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IEEE international conference on High Performance computing and Communications (HPCC)

作者： Xiaowei Chen Xiaowen Chu Adele L. Jia Johan A. Pouwelse Computer Science Department Hong Kong Baptist University Hong Kong China Parallel and Distributed System Delft University of Technology Netherlands

Private BitTorrent community (PT), as known as "BitTorrent Darknet", has become a popular research spot in recent years. PTs can provide ultra-high download performance which is much better than public BitTorrent communities. the Sharing Ratio Enhancement (SRE) mechanism is the key to PTs' success. However, it also brings negative side effects to the registered users in PTs. In this paper, we crawl and analyze all of user profiles from three influential PTs which provide very detailed information. We show that the sharing ratio of members cannot represent their upload contribution in terms of upload time and amount. Members are forced to seed for a long time to maintain adequate sharing ratios to survive in the community. SRE mechanism's nature drawbacks induce inequity. Based on these measurements, we propose a unified two-track payment system to pay peers based on their contribution, which is an alternative mechanism to SRE. We consider the payment with inflation and transit process. Our systems can provide a fair and consistent environment, which is helpful to unify and to build sustainable development of private BitTorrent communities.

关键词： Communities Educational institutions Peer to peer computing Computer science Sustainable development thin film transistors Measurement

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A Reconfigurable Multi-core computing Platform for Robotics and e-Health applications

A Reconfigurable Multi-core Computing Platform for Robotics ...

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international conference on Computer and Information Science (ACIS)

作者： Dennis Majoe Lars Widmer Liu Ling Jim Chih-Chen Kao Jurg Gutknecht MA Systems and Control Limited UK ETH Zürich Switzerland

Increasingly embedded devices are turning to two technologies to achieve high performance and enable efficient programmability as well as product usability. the first is multi-core processing on FPGA devices in which the multi-core architecture allows software to map application-level parallelism to inherent parallel fabric to offer better performance, the re-configurability leads to flexible and adaptive designs. the second is wireless communications that allow sensors to be distributed flexibly across a structure for example in the case of a body area network. this paper describes the ongoing design of a multi RF channel, multi-core embedded design which will be used as a generic FPGA solution to meet the requirements of both e-health applications as well as robotics applications.

关键词： Field programmable gate arrays Robots Program processors Sensors Electroencephalography Hardware parallel processing

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On key issuing privacy in distributed online social networks

On key issuing privacy in distributed online social networks

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international conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Tao Yang Liyong Tang Lingbo Kong Zhong Chen Institute of Software EECS MoE Key Laboratory of Network and Software Assurance MoE Key Laboratory of High Confidence Software Technologies Peking University Beijing China School of Software Engineering Beijing Jiaotong University Beijing China

Recently, distributed online social networks (OSNs) are developed to address the security and privacy issues in centralized OSNs. Identity based cryptography (IBC) was introduced into distributed OSNs recently for better identity verification and authentication purposes. However, current IBC-based solutions in OSNs could not address the problem of secure private key issuing. In this paper we propose PEKING: a novel Pivacy Enhanced Key IssuiNG scheme for distributed online social networks using IBC. Our scheme adopts key generate center (KGC) and key privacy assistants (PAs) to issue keys to peers securely. In the scheme, PAs can be selected from users' friends. Neither KGC nor PAs can impersonate the users to obtain the private keys. Furthermore, to maintain the security of PAs, we develop a scheme to authenticate PAs using Byzantine fault tolerance protocol. the experimental results show that PEKING performs effectively and efficiently, and is able to support large scale networks.

关键词： Peer to peer computing Cryptography Privacy Social network services Authentication Protocols

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2012年 7513 LNCS卷 V-VI页

作者： Park, James J. Zomaya, Albert Yeo, Sang-Soo Sahni, Sartaj SeoulTech Department of Computer Science and Engineering 172 Gongreung 2-dong Nowon-gu Seoul 139-743 Korea Republic of University of Sydney School of Information Technologies Building J12 Sydney NSW 2006 Australia Mokwon University Division of Computer Engineering 88 Do-An-Buk-Ro Seo-gu Daejeon 302-729 Korea Republic of University of Florida Computer and Information Science and Engineering Department CSE 301 Gainesville FL 32611 United States

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Data-intensive computing with map-reduce and hadoop

Data-intensive computing with map-reduce and hadoop

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international conference on Application of Information and Communication technologies (AICT)

作者： Shamil Humbetov Department of Computer Engineering Qafqaz University Azerbaijan Azerbaijan

Every day, we create 2.5 quintillion bytes of data - so much that 90% of the data in the world today has been created in the last two years alone. this data comes from everywhere: sensors used to gather climate information, posts to social media sites, digital pictures and videos, purchase transaction records, and cell phone GPS signals to name a few. the IDC sizing of the digital universe - information that is either created or captured in digital form and then replicated in 2006 - is 161 Exabyte, growing to 988 Exabyte in 2010, representing a compound annual growth rate (CAGR) of 57%. A variety of system architectures have been implemented for data-intensive computing and large-scale data analysis applications including parallel and distributed relational database management systems which have been available to run on shared nothing clusters of processing nodes for more than two decades. However most data growth is with data in unstructured form and new processing paradigms with more flexible data models were needed. Several solutions have emerged including the MapReduce architecture pioneered by Google and now available in an open-source implementation called Hadoop used by Yahoo, Facebook, and others. 20% of the world's servers go into huge data centers by the “Big 5” - Google, Microsoft, Yahoo, Amazon, eBay [1].

关键词： File systems Google Computers Data processing distributed databases Computational modeling Servers

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High Performance Database Processing

High Performance Database Processing

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international conference on Advanced Information Networking and applications (AINA)

作者： David Taniar Clayton School of Information Technology Monash University Clayton VIC Australia

the sizes of databases have seen exponential growth in the past, and such growth is expected to accelerate in the future, with the steady drop in storage cost accompanied by a rapid increase in storage capacity. Many years ago, a terabyte database was considered to be large, but nowadays they are sometimes regarded as small, and the daily volumes of data being added to some databases are measured in terabytes. In the future, petabyte and exabyte databases will be common. With such volumes of data, it is evident that the sequential processing paradigm will be unable to cope, for example, even assuming a data rate of 1 terabyte per second, reading through a petabyte database will take over 10 days. To effectively manage such volumes of data, it is necessary to allocate multiple resources to it, very often massively so. the processing of databases of such astronomical proportions requires an understanding of how high-performance systems and parallelism work. Besides the massive volume of data in the database to be processed, some data has been distributed across the globe in a Grid environment. these massive data centres are also a part of the emergence of Cloud computing, where data access has shifted from local machines to powerful servers hosting web applications and services, making data access across the Internet using standard web browsers pervasive. this adds another dimension to such systems. this talk, based on our recent published book [1], discusses fundamental understanding of parallelism in data-intensive applications, and demonstrates how to develop faster capabilities to support them. this includes the importance of indexing in parallel systems [2-4], specialized algorithms to support various query processing [5-9], as well as objectoriented scheme [10-12]. parallelism in databases has been around since the early 1980s, when many researchers in this area aspired to build large special-purpose database machines -- databases employing dedicated specialized

关键词： distributed databases parallel processing Query processing Bioinformatics Algorithm design and analysis

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parallel immune algorithm for lung cancer detection in X-ray images based on object shared space

Parallel immune algorithm for lung cancer detection in X-ray...

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2011 12th international conference on parallel and distributed computing, applications and technologies, PDCAT 2011

作者： Peng, Gang Yang, Xiong Liu, Li Dept. of Computer Science and Technology Huizhou University Huizhou City Guangdong 516007 China

ISBN: (纸本)9780769545646

this paper discusses a parallel immune algorithm (IA) for detection of lung cancer in chest X-ray images based on object shared space. the template matching method is combined to the algorithm and JavaSpaces is used as object shared space. the experiment results show that the algorithm is efficient for detecting suspected lung cancer in chest X-ray images. © 2011 IEEE.

关键词： Diseases

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Private cloud system based on BOINC with support for parallel and distributed simulation

Private cloud system based on BOINC with support for paralle...

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9th IEEE Int. Conf. on Dependable, Autonomic and Secure Comput., DASC 2011, incl. 9th Int. Conf. on Pervasive Intelligence and computing, PICom 2011, 9th Int. Symp. on Embedded computing, EmbeddedCom 2011, 1st Int. Conf. on Cloud and Green Comput.CGC

作者： Wu, Yihua Cao, Jian Li, Minglu Shanghai Key Laboratory of Scalable Computing and Systems Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9780769546124

Cloud computing provides an efficient way to expose computing capabilities as sophisticated services that can be accessed remotely. It eliminates the need for organizations to maintain extensive infrastructures. parallel and distributed simulation over cloud will bring us not only the increased productivity and efficiency but also the lower barrier for usage. this paper introduces a private cloud system based on BOINC which supports parallel and distributed simulation. the design idea and implementation method of each component for our system is discussed in detail. © 2011 IEEE.

关键词： BOINC parallel and distributed simulation private cloud parallel Lines design concept Distribute simulating Cloud computing

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On using pattern matching algorithms in MapReduce applications

On using pattern matching algorithms in MapReduce applicatio...

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9th IEEE international Symposium on parallel and distributed Processing with applications, ISPA 2011

作者： Rizvandi, Nikzad Babaii Taheri, Javid Zomaya, Albert Y. Center for Distributed and High Performance Computing School of Information Technologies University of Sydney Australia Australian Technology Park Sydney NSW 1430 Australia

ISBN: (纸本)9780769544281

In this paper, we study CPU utilization time patterns of several MapReduce applications. After extracting running patterns of several applications, they are saved in a reference database to be later used to tweak system parameters to efficiently execute unknown applications in future. To achieve this goal, CPU utilization patterns of new applications are compared with the already known ones in the reference database to find/predict their most probable execution patterns. Because of different patterns lengths, the Dynamic Time Warping (DTW) is utilized for such comparison;a correlation analysis is then applied to DTWs' outcomes to produce feasible similarity patterns. three real applications (WordCount, Exim Mainlog parsing and Terasort) are used to evaluate our hypothesis in tweaking system parameters in executing similar applications. Results were very promising and showed effectiveness of our approach on pseudo-distributed MapReduce platforms. © 2011 IEEE.

关键词： MapReduce

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A multi-constraint preemption algorithm for parallel job scheduling

A multi-constraint preemption algorithm for parallel job sch...

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2011 12th international conference on parallel and distributed computing, applications and technologies, PDCAT 2011

作者： Luo, Hongbing Wu, Linping Wang, Wei Applied Physics and Computional Mathematics High Performance Computing Center Institute 100094 Beijing China

ISBN: (纸本)9780769545646

Using effective scheduling strategies to improve turnaround time, slowdown, and utilization is an important consideration in large supercomputing environments. Since such machines have traditionally used non-preemption strategies to accommodate multiple jobs at the same time, a number of questions remain unanswered regarding the practical effect of preemptive scheduling. In this paper, we first discuss how to improve the turnaround time, slowdown, and utilization using an appropriate suspension criterion. We then develop a new multi-constraint preemptive scheduling algorithm (MCPS). Finally, we describe the experiments on a simulator with several realistic workloads. the experimental results show that MCPS is better than the conventional no-preemption strategies, and outperforms other preemptive scheduling strategies by its balanced performance. © 2011 IEEE.

关键词： Scheduling algorithms

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