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Peer-to-peer networks and collective intelligence: The case for agency

Peer-to-peer networks and collective intelligence: The case ...

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5th international conference on P2P, parallel, Grid, Cloud and Internet computing, 3PGCIC 2010

作者： Hill, Richard Antonopoulos, Nikos Distributed and Intelligent Systems Research Group University of Derby Derby United Kingdom

ISBN: (纸本)9780769542379

The vast quantity of data contributed and consumed via the Internet provides an environment where Collective Intelligence (CI) can emerge. This article considers CI in relation to the Peer-to-Peer (P2P) paradigm, an environment that has the necessary conditions for the generation of large data sets through frequent peer interactions. We then examine the characteristics of agency and relate agent computing to the conditions required to facilitate CI in P2P systems. Furthermore, we present a key research challenge for the community and propose an approach to scrutinise CI in a P2P scenario that makes use of local primitive behaviours to infer the likely collective emergent behaviours for a particular system. © 2010 IEEE.

关键词： Peer to peer networks

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mPlogP: A parallel computation model for heterogeneous multi-core computer 10

mPlogP: A parallel computation model for heterogeneous multi...

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10th IEEE/ACM international Symposium on Cluster, Cloud, and Grid computing, CCGrid 2010

作者： Li, Liang Zhang, Xingjun Feng, Jinghua Dong, Xiaoshe Department of Computer Science and Technology Xi'an Jiaotong University Xi'an China

ISBN: (纸本)9781424469871

Due to the heterogeneity and the multigrain parallelism of the heterogeneous multi-core computer, communication and memory access show hierarchical characteristics ignored by other models. In this paper, a new model named mPlogP, is presented on the basis of the PlogP model, in which communication and memory access is abstracted by considering these new characteristics of the heterogeneous multi-core computer. It uses memory access to model the behavior of computation, estimates the execution time of every part of applications and guides the optimization of effective parallel programs. Finally this proposed model is validated by experiments that it can precisely evaluate the execution of parallel applications under the heterogeneous multi-core computer. © 2010 IEEE.

关键词： Memory architecture

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distributed analysis with PROOF in ATLAS collaboration

Distributed analysis with PROOF in ATLAS collaboration

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17th international conference on computing in High Energy and Nuclear Physics (CHEP)

作者： Panitkin, S. Y. Benjamin, D. Montoya, G. Carillo Cranmer, K. Ernst, M. Guan, W. Ito, H. Maeno, T. Majewski, S. Mellado, B. Rind, O. Shibata, A. Tarrade, F. Wenaus, T. Xu, N. Ye, S. Brookhaven Natl Lab Upton NY 11973 USA Duke Univ Durham NC 27708 USA Univ Wisconsin Madison Madison WI 53706 USA NYU New York NY 10003 USA

The parallel ROOT Facility - PROOF is a distributed analysis system which allows to exploit inherent event level parallelism of high energy physics data. PROOF can be configured to work with centralized storage systems, but it is especially effective together with distributed local storage systems - like Xrootd, when data are distributed over computing nodes. It works efficiently on different types of hardware and scales well from a multi-core laptop to large computing farms. From that point of view it is well suited for both large central analysis facilities and Tier 3 type analysis farms. PROOF can be used in interactive or batch like regimes. The interactive regime allows the user to work with typically distributed data from the ROOT command prompt and get a real time feedback on analysis progress and intermediate results. We will discuss our experience with PROOF in the context of ATLAS Collaboration distributed analysis. In particular we will discuss PROOF performance in various analysis scenarios and in multi-user, multi-session environments. We will also describe PROOF integration with the ATLAS distributed data management system and prospects of running PROOF on geographically distributed analysis farms.

关键词： High energy physics

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Peer interest-based discovery for decentralized peer-to-peer systems

Peer interest-based discovery for decentralized peer-to-peer...

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5th international conference on P2P, parallel, Grid, Cloud and Internet computing, 3PGCIC 2010

作者： Visan, Andreea Istin, Mihai Pop, Florin Xhafa, Fatos Cristea, Valentin Faculty of Automatics and Computer Science University POLITEHNICA of Bucharest Romania Department of Languages and Informatics Systems Technical University of Catalonia Barcelona Spain

ISBN: (纸本)9780769542379

The success of content distribution oriented peer-to-peer systems heavily depends on the resource discovery mechanism. In case of large-scale distributed systems, this mechanism must be scalable and robust. The paper proposes a structured solution for resource discovery in decentralized peer-to-peer systems, which is guided by peer interest in collaborating with other peers. The problem of discovering peers of interest has many applications in file sharing, in data-aware scheduling, and in optimizing the files and documents downloads. Moreover, if trust is added as another parameter to define peers of interest, the interest-based discovery is useful in trusted P2P applications. We focused on developing the overlay network to ensure a very small number of messages required to retrieve, insert or delete a file even in the case of a very large network containing millions of nodes. In the experimental validation we used Over Sim, a simulation tool for P2P systems. The experimental results highlight the good performance obtained regarding message communication and system's scalability. © 2010 IEEE.

关键词： distributed computer systems

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16th IEEE international conference on parallel and distributed systems, ICPADS 2010

作者： Luo, Xiangfeng Ni, Jingjing Zhang, Jun Wang, Lizhe High Performance Computing Center School of Computer Engineering and Science Shanghai University Shanghai 200072 China Pervasive Technology Institute Indiana University United States

ISBN: (纸本)9780769543079

Similar Link Network (SiLN) is a semantic over layer on Web resources with similar relations instead of hyperlinks, which aims at providing plentiful semantics for intelligent Web activities. However, SiLN is difficult to be built based on cosine computation in large-scale Web resources due to its high building time complexity and weak connectivity. Herein, three strategies are proposed to address those issues. First, dividing and conquering strategy is applied to divide the large-scale Web resources into amounts of rough similar communities, which reduces SiLN's building time complexity significantly. After that, a multi-level structure network is designed to effectively manage the large-scale Web resources to guarantee SiLN's connectivity. Finally, two-level feedback with isolated resources strategy is developed to improve the accuracy of the building of SiLN. Experimental results have proved that our proposed method of building SiLN is feasible and efficient, with the merits of low complexity, good connectivity and high precision. © 2010 IEEE.

关键词： Semantics

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Optimizing service level agreements for autonomic cloud bursting schedulers

Optimizing service level agreements for autonomic cloud burs...

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international Workshop on Scheduling and Resource Management for parallel and distributed systems

作者： Kailasam, Sriram Gnanasambandam, Nathan Dharanipragada, Janakiram Sharma, Naveen Distributed and Object Systems Lab Dept. of Comp. Sci. and Engg. IIT Madras Chennai 600036 India Xerox Research Center Webster Xerox Corporation Webster NY 14580 United States

ISBN: (纸本)9780769541570

The practice of computing across two or more data centers separated by the Internet is growing in popularity due to an explosion in scalable computing demands and payas- you-go schemes offered on the cloud. While cloud-bursting is addressing this process of scaling up and down across data centers (i.e. between private and public clouds), offering service level guarantees, is a challenge for inter-cloud computation, particularly for best-effort traffic and large files. The parallel workload we address is real-time and involves inter-cloud processing and analysis of images and documents. In our production printing domain, dedicated processing/network resources are cost-prohibitive. Further, the problem is exacerbated by data intensive computing - we encounter huge file sizes atypical of intercloud parallel processing. To address these problems we propose three flavors of autonomic cloud-bursting schedulers that offer probabilistic guarantees on service levels required by customers (such as speed-up and queue sequence preservation) by adapting to changing workload characteristics, variation in bandwidth and available resources. In particular, these opportunistic schedulers use a quadratic response surface model for processing time in concert with a time-of-day dependent bandwidth predictor to increase the throughput and utilization while simultaneously reducing out-of-sequence completions for a document processing workload. © 2010 IEEE.

关键词： Bandwidth

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Using grid computing to accelerate optimization solution: A system of systems approach

Using grid computing to accelerate optimization solution: A ...

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2010 5th international conference on System of systems Engineering, SoSE 2010

作者： Pham, D.T. Marzi, H. Marzi, A. Marzi, E. Darwish, A. Haj Lee, J.Y. Manufacturing Engineering Centre Cardiff University Cardiff CF24 3AA United Kingdom Dept. of Information Systems St. Francis Xavier University NS B2G 2W5 Canada

ISBN: (纸本)9781424481972

This paper presents a system of systems approach to implement high-speed searching to solve complex optimization problems. In most optimization techniques, parallel computation is not effective due to the complexity in algorithm. Here, the search space is distributed within processing power of high performance computing resources. The methodology takes advantage of the Bees Algorithm and adapts it for best performance in a cluster grid computing environment. The effectiveness of the approach is verified by solving the problem of efficiency in a power plant by economizing fuel cost, efficiency of transmission losses and environmental hazardous emissions. © 2010 IEEE.

关键词： Optimization

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Evaluation of improvement algorithms for dynamic co-allocation with respect to parallel downloading in grid computing

Evaluation of improvement algorithms for dynamic co-allocati...

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international conference on Integrated Intelligent computing

作者： Suvarna, N.A. Chandra, Dinesh JSS Academy of Technical Education Noida-201301 India

ISBN: (纸本)9780769541525

Grid technology is the next evolutionary level in the field of distributed systems. This technology is used to create the illusion of a super computer by connecting a number of heterogeneous systems to share various kinds of resources and to solve large scale problems[3]. Grid technology, with SOA architecture[2] has lead to the virtualization of almost every real life activity. Data Grid is one such, which is used to solve data intensive applications by sharing tera and peta bytes of information. Since a single computer cannot handle such huge amount of data, replication and fragmentation is used. It improves the data retrieval performance in a Grid environment by increasing the data availability[6]. But, for parallel downloading, replication alone will not suffice. Downloading a data file from multiple locations in parallel also require multiple data streams between the clients of an enterprise and the Internet. The Dataset is then divided into a number of disjoint blocks of equal size and threads are created, with each thread downloading a single block of data. Next, these threads are executed in parallel across a number of grid nodes on the client side. Algorithms for scheduling this task must ensure the completion of download process in addition to improving the speed. This research paper is based on the practical outcomes of the implementation of a parallel downloading process in a Grid setup with ***[1] as the Grid machinery and runtime environment for windows based systems. © 2010 IEEE.

关键词： Grid computing

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7th IFIP TC 10 Working conference on distributed and parallel Embedded systems, DIPES 2010 and 3rd IFIP TC 10 international conference on Biologically-Inspired Collaborative computing, BICC 2010 held as part of the 21st IFIP World Computer Congress, WCC 2010

7th IFIP TC 10 Working Conference on Distributed and Paralle...

引用

7th IFIP TC 10 Working conference on distributed and parallel Embedded systems, DIPES 2010 and 3rd IFIP TC 10 international conference on Biologically-Inspired Collaborative computing, BICC 2010 Held as Part of 21st IFIP World Computer Congress, WCC 2010

ISBN: (纸本)9783642152337

The proceedings contain 29 papers. The special focus in this conference is on distributed, parallel and Biologically Inspired systems. The topics include: Mastering conflicting trends in embedded systems design;a language for heterogeneous computations;scenario-based modeling in industrial information systems;an entirely model-based framework for hardware design and simulation;extending the standard execution model of UML for real-time systems;task migration for fault-tolerant flexray networks;flexible and dynamic replication control for interdependent distributed real-time embedded systems;generation of executable testbenches from natural language requirement specifications for embedded real-time systems;model checking of concurrent algorithms;integrate online model checking into distributed reconfigurable system on chip with adaptable OS services;efficient mutation-analysis coverage for constrained random verification;generating VHDL source code from UML models of embedded systems;a rapid, architectural simulation and synthesis framework for embedded processors;a mixed level simulation environment for stepwise RTOS software refinement;dependency-driven distribution of synchronous programs;distributed resource-aware scheduling for multi-core architectures with system C;robust partitioned scheduling for real-time multiprocessor systems;an infrastructure for flexible runtime reconfigurable multi-microcontroller systems;feature selection for classification using an ant system approach;a collaborative decision support model for marine safety and security operations and collaborating and learning predators on a pursuit scenario.

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On the parallelization and Optimization of the Genetic-Based ANN Classifier for the Diagnosis of Students with Learning Disabilities

On the Parallelization and Optimization of the Genetic-Based...

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IEEE international conference on systems, Man and Cybernetics

作者： Wu, T-K Huang, S-C Lin, Y-L Chang, H. Meng, Y-R Natl Changhua Univ Educ Changhua Taiwan Natl Hsinchu Univ Educ Hsinchu Taiwan

ISBN: (纸本)9781424465880

Diagnosis of students with learning disabilities has long been a difficult issue as it requires extensive man power and takes a long time. Through genetic algorithm based feature selection method and genetic based parameters optimization, artificial neural network (ANN) classifier has proven to be a good predictor to the diagnosis of students with learning disabilities. In this study, we keep focusing on the ANN model and compare three strategies of parallelizing the ANN parameter optimization procedure with OpenMP and MPI APIs. Not surprisingly, the outcomes show that all three parameter optimization procedures indeed converged or executed more quickly with the aid of parallel processing. In particular, the genetic-based method tends to derive the best accuracy and require less execution time. Most important of all, potentially due to a more diverse search space provided by the distributed parallel processing environment, the accuracy of the genetic-based ANN classifier may also be improved in general. In addition, with appropriate combinations of features and parameters setting, the accuracy in LD identification model has exceeded the 90% mark (using 5-fold cross validation), which is the best we have achieved so far. The result suggests that genetic-based (or perhaps similar) optimization methods may be benefited, both in reducing execution time and achieving better outcome, from current grid-based computing technologies.

关键词： Learning Disabilities Genetic Algorithm Evolutionary Computation Grid computing Neural Network

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