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检索条件"任意字段=International Conference on Parallel and Distributed Processing Techniques and Applications"

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Minimizing Network Traffic for distributed Joins Using Lightweight Locality-Aware Scheduling 24th

Minimizing Network Traffic for Distributed Joins Using Light...

引用

24th international European conference on parallel and distributed Computing (Euro-Par)

作者： Cheng, Long Murphy, John Liu, Qingzhi Hao, Chunliang Theodoropoulos, Georgios Univ Coll Dublin PEL Dublin Ireland Eindhoven Univ Technol Eindhoven Netherlands Chinese Acad Sci Inst Software Beijing Peoples R China Southern Univ Sci & Technol Shenzhen Peoples R China

ISBN: (纸本)9783319969831;9783319969824

Large computing systems such as data centers are becoming the mainstream infrastructures for big data processing. As one of the key data operators in such scenarios, distributed joins is still challenging current techniques since it always incurs a significant cost on network communication. Various advanced approaches have been proposed to improve the performance, however, most of them just focus on data skew handling, and algorithms designed specifically for communication reduction have received less attention. Moreover, although the state-of-the-art technique can minimize network traffic, it provides fine-grained optimal schedules for all individual join keys, which could result in obvious overhead. In this paper, we propose a new approach called LAS (Lightweight Locality-Aware Scheduling), which targets reducing network communication for large distributed joins in an efficient and effective manner. We present the detailed design and implementation of LAS, and conduct an experimental evaluation using large data joins. Our results show that LAS can effectively reduce scheduling overhead and achieve comparable performance on network reduction compared to the state-of-the-art.

关键词： Scheduling

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Colony: parallel Functions as a Service on the Cloud-Edge Continuum 27th

Colony: Parallel Functions as a Service on the Cloud-Edge Co...

引用

27th international European conference on parallel and distributed Computing (Euro-Par)

作者： Lordan, Francesc Lezzi, Daniele Badia, Rosa M. Barcelona Supercomp Ctr BSC Dept Comp Sci Barcelona Spain

ISBN: (纸本)9783030856656;9783030856649

Although smart devices markets are increasing their sales figures, their computing capabilities are not sufficient to provide good-enough-quality services. This paper proposes a solution to organize the devices within the Cloud-Edge Continuum in such a way that each one, as an autonomous individual -Agent-, processes events/data on its embedded compute resources while offering its computing capacity to the rest of the infrastructure in a Function-as-a-Service manner. Unlike other FaaS solutions, the described approach proposes to transparently convert the logic of such functions into task-based workflows backing on task-based programming models;thus, agents hosting the execution of the method generate the corresponding workflow and offloading part of the workload onto other agents to improve the overall service performance. On our prototype, the function-to-workflow transformation is performed by COMPSs;thus, developers can efficiently code applications of any of the three envisaged computing scenarios - sense-process-actuate, streaming and batch processing - throughout the whole Cloud-Edge Continuum without struggling with different frameworks specifically designed for each of them.

关键词： Edge Fog Cloud Compute Continuum distributed systems Programming model Runtime system Serverless Function-as-a-Service Stream-processing Task-based workflow

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BCE: A privacy-preserving common-friend estimation method for distributed online social networks without cryptography

BCE: A privacy-preserving common-friend estimation method fo...

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2012 7th international ICST conference on Communications and Networking in China, CHINACOM 2012

作者： Fu, Yongquan Wang, Yijie National Key Laboratory for Parallel and Distributed Processing College of Computer Science National University of Defense Technology Hunan province 410073 China

ISBN: (纸本)9781467326995

distributed online social networks (DOSN) have emerged recently. Nevertheless, recommending friends in the distributed social networks has not been exploited fully. We propose BCE (Bloom Filter based Common-Friend Estimation), a scalable and privacy-preserving common-friend estimation scheme that estimates the set of common friends without the need of cryptography techniques. First, BCE denotes each user using the identifiers created by the Peer-to-Peer underlay that are robust against the dictionary attacks. Second, BCE uses a Bloom filter to represent a friend list for scalability. Third, BCE estimates common friends of two users using the intersection of Bloom filters computed by one of their common friends, which ensures the privacy of friend lists against unknown users. Our privacy analysis shows that BCE hides the privacy of each user with a high probability. Simulations over real-world social-network data sets confirms that BCE is both accurate and scalable. © 2012 IEEE.

关键词： Social networking (online)

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Moving to the Cloud: Workload Migration techniques and Approaches

Moving to the Cloud: Workload Migration Techniques and Appro...

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19th international conference on High Performance Computing (HiPC)

作者： Banerjee, Joydipto IBM Corp Kolkata India

ISBN: (纸本)9781467323703

The paper presents an important aspect of cloud computing technology, namely migrating enterprise level workloads to a cloud environment, without re-architecting or re-engineering the existing applications. How readily an application can be lifted and shifted onto a cloud platform depends on factors like nature of the application, the type of cloud etc. In this respect, the paper explores the methodology of migrations along with the challenges and issues that usually acts as a barrier for organizations trying to pursue this goal. An effort is also made to see how the cloud migration framework maps to the cloud Computing Reference Architecture model. Finally, a set of migration patterns which span the continuum from legacy IT environment to the cloud are included as a common framework for aligning the various migration approaches developed in support of using cloud as a delivery paradigm.

关键词： business data processing cloud computing organisational aspects

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j2eeprof-a tool for testing multitier applications

j2eeprof-a tool for testing multitier applications

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IFIP Working conference on Software Engineering techniques

作者： Klaczewski, Pawel Wytrebowicz, Jacek Warsaw Univ Technol Inst Comp Sci Warsaw Poland

ISBN: (纸本)0387393870

Quality assurance of multitier application is still a challenge. Especially difficult is testing big, distributed applications written by several programmers, with the use of components from different sources. Due to multi threaded and distributed architecture, their ability to be observed and their profiling are extremely difficult. J2eeprof is a new tool developed for testing and profiling multitier applications that run in the J2EE environment. The tool is based on the paradigm of aspect insertion. The main goal of j2eeprof is to help in fixing of integration errors and efficiency errors. This paper presents the concept of j2eeprof and gives some insides of j2eeprof development. On the beginning we give some introduction to the methods of software profiling, and a brief characteristic of existing profilers, i.e., JFluid, Iron Track Sql, Optimizelt Server Trace and JXInsight. Next we present the architecture of j2eeprof, and we describe how it collects data, what protocols it uses, and what kind of analysis it supports. On the end we demonstrate how j2eeprof works in practice. In conclusions we list the strong and weak points of this tool, which is still in a beta version. J2eeprof is planned to be offered as an open source for the programmer community.

关键词： Quality assurance

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Protocol synthesis from context-free processes using event structures 5

Protocol synthesis from context-free processes using event s...

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5th international conference on Real-Time Computing Systems and applications

作者： Nakata, A Higashino, T Taniguchi, K Hiroshima City Univ Dept Comp Sci Asaminami Ku Hiroshima 7313194 Japan

ISBN: (纸本)081869209X

In this paper we propose a protocol synthesis method based on a partial order model (called event structures)for the class of context-free processes. First, we assign a unique name called event ID to every event executable by a given service specification. An event ID is a finite sequence of symbols derived from the context-free process specification. Then we show that some interesting sets of events are expressible by regular expressions on symbols, and that the event structure can be finitely represented by a set of relations among the regular expressions. Finally, we present a method to derive a protocol specification which implements a given service specification on distributed nodes, by using the obtained finite representation of event structures. The derived protocol specification contains the minimum message exchanges necessary to ensure the partial order of events of the service specification.

关键词： formal description techniques distributed systems protocol synthesis context-free processes event structures

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Exploiting Apache Flink's Iteration Capabilities for distributed Apriori: Community Detection Problem as an example 5

Exploiting Apache Flink's Iteration Capabilities for Distrib...

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

作者： Rathee, Sanjay Kashyap, Arti IIT Sch Comp & Elect Engn Mandi Himachal Pardes India

ISBN: (纸本)9781509020287

Extraction of useful information from large datasets is one of the most important research problem. Association rule mining is one of the best methods for this purpose. Finding possible associations between items in large transaction based datasets (finding frequent patterns) is most important part of the association rule mining. There exists many algorithms to find frequent patterns but Apriori algorithm always remains a preferred choice due to its ease of implementation and natural tendency to be parallelized. Many single-machine based Apriori variants exist but massive amount of data available these days is above capacity of a single machine. Therefore, to meet the demands of this ever-growing huge data, there is a need of multiple machines based Apriori algorithm. For these type of distributed applications, mapreduce is a popular fault-tolerant framework. Hadoop is one of the best open-source software framework with mapreduce approach for distributed storage and distributed processing of huge datasets using clusters built from commodity hardware. But heavy disk I/O operation at each iteration of a highly iterative algorithm like Apriori makes hadoop inefficient. A number of map reduce based platforms are being developed for parallel computing in recent years. Among them, two platforms, namely, Spark and Flink have attracted lot of attention because of their inbuilt support to distributed computations. Earlier we had proposed a reduced- Apriori algorithm on Spark platform which outperforms parallel Apriori, firstly because of use of Spark and secondly because of the improvement we proposed in standard Apriori. Therefore, present work is a natural sequel of our earlier work and targets on implementing, testing and benchmarking Apriori on Apache Flink and compares it with Spark implementation. We conduct in-depth experiments to gain insight into the effectiveness, efficiency and scalability of the Apriori algorithm on Flink. We also use community detection graph mi

关键词： Apriori Apache Flink Mapreduce Spark Hadoop R-Apriori Frequent itemset mining

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Accelerating multimedia applications using Intel Threading Building Blocks on multi-core processors

Accelerating multimedia applications using Intel Threading B...

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2011 international conference on Information Science and applications, ICISA 2011

作者： Kim, Cheong Ghil Dept. of Computer Science Namseoul University Maejuri Seongwhaneub Seobukgu Cheonan Chungnam Korea Republic of

ISBN: (纸本)9781424492244

The recent development on semiconductor process and design technologies enables multi-core processors to become a dominant market trend in desk-top PCs as well as high end mobile devices. At the same time, the increasing popularity of high quality digital contents processing makes processors to quip with dedicated instructions based on sub-word parallelism in order to process streaming data. This paper presents a way of optimizations of 2D convolution operator, a widely used technique in image and signal processing applications, on speed in Intel multi-core processors. Two optimization techniques are discussed in detail. One is the streaming SIMD (Single Instruction Multiple Data) extension (SSE) technology, available in Intel processors, for data parallelism. The other is the Intel TBB (Threading Building Block) run-time library to exploit parallelism in task level. As a result, this paper can investigate the advantage of two different parallelisms, both data and task, concurrently. For the performance evaluation, we implemented Sobel operator using SSE and TBB with different combinations and compared their processing speeds. The results show that both technologies have a significant effect on the performance and the processing speed can be greatly improved when using two technologies at the same time. © 2011 IEEE.

关键词： parallel processing systems

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Succinct representations in collaborative filtering: A case study using wavelet tree on 1,000 cores 20

Succinct representations in collaborative filtering: A case ...

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20th international conference on parallel and distributed Computing, applications and Technologies, PDCAT 2019

作者： Peng, Xiangjun Wang, Qingfeng Sun, Xu Gong, Chunye Wang, Yaohua User-Centric Computing Group University of Nottingham Ningbo China China Department of Computer Science and Technology National University of Defense Technology China Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology China

ISBN: (纸本)9781728126166

User-Item (U-I) matrix has been used as the dominant data infrastructure of Collaborative Filtering (CF). To reduce space consumption in runtime and storage, caused by data sparsity and growing need to accommodate side information in CF design, one needs to go beyond the U-I Matrix. In this paper, we took a case study of Succinct Representations in Collaborative Filtering, rather than using a U-I Matrix. Our key insight is to introduce Succinct Data Structures as a new infrastructure of CF. Towards this, we implemented a User-based K-Nearest-Neighbor CF prototype via Wavelet Tree, by first designing a Accessible Compressed Documents (ACD) to compress U-I data in Wavelet Tree, which is efficient in both storage and runtime. Then, we showed that ACD can be applied to develop an efficient intersection algorithm without decompression, by taking advantage of ACD's characteristics. We evaluated our design on 1,000 cores of Tianhe-II supercomputer, with one of the largest public data set ml-20m. The results showed that our prototype could achieve 3.7 minutes on average to deliver the results. © 2019 IEEE.

关键词： Collaborative filtering

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Analysis on Big Data techniques

Analysis on Big Data Techniques

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international conference on Advances in Soft Computing, Intelligent Systems and applications (ASISA)

作者： Harleen Garg, Naveen Amity Univ Dept Informat Technol Noida India

ISBN: (纸本)9789811052729;9789811052712

Nowadays, digitization data is used and there are more and more data that generates everyday about everything. Data sets whose size is complex or large that commonly used today. Management of this data which ensures that the data from varied sources is processed error free and is of good quality to perform analysis processing and sharing of such a large data by traditional methods is difficult by the use of traditional methods. So we need such systems that are more flexible, scalable, fault tolerance, compatible, and cheap to process large amount of data. Hadoop is designed to handle the extremely high volumes of data in any structure. There are various ways for Hadoop to run the job. The three programming approaches that are MapReduce, Hive, and Pig are used. In this paper, we present the comparison of MapReduce, Hive, and Pig. These three techniques are useful under different constraints.

关键词： Hadoop MapReduce Pig Hive Hadoop distributed file system ReStore

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