University of Technology
Computer Science & IT

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An Optimized Model for MapReduce Based on Hadoop Zhang Hong; Wang Xiao-ming; Cao Jie; Ma Yan-hong; Guo Yi-rong; Wang Min
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 4: December 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i4.3606

Abstract

Aiming at the waste of computing resources resulting from sequential control of running mechanism of MapReduce model on Hadoop platform，Fork/Join framework has been introduced into this model to make full use of CPU resource of each node. From the perspective of fine-grained parallel data processing, combined with Fork/Join framework，a parallel and multi-thread model，this paper optimizes MapReduce model and puts forward a MapReduce+Fork/Join programming model which is a distributed and parallel architecture combined with coarse-grained and fine-grained on Hadoop platform to Support two-tier levels of parallelism architecture both in shared and distributed memory machines. A test is made under the environment of Hadoop cluster composed of four nodes. And the experimental results prove that this model really can improve performance and efficiency of the whole system and it is not only suitable for handling tasks with data intensive but also tasks with computing intensive. it is an effective optimization and improvement to the MapReduce model of big data processing.
A New Fusion Tracking Method with Unknown Noise Sun Tao; Qin Lu-Fang; Li Wei; Li Jun; Cao Jie
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 10: October 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i10.pp7262-7273

Abstract

In order to sovle the problem of video target tracking problem, this paper proposed a new kind of particle filter with unknown statistical characteristics of noises. This paper derivates the distribution function of statistical properties in detailed with correlative noise by the establishment model of related noise, and gives the real-time estimation equation of the noise statistical characteristics and the system state. The new algorithm reduced the estimation error effectively and improved the anti-noise ability of the system. Under the improving particle filter framework, we used color and motion edge character as observation model and fused multi features weights through the D-S evidence theory. The experimental results showed that the method proposed in this paper has high precision and strong robustness to target tracking under the complicated conditions.
Study on Cooperation between Traffic Control and Route Guidance Based on Real-time Speed Cao Jie; Wang Chuan
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 10: October 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i10.pp7242-7248

Abstract

Aiming at minimizing the total travel time of the road network, a cooperation model of traffic control and route guidance is built based on real-time speed obtained from cooperative vehicle infrastructure system. Genetic algorithm is used to solve the cooperation model to get the optimal green ratio and guidance rate of flow through transforming genetic algorithm with constraints into unconstrained genetic algorithm by penalty function. The simulation results of an experimental simulation on a small network show that this method can effectively balance the network flow, reduce total travel time and improve the efficiency of road network.
A New Particle Filter Algorithm with Correlative Noises Qin Lu-Fang; Li Wei; Sun Tao; Li Jun; Cao Jie
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 8: August 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i8.pp6164-6172

Abstract

The standard particle filter (SPF) requirements system noise and measurement noise must be independent. In order to overcome this limit, a new kind of correlative noise particle filter (CN-PF) algorithm is proposed. In this new algorithm, system state model with correlative noise is established, and the noise related proposal distribution function characteristics were analyzed in detail. At last, the concrete form of the best proposal distribution function is derived based on the condition of the minimum variance of importance weight with the assumption of gaussian noise. Theoretical analysis and experimental results show the effectiveness of the proposed new algorithm.
Co-Authors Guo Yi-rong Li Jun Li Wei Ma Yan-hong Qin Lu-Fang Sun Tao Wang Chuan Wang Min Wang Xiao-ming Zhang Hong