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Wenhui Li
Jilin University

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A Novel Watermarking Algorithm based on SURF and SVD Wei Wang; Wenhui Li; Chengxi Wang; Huijie Xin
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 3: March 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

Protection against geometric distortions and common image processing operations becomes a much challenging task in image watermarking. To achieve this, a novel watermarking algorithm based on Speeded Up Robust Features (SURF) and Singular Value Decomposition (SVD) was presented for digital image copyright protection. By introducing the SURF’s key points matching and geometric distortion estimation, the attacked watermarked image could be corrected and the watermark synchronization was realized. In this way, the feature regions of the host image, which were used for information hiding, could be correctly detected by the improved Harris-Laplace corner detector even after signal processing and geometric attacks. Finally, the watermark information were embedded into the U matrix of SVD of the host image. The application of the proposed scheme makes the watermark capable of transparent hiding. Extensive experimental results demonstrate that our technique performs better than traditional methods under different attacks. DOI: http://dx.doi.org/10.11591/telkomnika.v11i3.2305
Agent-based Dynamic Adaptive Cluster Load Balancing Model Tianshu You; Wenhui Li; Zhiyi Fang; Chunfei Zhang; Guannan Qu
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 3: March 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

In a cluster environment, the identification and the classification of the requested task is a prerequisite for choosing the appropriate load balancing algorithm and improving the processing capacity of the network. As the existing load balancing strategies cannot relate tasks and load balancing algorithm intelligently, this paper present an Agent-based dynamic adaptive load balancing model. Through the identification and classification of the requested task, the model selects corresponding load balancing algorithm to reach the load balancing in cluster. This model has a distinct advantage over other load balancing schedule strategies on response time. DOI : http://dx.doi.org/10.11591/telkomnika.v12i3.4568
Performance Evaluation of Dynamic Load Balancing Algorithms Tianshu You; Wenhui Li; Zhiyi Fang; Hongbin Wang; Guannan Qu
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 4: April 2014
Publisher : Institute of Advanced Engineering and Science

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Efficient task scheduling mechanism can better meet the users’ QoS requirement, and achieve the load balancing in physical hosts, so the cluster system with high scalability and reliability can effectively improve the information utilization of the system, thereby enhance the overall performance of the Web server cluster system. In order to build a network service system with better scalability and reliability, this paper describes the round-robin scheduling algorithm of LVS cluster system, least-connection scheduling algorithm, weighted least-connection scheduling algorithm and a prior proposed new weighted value assigned scheduling algorithm, dynamic adaptive feedback load balancing strategy. Meanwhile, it takes simulation experiment for the round-robin scheduling algorithm of LVS, least-connection scheduling algorithm, weighted least-connection scheduling algorithm and the new weighted value assigned scheduling algorithm, dynamic adaptive feedback load balancing strategy and take comparative analysis for the experimental data, through the analysis and assessment, effectively point out the advantages and disadvantages of the existing load balancing strategy. It is conducive to better improve the existing equalization algorithm performance deficiencies and propose optimum load balancing strategy DOI : http://dx.doi.org/10.11591/telkomnika.v12i4.4731
Co-Authors Chengxi Wang Chunfei Zhang Guannan Qu Hongbin Wang Huijie Xin Tianshu You Wei Wang Zhiyi Fang