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Design of security functionality in P2P applications

Design of security functionality in P2P applications

引用

8th Korea-Russia international symposium on science and Technology, KORUS 2004

作者： Park, Zin-Won Lee, Joon-Hyung Kim, Myung-Kyun Dept. of Computer Engineering and Information Technology University of Ulsan San-29 Moogu-2 Dong Namgu Ulsan 680-749 Korea Republic of

ISBN: (纸本)0780383834

Peer-to-Peer (P2P) applications are used to communicate among peers or groups. P2P computing draws growing interest as a new distributed computing paradigm for its potential to use user's computing resources efficiently. It assumes that the user communicates with reliable peer because P2P applications are usually used to transmit private messages or files and share private data. But most existing P2P applications does not provide confidentiality, and may hurt peer's system whether it is intentional or unintentional. In this paper, we have addressed the security problems in P2P applications. We also have designed a security functionality in P2P applications for the secure and reliable group communications. ©2004 IEEE.

关键词： Security of data

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Development of a novel finder pattern for effective color 2D-barcode detection

Development of a novel finder pattern for effective color 2D...

引用

IEEE international symposium on Parallel and distributed Processing with applications

作者： Kato, Hiroko Tan, Keng T. Chai, Douglas Edith Cowan University School of Computer and Information Science Mount Lawley WA 6050 2 Bradford Street Australia School of Computer and Information Science Mount Lawley WA 6050 2 Bradford Street Australia School of Engineering Joondalup WA 6027 270 Joondalup Drive Australia

ISBN: (纸本)9780769534718

With a camera mobile phone, which has become a, "must-have" device, 2D-barcode works as an interface to bridge the physical and digital world. As the notion of ubiquitous computing has permeated, developing a new 2D-barcode and its applications has been a growing trend worldwide. A 2D-barcode symbol consists of two broad areas: data area and guide area. The components of the latter is collectively called "finder pattern" and used in locating the 2D-barcode symbol. The failure of finding the target symbol prevents a barcode reader from successfully decoding the barcode. Hence, designing a functional finder pattern is Me of the key for improving the robustness of barcode reading, and thus, the entire 2D-barcode system. We have designed a novel finder pattern integrated with a color 2D-barcode for camera mobile phone applications. Through the development and evaluation of the finder pattern for effective color 2D-barcode detection, this paper discusses keys to improve the functionality and reliability of finder patterns, which should be kept in mind when designing a finder pattern for any 2D-barcode symbol.

关键词： selectors Bar code scanners Bar Codes Ubiquitous computing Coding systems Color Mind

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Auto-tuning Streamed applications on Intel Xeon Phi 32

Auto-tuning Streamed Applications on Intel Xeon Phi

引用

27th international Heterogeneity in computing Workshop in conjunction with 32nd IEEE international Parallel and distributed Processing symposium (IPDPS)

作者： Zhang, Peng Fang, Jianbin Tang, Tao Yang, Canqun Wang, Zheng Natl Univ Def Technol Coll Comp Compiler Lab Changsha Hunan Peoples R China Univ Lancaster Sch Comp & Commun MetaLab Lancaster England

ISBN: (纸本)9781538643686

Many-core accelerators, as represented by the XeonPhi coprocessors and GPGPUs, allow software to exploit spatial and temporal sharing of computing resources to improve the overall system performance. To unlock this performance potential requires software to effectively partition the hardware resource to maximize the overlap between host-device communication and accelerator computation, and to match the granularity of task parallelism to the resource partition. However, determining the right resource partition and task parallelism on a per program, per dataset basis is challenging. This is because the number of possible solutions is huge, and the benefit of choosing the right solution may be large, but mistakes can seriously hurt the performance. In this paper, we present an automatic approach to determine the hardware resource partition and the task granularity for any given streamed application, targeting the Intel XeonPhi architecture. Instead of hand-crafting the heuristic for which the process will have to repeat for each hardware generation, we employ machine learning techniques to automatically learn it. We achieve this by first learning a predictive model offline using training programs;we then use the learned model to predict the resource partition and task granularity for any unseen programs at runtime. We apply our approach to 23 representative parallel applications and evaluate it on a CPU-XeonPhi mixed heterogenous many-core platform. Our approach achieves, on average, a 1.6x (upto 5.6x) speedup, which translates to 94.5% of the performance delivered by a theoretically perfect predictor.

关键词： Heterogeneous computing Parallelism Performance Tuning Machine learning

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Design and implementation of an efficient multi-cluster GridRPC system

Design and implementation of an efficient multi-cluster Grid...

引用

2005 IEEE international symposium on Cluster computing and the Grid, CCGrid 2005

作者： Ho, Quoc-Thuan Cai, Wentong Ong, Yew-Soon Institute of High Performance Computing Agency for Science Technology and Research Singapore Science Park II 1 Science Park Road Singapore 117528 Singapore Parallel and Distributed Computing Centre School of Computer Engineering Nanyang Technological University Singapore 639798 Singapore

ISBN: (纸本)0780390741

Multi-cluster Grids have emerged as the most popular type of Grid environments. On multi-cluster Grid, resources are distributed across different networks. Hence, scheduling and dispatching jobs are difficult and inefficient due to the restrictions of network and the communication over-head. This paper presents the design and implementation of an efficient GridRPC system for the multi-cluster Grid. Metascheduling mechanism is developed to distribute jobs onto different clusters of computers effectively. Further, a dynamic bundling mechanism is provided to reduce overhead of job dispatching. This mechanism bundles similar requests to form a composite request that is dispatched to a Grid resource. The above mechanisms have been tested with different types of services and loads, and the results show that they help to achieve more balanced workload and reduce the overhead of job dispatching. This cuts down execution time of applications. © 2005 IEEE.

关键词： distributed computer systems

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Multi-party k-means clustering with privacy consideration

Multi-party k-means clustering with privacy consideration

引用

IEEE international symposium on Parallel and distributed Processing With applications

作者： Yu, Teng-Kai Lee, D.T. Chang, Shih-Ming Zhan, Justin Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan National Center for the Protection of the Financial Infrastructure Dakota State University Madison SD United States Institute of Information Science Academia Sinica Nankang Taipei Taiwan Taiwan Information Security Center Research Center for Information Technology Innovation Academia Sinica Nankang Taipei Taiwan

ISBN: (纸本)9780769541907

The k-means clustering algorithm is a widely used scheme to solve the clustering problem which classifies a given set of n data points in m-dimensional space into k clusters, whose centers are obtained by the centroids of the points in the same cluster. The problem with privacy consideration has been studied, when the data is distributed among different parties and the privacy of the distributed data is to be preserved. In this paper, we apply the concept of parallel computing to solve the privacy-preserving multi-party k-means clustering problem, when the data is vertically partitioned and horizontally partitioned respectively among different parties. We present algorithms for solving the problems for these two data partition models that run in O(nk) time and in O(m(k + log(n/k))) time respectively. The time complexities of the algorithms are much better than others without parallel computing. © 2010 IEEE.

关键词： Problem solving

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An efficient dynamic neural network for predicting time series data stream 18

An efficient dynamic neural network for predicting time seri...

引用

18th IEEE Int Symp on Parallel and distributed Proc with Applicat (ISPA) / 10th IEEE Int Conf on Big Data and Cloud Comp (BDCloud) / IEEE Int Symp on Social Comp and Networking (SocialCom) / IEEE Int Conf on Sustainable Comp and Commun (SustainCom)

作者： Chen, Liang Wang, Wei Yang, Yun East China Normal Univ Sch Data Sci & Enginerring Shanghai Peoples R China USST Business Sch Shanghai Peoples R China

ISBN: (纸本)9781665414852

The prediction of the time-series data stream in AIOps is an important research field of data mining. However, due to the non-stationary and non-linear characteristics of time series data, many existing methods cannot comprehensively solve the accuracy and reduce time consumption. To solve this problem, we propose a new MWNN (Memory Wavelet Neural Network) algorithm. It can effectively overcome the contradiction between accuracy and time consumption. In MWNN, we designed a new hidden layer structure. By adding a new memory storage unit to the hidden layer, it can be ensured that the hidden layer can make the best use of historical data and greatly improve the prediction accuracy. Moreover, the model does not require any prior information or data distribution assumptions. This paper selects real Ops data for verification. The final experimental results show that, compared with the commonly used prediction models, this model has the highest prediction accuracy and lower time consumption. The data set used in the experiment has been uploaded to https://***/Yang-Yun726/MWNN/tree/master/DATA.

关键词： data stream Prediction dynamic neural network memory neuron AIOps

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Tuning evolutionary algorithm performance using nature inspired heuristics

Tuning evolutionary algorithm performance using nature inspi...

引用

8th international symposium on Symbolic and Numeric Algorithms for Scientific computing

作者： Abraham, Ajith Yonsei Univ Sch Comp Sci IITA Professorship Program Seoul 120749 South Korea

ISBN: (纸本)9780769527406

Summary form only given. Evolutionary algorithms have become an important problem solving methodology among many researchers working in the area of computational intelligence. The population based collective learning process; self adaptation and robustness are some of the key features of evolutionary algorithm when compared to other global optimization techniques. Due to its simplicity, evolutionary algorithms have been widely accepted for solving several important practical applications in engineering, business, commerce etc. However, experimental evidence had indicated cases where evolutionary algorithms are inefficient at fine tuning solutions, but better at finding global basins of attraction. The efficiency of evolutionary training can be improved significantly by hybridization of some search procedures or incorporating some heuristics into the evolution process. In this talk, we will review how particle swarm optimization algorithm and bacterial foraging algorithm could be used to optimize the performance of evolutionary algorithms. The performance of the hybridized algorithms will be illustrated using some benchmark problems

关键词： Evolutionary computation Computer science Problem-solving Computational intelligence Robustness business Particle swarm optimization Microorganisms Scientific computing

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Enhancing data replication with greedy pipeline-based aggressive copy protocol in data grids

引用

5th international symposium on Parallel and distributed Processing and applications/ISPA 2007 international Workshops

作者： Wang, Reen-Cheng Wu, Su-Ling Chang, Ruay-Shiung Department of Computer Science and Information Engineering National Dong Hwa University

ISBN: (纸本)9783540747413

To gain high performance computing or store large amount of data using inexpensive devices, grid system is one of the well-known solutions. In most cases, the grid can be categorized into two types: computational grid and data grid. Data grid is used for data intensive applications. In data grids, replication is used to reduce access latency and bandwidth consumption. Furthermore, it can also improve data availability, load balancing and fault tolerance. If there are many replicas, they may have coherence problems while being updated. In this paper, based on the aggressive-copy method, we propose a novel Greedy Pipeline-based Aggressive Copy (GPAC) protocol. The performance of pipelining dataset blocks and greedy sequencing in the GPAC can accelerate data replication speed in compared with previous works. Both analytical and experimental results show promising performance enhancements.

关键词： Pipelines

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Data Driven e-science: Use Cases and Successful applications of distributed computing Infrastructures - ISGC 2010

引用

2014年

作者： Simon C Lin Eric Yen

ISBN: (纸本)9781489982476

ISGC 2010, The international symposium on Grid computing was held at Academia Sinica, Taipei, Taiwan, March, 2010. The 2010 symposium brought together prestigious scientists and engineers worldwide to exchange ideas, present challenges/solutions and to discuss new topics in the field of Grid computing. Data Driven e-science: Use Cases and Successful applications of distributed computing Infrastructures (ISGC 2010), an edited volume, introduces the latest achievements in grid technology for Biomedicine Life sciences, Middleware, Security, Networking, Digital Library, Cloud computing and more. This book provides Grid developers and end users with invaluable information for developing grid technology and applications. The last section of this book presents future development in the field of Grid computing. This book is designed for a professional audience composed of grid users, developers and researchers working in the field of grid computing. Advanced-level students focused on computer science and engineering will also find this book valuable as a reference or secondary text book.

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Biomedical applications on the GRID: Efficient management of parallel jobs

Biomedical applications on the GRID: Efficient management of...

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2004 Nuclear science symposium, Medical Imaging Conference, symposium on Nuclear Power Systems and the 14th international Workshop on Room Temperature Semiconductor X- and Gamma- Ray Detectors

作者： Mościcki, J.T. Lee, H.C. Guatelli, S. Lin, S.C. Pia, M.G. CERN IT 1211 Geneva 23 Switzerland Academia Sinica Computing Centre 128 Sec. 2 Academia Rd. Nankang 11529 Taipei Taiwan INFN Sezione di Geneva Via Dodccaneso 33 16146 Genova Italy

distributed computing based on the Master-Worker and PULL interaction model is applicable to a number of applications in high energy physics, medical physics and bioinformatics. We demonstrate a realistic medical physics use-case of a dosimetric system for brachytherapy using distributed GRID resources. We present the efficient techniques for running parallel jobs in a case of the BLAST, a gene sequencing application, as well as for the Monte Carlo simulation based on Geant 4. We present a strategy for improving the runtime performance and robustness of the jobs as well as for the minimization of the development time needed to migrate the applications to a distributed environment. © 2004 IEEE.

关键词： Biomedical engineering

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