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Articles by Yi Zhu
Total Records ( 4 ) for Yi Zhu
  Cheng Ma , Ye San and Yi Zhu
  The truncated particle filter was proposed based on the analysis of residual particle filter and regularized particle filter. The main idea of the truncated particle filter was to draw the new particles from the resampling area of the particles with large weights, rather than point-wise determine the repetition number of each particle. The effective resampling areas were established by these particles whose weights were larger than the truncated value. The uniform kernel was used to draw new particles from these areas. This method combined the information contained in the prior transformation function and the likelihood function, meanwhile increased the particle diversity. The simulation results showed that the truncated particle filter reduces the computational complexity, meanwhile maintains the same estimation accuracy as the common resampling algorithms. Furthermore, this new algorithm greatly shortened the estimated time and improves the stability of the estimates.
  Zhenbo Shi , Yi Zhu , Ya`nan Ni , Jia Shi and Shu Yan
  As an important issue in wireless sensor networks, localization is widely used to acquire node’s location in many aspects such as some routing mechanisms, target tracking, load balancing, topology control and so on. Traditional localization schemes need to pre-deploy a certain amount of static beacons in the network and the percentage of static beacons will directly affect the final localization result. In contrast, localization by use of mobile beacons is inherently more accurate and cost-effective. This study proposes a new ranging-free localization scheme with dual mobile beacons for wireless sensor networks. By deploying two fixed spacing mobile beacons moving in line with constant speed but different communication reach range, the localization can be realized through a single interaction with the unknown node. Since there is only few messages exchanged between unknown node and mobile beacons, this scheme is easy to control the node energy consumption. Furthermore, free from the channel noise interference is another key feature of this scheme due to the ranging-free technology. The simulation results have shown that the proposed scheme has good localization accuracy when mobile beacons themselves are localized with small error and beacon message transmit interval is reasonable.
  Yuanjun He , Yi Zhu , Ya`nan Ni , Jia Shi and Na Zhu
  Ubiquitous in-network caching is one of the key aspects of Content-centric Networking (CCN) which has recently received widespread research interest. At present, researchers usually use Leave Copy Everywhere (LCE) strategy as the cache decision strategy by default. Experimental investigation shows that LCE apparently is not a good choice because it does not effectively distinguish the importance of nodes on content delivery path. By learning from the advantages of some existing basic cache decision strategies, a new cache decision strategy which called Content Gradually Tend to Important Node (CGTIN), is proposed in this study. CGTIN is a cache decision strategy who tries its best to push more popular contents to more important nodes and extend the survival time of these more popular contents. In order to test the performance of CGTIN, programs of 4-level binary tree topology are developed by MATLAB. Simulation results show that while compared to LCE, both the SSHP and AHD of CGTIN has an apparent decline while compared to MCD, the SSHP of CGTIN has an apparent degradation and the AHD of CGTIN is exact same when not considering the class of CCN content.
  Yi Zhu , Xingming Sun , Zhihua Xia , Li Chen , Tao Li and Daxing Zhang
  With the growing popularity of cloud computing, more and more users are willing to outsource their private data to the cloud. To ensure the security of data, data owners usually encrypted their private data before outsourcing them to the cloud server. Though data encryption improves the security of data, it increases the difficulty of data operating. This study focuses on the search of encrypted images in the cloud and proposes an efficient similarity retrieval scheme over encrypted images. The proposed scheme enables data owners to outsource their personal images and the content-based image retrieval service to the cloud without revealing the actual content of the image database to the cloud. The proposed scheme in this study supports the global feature based image retrieval methods under the Euclidean distance metric. Besides, rigorous security analysis and extensive experiments show that the proposed scheme is secure and efficient.
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