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Extended Equal Service and Differentiated Service Models for Peer-to-Peer File Sharing
Zhang, Jianwei,Wang, Yongchao,Xing, Wei,Lu, Dongming The Korea Institute of Information and Commucation 2013 Journal of communications and networks Vol.15 No.2
Peer-to-peer (P2P) systems have proved the most effective and popular file sharing applications in recent years. Previous studies mainly focused on equal service and differentiated service strategies when peers have no initial data before their downloads. For an upload-constrained P2P file sharing system, we model both the equal service process and the differentiated service process when the initial data distribution of peers satisfies some special conditions. Moreover, we show how to minimize the time required to distribute the file to any number of peers. The proposed fluid-based models can reveal the intrinsic relations among the initial data amount, the peer set size, and the minimum last finish time. The closed-form expressions derived from the extended models can closely approximate chunk-based models and systems, especially for relatively large files. As an application of the extended models, we show how to provide differentiated service efficiently to multiple peer sets. Since no limits are imposed on the upload bandwidth of peers or the size of each peer set, we believe that our analytic process and the results achieved can provide not only fundamental insights into bandwidth allocation and data scheduling but also a helpful reference for both improving system performance and building an effective incentive mechanism for P2P file sharing systems.
Extended Equal Service and Differentiated Service Models for Peer-to-Peer File Sharing
Jianwei Zhang,Yongchao Wang,Wei Xing,Dongming Lu 한국통신학회 2013 Journal of communications and networks Vol.15 No.2
Peer-to-peer (P2P) systems have proved the most effective and popular file sharing applications in recent years. Previous studies mainly focused on equal service and differentiated service strategies when peers have no initial data before their downloads. For an upload-constrained P2P file sharing system, wemodel both the equal service process and the differentiated service process when the initial data distribution of peers satisfies some special conditions. Moreover, we show how to minimize the time required to distribute the file to any number of peers. The proposed fluid-based models can reveal the intrinsic relations among the initial data amount, the peer set size, and the minimum last finish time. The closed-form expressions derived from the extended models can closely approximate chunk-based models and systems, especially for relatively large files. As an application of the extended models, we show how to provide differentiated service efficiently to multiple peer sets. Since no limits are imposed on the upload bandwidth of peers or the size of each peer set, we believe that our analytic process and the results achieved can provide not only fundamental insights into bandwidth allocation and data scheduling but also a helpful reference for both improving systemperformance and building an effective incentive mechanism for P2P file sharing systems.
Multi-level Cross-attention Siamese Network For Visual Object Tracking
Jianwei Zhang,Jingchao Wang,Huanlong Zhang,Mengen Miao,Zengyu Cai,Fuguo Chen 한국인터넷정보학회 2022 KSII Transactions on Internet and Information Syst Vol.16 No.12
Currently, cross-attention is widely used in Siamese trackers to replace traditional correlation operations for feature fusion between template and search region. The former can establish a similar relationship between the target and the search region better than the latter for robust visual object tracking. But existing trackers using cross-attention only focus on rich semantic information of high-level features, while ignoring the appearance information contained in low-level features, which makes trackers vulnerable to interference from similar objects. In this paper, we propose a Multi-level Cross-attention Siamese network(MCSiam) to aggregate the semantic information and appearance information at the same time. Specifically, a multi-level cross-attention module is designed to fuse the multi-layer features extracted from the backbone, which integrate different levels of the template and search region features, so that the rich appearance information and semantic information can be used to carry out the tracking task simultaneously. In addition, before cross-attention, a target-aware module is introduced to enhance the target feature and alleviate interference, which makes the multi-level cross-attention module more efficient to fuse the information of the target and the search region. We test the MCSiam on four tracking benchmarks and the result show that the proposed tracker achieves comparable performance to the state-of-the-art trackers.
A New Operator Extracting Image Patch Based on EPLL
Jianwei Zhang,Tao Jiang,Yuhui Zheng,Jin Wang,Jiacen Xie 한국정보처리학회 2018 Journal of information processing systems Vol.14 No.3
Multivariate finite mixture model is becoming more and more popular in image processing. Performingimage denoising from image patches to the whole image has been widely studied and applied. However, thereremains a problem that the structure information is always ignored when transforming the patch into thevector form. In this paper, we study the operator which extracts patches from image and then transformsthem to the vector form. Then, we find that some pixels which should be continuous in the image patches arediscontinuous in the vector. Due to the poor anti-noise and the loss of structure information, we propose anew operator which may keep more information when extracting image patches. We compare the newoperator with the old one by performing image denoising in Expected Patch Log Likelihood (EPLL) method,and we obtain better results in both visual effect and the value of PSNR.
A New Operator Extracting Image Patch Based on EPLL
Zhang, Jianwei,Jiang, Tao,Zheng, Yuhui,Wang, Jin,Xie, Jiacen Korea Information Processing Society 2018 Journal of information processing systems Vol.14 No.3
Multivariate finite mixture model is becoming more and more popular in image processing. Performing image denoising from image patches to the whole image has been widely studied and applied. However, there remains a problem that the structure information is always ignored when transforming the patch into the vector form. In this paper, we study the operator which extracts patches from image and then transforms them to the vector form. Then, we find that some pixels which should be continuous in the image patches are discontinuous in the vector. Due to the poor anti-noise and the loss of structure information, we propose a new operator which may keep more information when extracting image patches. We compare the new operator with the old one by performing image denoising in Expected Patch Log Likelihood (EPLL) method, and we obtain better results in both visual effect and the value of PSNR.
Extended kernel correlation filter for abrupt motion tracking
( Huanlong Zhang ),( Jianwei Zhang ),( Qinge Wu ),( Xiaoliang Qian ),( Tong Zhou ),( Hengcheng Fu ) 한국인터넷정보학회 2017 KSII Transactions on Internet and Information Syst Vol.11 No.9
The Kernelized Correlation Filters (KCF) tracker has caused the extensive concern in recent years because of the high efficiency. Numerous improvements have been made successively. However, due to the abrupt motion between the consecutive image frames, these methods cannot track object well. To cope with the problem, we propose an extended KCF tracker based on swarm intelligence method. Unlike existing KCF-based trackers, we firstly introduce a swarm-based sampling method to KCF tracker and design a unified framework to track smooth or abrupt motion simultaneously. Secondly, we propose a global motion estimation method, where the exploration factor is constructed to search the whole state space so as to adapt abrupt motion. Finally, we give an adaptive threshold in light of confidence map, which ensures the accuracy of the motion estimation strategy. Extensive experimental results in both quantitative and qualitative measures demonstrate the effectiveness of our proposed method in tracking abrupt motion.