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8th ACM international conference on distributed Event-Based Systems, DEBS 2014

作者： Ottenwälder, Beate Koldehofe, Boris Rothermel, Kurt Hong, Kirak Ramachandran, Umakishore Institute of Parallel and Distributed Systems University of Stuttgart Stuttgart Germany College of Computing Georgia Institute of Technology Atlanta GA United States

ISBN: (纸本)9781450327374

An appealing use case of complex event processing (CEP) systems is for mobile users to react in real-time to events in their environment, e.g., to the occurrence of a dangerous situation such as an accident. Maintaining mobile CEP systems is highly resource intensive since in many cases events need to be detected in a consumer-centric manner to ensure low latency event detection and high quality of results. In this paper we propose the RECEP system to increase the scalability of mobile CEP systems. In the presence of mobile users with partially overlapping interest, the RECEP system offers methods to efficiently reuse computations and this way reduces the resource requirements of mobile CEP. Since reuse of computations happens with respect to well defined quality metrics, RECEP can be easily tailored to specific mobile applications and maximize the resource savings for their desired quality in terms of precision and recall of the processed events from the user's environment. © 2014 ACM.

关键词： Real time systems

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Stream oriented modular architecture with polymorphic processing engines 26

Stream oriented modular architecture with polymorphic proces...

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26th IEEE international Symposium on Computer Architecture and High Performance Computing Workshops, SBAC-PADW 2014

作者： Gorobets, Andriy Pratas, Frederico Roma, Nuno Tomís, Pedro INESC-ID IST Universidade de Lisboa Portugal

ISBN: (纸本)9781479970148

Stream computing has shown to be an effective technique to decouple communication from computation in many application domains. It provides an efficient mitigation of bandwidth restrictions, by reducing the amount of memory accesses and by maximizing the available computational resources, potentiating the parallel processing using multiple execution engines. However, it frequently implies significant development costs, since efficient stream-based architectures are usually attained through application-specific full-custom processors, often tightened to the application at hand. To circumvent this limitation, a modular stream computing architecture aiming generic and high performance applications is presented. The proposed architecture, designed for reconfigurable hardware, is composed of modular processing engines that can be customized by the end-user in many ways, such as in terms of their number, type and precision of the functional units. Furthermore, these processing engines are designed as programmable cores, allowing the execution of a wide set of applications using the same configuration. From the conducted evaluation by using a series of benchmark case studies, it was observed that the proposed architecture achieves competitive results when compared with alternative solutions. © 2014 IEEE.

关键词： Engines

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Reliability based routing strategy for performance Optimization in distributed Mobile Computing through clustering 3

Reliability based routing strategy for performance Optimizat...

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international conference parallel distributed Grid Computing

作者： Khan, Faizul Navi Govil, Kapil Agarwal, Alok Teerthanker Mahaveer Univ Moradabad UP India JP Inst Engn & Tech Meerut Uttar Pradesh India

ISBN: (纸本)9781479976836

Technology enhancement makes the computing available everywhere and provides access to widely distributed resources which is known as Mobile Computing. Mobile computing enables innovative applications through the sharing of computing resources among mobile devices such as notebook, smart phones and Personal Digital Assistant (PDAs) without any pre-existing infrastructure. Mobile computing includes a number of technologies and devices. The state of the user, static or mobile, does not affect the information management capability of the mobile platform. A user can continue to access and perform data manipulation during the state of mobility by using mobile computing devices. Delivering data packets between pair of processors is a primary responsibility of any mobile computing network This activity is performed using a routing strategy Maximize reliability of the data packets always a major concern while transmitting the data from one point to another point. In mobile computing it is the process of determining the data path through the network that data packets will move from the one computing device to another computing device. Routing strategy for data transmission is an important factor for achieving high degree of reliability. Multiple data packets are move within a network from source to destination in order to execute on available processing units with the objective of getting maximum reliability of data packets. This research paper present a routing strategy to achieve maximum data packets transmission reliability in mobile computing network during the data transmission.

关键词： Data transmission Mobile computing performance Routing Reliability

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parallel k-way partitioning approach for large graphs

Parallel k-way partitioning approach for large graphs

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2014 international conference on Frontiers of Advanced Materials and Engineering Technology, FAMET 2014

作者： Xu, Jin Zhong, Yu Peng, Bo China Coal Technology Engineering Group Chongqing Research Institute China

ISBN: (纸本)9783038350774

With the emergence of large social networks, such as Facebook and Twitter, graphs with millions to billions vertices are common. Instead of processing the network within a single machine, all the applications related are intended to be done in a distributed way using a cluster of commodity machines. In this paper, we study the parallel graph partitioning problem, which is the fundamental operation for large graphs. With the help of Hadoop/MapReduce, we propose a parallel k-way partitioning approach. Unlike the previous ones, which require enough memory to keep the whole graph data within, our novel approach breaks such limitations. Also, due to the distributed nature, it is easy to integrate our partitioning approach into existed parallel platforms. We conduct extensive experiments on real graphs and synthetic graphs. All the experimental results prove the effectiveness and efficiency of our approach. © (2014) Trans Tech Publications, Switzerland.

关键词： MapReduce

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distributed Vertex-Cut Partitioning

Distributed Vertex-Cut Partitioning

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14th IFIP WG 6.1 international conference on distributed applications and Interoperable Systems (DAIS)

作者： Rahimian, Fatemeh Payberah, Amir H. Girdzijauskas, Sarunas Haridi, Seif Swedish Inst Comp Sci Stockholm Sweden Royal Inst Technol KTH Stockholm Sweden

ISBN: (纸本)9783662433522;9783662433515

Graph processing has become an integral part of big data analytics. With the ever increasing size of the graphs, one needs to partition them into smaller clusters, which can be managed and processed more easily on multiple machines in a distributed fashion. While there exist numerous solutions for edge-cut partitioning of graphs, very little effort has been made for vertex-cut partitioning. This is in spite of the fact that vertex-cuts are proved significantly more effective than edge-cuts for processing most real world graphs. In this paper we present JA-BEJA- VC, a parallel and distributed algorithm for vertex-cut partitioning of large graphs. In a nutshell, JA-BE-JA-VC is a local search algorithm that iteratively improves upon an initial random assignment of edges to partitions. We propose several heuristics for this optimization and study their impact on the final partitioning. Moreover, we employ simulated annealing technique to escape local optima. We evaluate our solution on various graphs and with variety of settings, and compare it against two state-of-the-art solutions. We show that JA-BE-JA-VC outperforms the existing solutions in that it not only creates partitions of any requested size, but also requires a vertex-cut that is better than its counterparts and more than 70% better than random partitioning.

关键词： Big data

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Hierarchical parallelization and Runtime Scheduling for Pregel-like Graph processing Systems 6

Hierarchical Parallelization and Runtime Scheduling for Preg...

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6th IEEE international conference on Cloud Computing Technology and Science (CloudCom)

作者： Li, Zengxiang Duan, Rubing Wang, Long Lu, Sifei Qin, Zheng Goh, Rick Siow Mong ASTAR Inst High Performance Comp Singapore Singapore

ISBN: (纸本)9781479940936

Graph processing has become popular for various big data analytic applications. Google's Pregel framework enables vertex-centric graph processing in distributed environment based on Bulk Synchronous parallel (BSP) model. However, the BSP model is inefficient for many complex graph algorithms requiring graph traversals, as only a small number of vertices really update states in each superstep. In this paper, we propose an hierarchical parallelization mechanism, taking the advantages of both synchronous (warp-level) and asynchronous (task-level) parallelization approaches. In addition, a runtime task scheduling mechanism is proposed, relying on real-time monitoring or prediction of resource utilization. Experiments have verified that the hierarchical parallelization mechanism can expose greater parallelism, and thus, increase resource utilization significantly. Moreover, the runtime scheduling mechanism can avoid aggressive resource competition, and thus, further enhance the performance of the parallelized graph processing.

关键词： Graph processing Pregel parallelization Scheduling Resource utilization Betweenness Centrality

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FooPar: A Functional Object Oriented parallel Framework in Scala 1

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10th international conference on parallel processing and Applied Mathematics (PPAM)

作者： Hargreaves, Felix Palludan Merkle, Daniel Univ Southern Denmark Dept Math & Comp Sci Odense Denmark

ISBN: (数字)9783642551956

ISBN: (纸本)9783642551956

We present FooPar, an extension for highly efficient parallel Computing in the multi-paradigm programming language Scala. Scala offers concise and clean syntax and integrates functional programming features. Our framework FooPar combines these features with parallel computing techniques. FooPar is designed to be modular and supports easy access to different communication backends for distributed memory architectures as well as high performance math libraries. In this article we use it to parallelize matrix-matrix multiplication and show its scalability by a isoefficiency analysis. In addition, results based on a empirical analysis on two supercomputers are given. We achieve close-to-optimal performance wrt. theoretical peak performance. Based on this result we conclude that FooPar allows programmers to fully access Scalas design features without suffering from performance drops when compared to implementations purely based on C and MPI.

关键词： Functional programming Isoefficiency Matrix multiplication

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GridSys- A state of the art grid framework 3

GridSys- A state of the art grid framework

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3rd international conference on Advances in Computing, Communications and Informatics (ICACCI)

作者： Shenoy, Sanath John, Nimmy Eeratta, Raghavendra Nair, Ranjith Siemens Technol & Serv Pvt Ltd Bangalore Karnataka India

ISBN: (纸本)9781479930807

Today many applications are developed using distributed technologies such as cluster, cloud and grid computing. These applications demand more resources for computation and storage. They demand flexible scaling and improved performance. Application now days can make use of multiple nodes (machines) to get the tasks completed. In this paper we discuss the, implementation details of a grid computing framework known as GridSys. This framework provides a fast and easy way to program a grid. It can easily help the application break the problem to compute intensive tasks. The framework distributes these tasks to different nodes of the grid efficiently and easily aggregate the results of these tasks provide fault tolerance and reliability.

关键词： Grid Computing Framework parallel processing

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Data Transmission techniques for Mobile Sensor Networks

Data Transmission Techniques for Mobile Sensor Networks

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28th IEEE international conference on Advanced Information Networking and applications Workshops (IEEE WAINA)

作者： Yoshihisa, Tomoki Nishio, Shojiro Osaka Univ Cybermedia Ctr Suita Osaka Japan Osaka Univ Grad Sch Info Sei & Tech Dept Multimedia Engn Suita Osaka Japan

ISBN: (纸本)9781479926527

In mobile sensor networks (MSNs), since sensor nodes and wireless networks are highly resource constrained and, it is highly required to manage sensor data in flexible and efficient manners. Under the MEXT research project(1) entitled "Studies on Efficient Data processing techniques for Mobile Sensor Networks," we have conducted researches on data management issues in MSNs. In this paper, we report some of our achievements in a sub-area of this project, which addresses data transmission for efficient data collection in MSNs. In particular, we first show our achievements on how to efficiently transmit sensor data from sensor nodes to mobile sink nodes considering the fairness and the amount of sensor data collected. Then, we also show our achievements on how to enlarge sensor data collection area and how to reduce communication traffic using mobile sink nodes.

关键词： mobile sensor networks data transmission sensor data collection mobile sinks fairness

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distributed RANDOM CONVEX PROGRAMMING VIA CONSTRAINTS CONSENSUS

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SIAM JOURNAL ON CONTROL AND OPTIMIZATION 2014年第1期52卷 629-662页

作者： Carlone, L. Srivastava, V. Bullo, F. Calafiore, G. C. Georgia Inst Technol Coll Comp Atlanta GA 30332 USA Princeton Univ Dept Mech & Aerosp Engn Princeton NJ 08544 USA Univ Calif Santa Barbara Ctr Control Dynam Syst & Computat Santa Barbara CA 93106 USA Politecn Torino Dipartimento Automat & Informat I-10129 Turin Italy

This paper discusses distributed approaches for the solution of random convex programs (RCPs). RCPs are convex optimization problems with a (usually large) number N of randomly extracted constraints;they arise in several application areas, especially in the context of decision-making under uncertainty;see [G. C. Calafiore, SIAM J. Optim., 20 (2010), pp. 3427-3464;G. C. Calafiore and M. C. Campi, IEEE Trans. Automat. Control, 51 (2006), pp. 742-753]. We here consider a setup in which instances of the random constraints (the scenario) are not held by a single centralized processing unit, but are instead distributed among different nodes of a network. Each node "sees" only a small subset of the constraints, and may communicate with neighbors. The objective is to make all nodes converge to the same solution as the centralized RCP problem. To this end, we develop two distributed algorithms that are variants of the constraints consensus algorithm [G. Notarstefano and F. Bullo, Proceedings of the 46th IEEE conference on Decision and Control, New Orleans, LA, 2007, pp. 927-932;G. Notarstefano and F. Bullo, IEEE Trans. Automat. Control, 56 (2011), pp. 2247-2261]: the active constraints consensus algorithm, and the vertex constraints consensus (VCC) algorithm. We show that the active constraints consensus algorithm computes the overall optimal solution in finite time, and with almost surely bounded communication at each iteration of the algorithm. The VCC algorithm is instead tailored for the special case in which the constraint functions are convex also with respect to the uncertain parameters, and it computes the solution in a number of iterations bounded by the diameter of the communication graph. We further devise a variant of the VCC algorithm, namely quantized vertex constraints consensus (qVCC), to cope with the case in which communication bandwidth among processors is bounded. We discuss several applications of the proposed distributed techniques, including estimation

关键词： distributed optimization distributed random convex programming constraints consensus distributed constraints removal parallel model predictive control

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