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检索条件"任意字段=10th International Conference on Parallel and Distributed Computing, Applications and Technologies"

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Big Data Platform Development with a Domain Specific Language for Telecom Industries

Big Data Platform Development with a Domain Specific Languag...

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10th international conference on High-Capacity Optical Networks and Emerging/Enabling technologies (HONET-CNS)

作者： Senbalci, Cuneyt Altuntas, Serkan Bozkus, Zeki Arsan, Taner Kadir Has Univ Dept Comp Engn TR-34083 Istanbul Turkey

ISBN: (纸本)9781479925698;9781479925681

this paper introduces a system that offer a special big data analysis platform with Domain Specific Language for telecom industries. this platform has three main parts that suggests a new kind of domain specific system for processing and visualization of large data files for telecom organizations. these parts are Domain Specific Language (DSL), parallel Processing/Analyzing Platform for Big Data and an Integrated Result Viewer. hi addition to these main parts, distributed File Descriptor (DFD) is designed for passing information between these modules and organizing communication. To find out benefits of this domain specific solution, standard framework of big data concept is examined carefully. Big data concept has special infrastructure and tools to perform for data storing, processing, analyzing operations. this infrastructure can be grouped as four different parts, these are infrastructure, programming models, high performance schema free databases, and processing-analyzing. Although there are lots of advantages of Big Data concept, it is still very difficult to manage these systems for many enterprises. therefore, this study suggest a new higher level language, called as DSL which helps enterprises to process big data without writing any complex low level traditional parallel processing codes, a new kind of result viewer and this paper also presents a Big Data solution system that is called Petaminer.

关键词： Big Data Analysis Domain Specific Language parallel Processing and Analyzing

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distributed computing and Artificial Intelligence: 10th international conference

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2013年

作者： Sigeru Omatu Jos Neves Juan M Corchado Rodriguez

ISBN: (纸本)9783319005522

the international Symposium on distributed computing and Artificial Intelligence 2013 (DCAI 2013) is a forum in which applications of innovative techniques for solving complex problems are presented. Artificial intelligence is changing our society. Its application in distributed environments, such as the internet, electronic commerce, environment monitoring, mobile communications, wireless devices, distributed computing, to mention only a few, is continuously increasing, becoming an element of high added value with social and economic potential, in industry, quality of life, and research. this conference is a stimulating and productive forum where the scientific community can work towards future cooperation in distributed computing and Artificial Intelligence areas. these technologies are changing constantly as a result of the large research and technical effort being undertaken in both universities and businesses. the exchange of ideas between scientists and technicians from both the academic and industry sector is essential to facilitate the development of systems that can meet the ever increasing demands of today's society. this edition of DCAI brings together past experience, current work, and promising future trends associated with distributed computing, artificial intelligence and their application in order to provide efficient solutions to real problems. this symposium is organized by the Bioinformatics, Intelligent System and Educational Technology Research Group (http://***/) of the University of Salamanca. the present edition was held in Salamanca, Spain, from 22nd to 24th May 2013.

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Energy Analysis of Hadoop Cluster Failure Recovery

Energy Analysis of Hadoop Cluster Failure Recovery

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14th international conference on parallel and distributed computing, applications and technologies (PDCAT)

作者： Xu, Weiyue Lu, Ying Univ Nebraska Dept Comp Sci & Engn Lincoln NE 68588 USA

ISBN: (纸本)9781479924189

Energy efficiency is now used as an important metric for evaluating a computing system. However, saving energy is a big challenge due to many constraints. For example, in one of the most popular distributed processing frameworks, Hadoop, three replicas of each data block are randomly distributed in order to improve performance and fault tolerance. But such a mechanism limits the largest number of machines that can be turned off to save energy without affecting the data availability. To overcome this limitation, previous research introduces a new mechanism called covering subset which maintains a set of active nodes to ensure the immediate availability of data, even when all other nodes are turned off. this covering subset based mechanism works smoothly if no failure happens. However, a node in the covering subset may fail. In this paper, we study the energy-efficient failure recovery in Hadoop clusters. Rather than only using the replication as adopted by a Hadoop system by default, we investigate both replication and erasure coding as possible redundancy mechanisms. We develop failure recovery algorithms for both systems and analytically compare their energy efficiency.

关键词： Data transfer Decoding distributed databases Encoding Energy consumption Fault tolerance Fault tolerant systems Fault tolerant systems distributed databases Fault tolerance data transmission failure recovery DECODING energy consumption data availability Energy efficiency active nodes ENERGY ANALYSIS

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

Proceedings - 2011 12th International Conference on Parallel...

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

ISBN: (纸本)9780769545646

the proceedings contain 73 papers. the topics discussed include: guaranteed scheduling for (m,k)-firm deadline-constrained real-time tasks on multiprocessors;a distributed task migration scheme for mesh-based chip-multiprocessors;jMigBSP: object migration and asynchronous one-sided communication for BSP applications;a social network-based information dissemination scheme;XunleiProbe: a sensitive and accurate probing on a large-scale P2SP system;data flow error recovery with checkpointing and instruction-level fault tolerance;an experimental study on memory allocators in multicore and multithreaded applications;efficient hierarchical agglomerative clustering algorithms on GPU using data partitioning;the multidimensional scaling and barycentric coordinates based distributed localization in wireless sensor networks;fast estimation of Gaussian mixture model parameters on GPU using CUDA;and optimizing web browser on many-core architectures.

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Efficient Distribution of Sensing Queries in Public Sensing Systems

Efficient Distribution of Sensing Queries in Public Sensing ...

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IEEE 10th international conference on Mobile Ad-Hoc and Sensor Systems (MASS)

作者： Baier, Patrick Duerr, Frank Rothermel, Kurt Univ Stuttgart Inst Parallel & Distributed Syst D-70569 Stuttgart Germany

ISBN: (纸本)9780769551043

the advent of mobile phones paved the way for a new paradigm for gathering sensor data termed "Public Sensing" (PS). PS uses built-in sensors of mobile devices to opportunistically gather sensor data. For instance, the microphones that are available in a crowd of mobile phones can be used to capture sound samples, which can be used to construct a city noise map. A great challenge of PS is to reduce the energy consumption of mobile devices since otherwise users might not be willing to participate. One crucial part in the overall power consumption is the energy required for the communication between the mobile devices and the infrastructure. In particular, the communication required for sending sensing queries to mobile devices has been largely neglected in the related work so far. therefore, in this paper, we address the problem of minimizing communication costs for the distribution of sensing queries. While existing systems simply broadcast sensing queries to all devices, we use a selective strategy by addressing only a subset of devices. In order not to negatively affect the quality of sensing w.r.t. completeness, this subset is carefully chosen based on a probabilistic sensing model that defines the probability of mobile devices to successfully perform a given sensing query. Our evaluations show that with our optimized sensing query distribution, the energy consumption can be reduced by more than 70% without significantly reducing the quality of sensing.

关键词： Mobile computing Energy-aware systems

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Slot Selection Algorithms in distributed computing with Non-dedicated and Heterogeneous Resources

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12th international conference on parallel computing technologies (PaCT)

作者： Toporkov, Victor Toporkova, Anna Tselishchev, Alexey Yemelyanov, Dmitry Natl Res Univ MPEI Ul Krasnokazarmennaya 14 Moscow 111250 Russia Natl Res Univ Higher Sch Econom Moscow State Inst Elect & Math Moscow 109028 Russia European Org Nucl Res CERN CH-1211 Geneva Switzerland

ISBN: (纸本)9783642399572;9783642399589

In this work, we introduce slot selection and co-allocation algorithms for parallel jobs in distributed computing with non-dedicated and heterogeneous resources (clusters, CPU nodes equipped with multicore processors, networks etc.). A single slot is a time span that can be assigned to a task, which is a part of a job. the job launch requires a co-allocation of a specified number of slots starting synchronously. the challenge is that slots associated with different resources of distributed computational environments may have arbitrary start and finish points that do not match. Some existing algorithms assign a job to the first set of slots matching the resource request without any optimization (the first fit type), while other algorithms are based on an exhaustive search. In this paper, algorithms for effective slot selection of linear complexity on an available slots number are studied and compared with known approaches. the novelty of the proposed approach consists of allocating alternative sets of slots. It provides possibilities to optimize job scheduling.

关键词： distributed computing economic scheduling resource management slot job task batch

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A Game theory based Repeated Rational Secret Sharing Scheme for Privacy Preserving distributed Data Mining

A Game Theory based Repeated Rational Secret Sharing Scheme ...

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10th international conference on Security and Cryptography (SECRYPT)

作者： Nanavati, Nirali R. Jinwala, Devesh C. Sardar Vallabhbhai Natl Inst Technol Surat India

ISBN: (纸本)9789897581311

Collaborative data mining has become very useful today with the immense increase in the amount of data collected and the increase in competition. this in turn increases the need to preserve the participants' privacy. there have been a number of approaches proposed that use Secret Sharing for privacy preservation for Secure Multiparty Computation (SMC) in different setups and applications. the different multiparty scenarios may have parties that are semi- honest, rational or malicious. A number of approaches have been proposed for semi honest parties in this setup. the problem however is that in reality we have to deal with parties that act in their self- interest and are rational. these rational parties may try and attain maximum gain without disrupting the protocol. Also these parties if cautioned would correct themselves to have maximum individual gain in the future. thus we propose a new practical game theoretic approach with three novel punishment policies with the primary advantage that it avoids the use of expensive techniques like homomorphic encryption. Our proposed approach is applicable to the secret sharing scheme among rational parties in distributed data mining. We have analysed theoretically the proposed novel punishment policies for this approach. We have also empirically evaluated and implemented our scheme using Java. We compare the punishment policies proposed in terms of the number of rounds required to attain the Nash equilibrium with eventually no bad rational nodes with different percentage of initial bad nodes.

关键词： Privacy Game theory Secure Multiparty Computation Rational Secret Sharing distributed Data Mining

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EasyHPS: A multilevel hybrid parallel system for dynamic programming

EasyHPS: A multilevel hybrid parallel system for dynamic pro...

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2013 IEEE 37th Annual Computer Software and applications conference, COMPSAC 2013

作者： Du, Jun Yu, Ce Sun, Jizhou Sun, Chao Tang, Shanjiang Yin, Yanlong School of Computer Science and Technology Tianjin University China School of Computer Engineering Nanyang Technological University Singapore Department of Computer Science Illinois Institute of Technology Chicago IL 60616 United States

ISBN: (纸本)9780769549798

Dynamic programming approach solves complex problems efficiently by breaking them down into simpler sub-problems, and is widely utilized in scientific computing. With the increasing data volume of scientific applications and development of multi-core/multi-processor hardware technologies, it is necessary to develop efficient techniques for parallelizing dynamic programming algorithms, particularly in multilevel computing environment. the intrinsically strong data dependency of dynamic programming also makes it difficult and error-prone for the programmer to write a correct and efficient parallel program. In order to make the parallel programming easier and more efficient, we have developed a multilevel hybrid parallel runtime system for dynamic programming named EasyHPS based on the Directed Acyclic Graph(DAG) Data Driven Model in this paper. the EasyHPS system encapsulates details of parallelization implementation, such as task scheduling and message passing, and provides easy API for users to reduce the complexity of parallel programming parallelization. In the DAG Data Driven Model, the entire application is initially partitioned by data partitioning into sub-tasks that each sub-task processing a data block. then all sub-tasks are modeled as a DAG, in which each vertex represents a sub-task and each edge indicates the communication dependency between the two sub-tasks. In task scheduling, a dynamic approach is proposed based on DAG Data Driven Model to achieve load balancing. Data partitioning and task scheduling are both done on processor-level and thread-level in the multilevel computing environment. In addition, experimental results demonstrate that the proposed dynamic scheduling approach in EasyHPS is more efficient in comparison with those static ones such as block-cyclic based wave front. © 2013 IEEE.

关键词： Directed graphs

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distributed processing of elevation data by means of apache hadoop in a small cluster

Distributed processing of elevation data by means of apache ...

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8th international Joint conference on Software technologies, ICSOFT 2013

作者： Komarkova, Jitka Spidlen, Jakub Bhattacharya, Devanjan Horak, Oldrich Faculty of Economics and Administration University of Pardubice Studentska 95 532 10 Pardubice Czech Republic

ISBN: (纸本)9789898565686

Geoinformation technologies require fast processing of high and quickly increasing volumes of all types of spatial data. parallel computational approach and distributed systems represent technologies which are able to provide required services, with reasonable costs. MapReduce is one example of such approach. It has been successfully implemented in large clusters in several instances. the applications include spatial and imagery data processing. the contribution deals with its implementation and operational performance using only a very small cluster (consisting of a few commodity personal computers) to process large-volume spatial data. Open-source implementation of MapReduce, named, Apache Hadoop, is used. the contribution is focused on a low-price solution and it deals with speed of processing and distribution of processed files. Authors run several experiments to evaluate the benefit of distributed data processing in a small-sized cluster and to find possible limitations. Size of processed files and number of processed values is used as the most important criteria for performance evaluation. Point elevation data were used during the experiments. Copyright © 2013 SCITEPRESS.

关键词： MapReduce

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Algorithms for High-throughput Disk-to-Disk Sorting 13

Algorithms for High-Throughput Disk-to-Disk Sorting

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international conference for High Performance computing, Networking, Storage and Analysis (SC)

作者： Sundar, Hari Malhotra, Dhairya Schulz, Karl W. Univ Texas Austin Austin TX 78712 USA Texas Adv Comp Ctr Austin TX 78712 USA

ISBN: (纸本)9781450323789

In this paper, we present a new out-of-core sort algorithm, designed for problems that are too large to fit into the aggregate RAM available on modern supercomputers. We analyze the performance including the cost of TO and demonstrate the fastest (to the best of our knowledge) reported throughput using the canonical sort Benchmark on a general-purpose, production HPC resource running Lustre. By clever use of available storage and a formulation of asynchronous data transfer mechanisms, we are able to almost completely hide the computation (sorting) behind the TO latency. this latency hiding enables us to achieve comparable execution times, including the additional temporary TO required, between a large sort problem (5TB) run as a single, in-RAM sort and our out-of-core approach using 1/10th the amount of RAM. In our largest run, sorting 100TB of records using 1792 hosts, we achieved an end-to-end throughput of 1.24TB/min using our general-purpose sorter, improving on the current Daytona record holder by 65%.

关键词： Sorting Out-of-Core Algorithms parallel Algorithms shared-memory parallelism distributed-memory parallelism hypercube quicksort samplesort asynchronous methods

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