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

共 1765 条记录，以下是441-450 订阅

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Track Chair's Report: Convergence of distributed Clouds, Grids and their Management CDCGM 2017 Cloud Native or Cloud Agnostic? that is the Question in 2017 WETICE2017 Poznan, Poland, June 21-23, 2017 26

Track Chair's Report: Convergence of Distributed Clouds, Gri...

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26th IEEE international conference on Enabling technologies - Infrastructure for Collaborative Enterprises (WETICE)

作者： Messina, Fabrizio Mikkilineni, Rao Morana, Giovanni Rosaci, Domenico Univ Catania Dept Math & Informat Vle Andrea Doria 6 I-95125 Catania Italy C3DNA Inc Santa Clara CA USA C3DNA Inc R&D & Engn Catania Italy Univ Reggio Calabria DICEAM Dept Reggio Di Calabria RC Italy

ISBN: (纸本)9781538617595

this track started in 2009 with opening remarks from the Chair observing that the computing cloud evolution depends on research efforts from the infrastructure providers creating next generation hardware that is service friendly, service developers that embed business service intelligence in the computing infrastructure to create distributed business workflow execution services and service providers who assure service delivery on a massive scale with global interoperability. the state of the art architecture and evolution of the cloud at that time was already increasing datacenter complexity by piling up new layers of management over the many layers that already exist. Since then, the scale of distributed applications and their management have taken a new dimension demanding tolerance to wild fluctuations both in workloads and available computing resource pools. there are many calls to go cloud native and architect applications using the many services provided by the cloud providers such as Amazon Web Services. On the other hand, there are also calls for avoiding vendor lock-in by going multi-cloud and becoming cloud agnostic. In this conference there is a new paper that proposes cloud agnostic approach with globally interoperable cloud network using private or public network while reducing the complexity of Virtual machine image motion across clouds. In addition, there are 7 papers describing advances in current distributed and cloud computing practices dealing with quality of service, adaptive algorithms and software defined network architectures.

关键词： Cloud computing grid computing distributed Intelligent Managed Element Networks distributed Services Management Services Virtualization parallel computing

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An Unsupervised Approach for Online Detection and Mitigation of High-Rate DDoS Attacks Based on an In-Memory distributed Graph Using Streaming Data and Analytics 17

An Unsupervised Approach for Online Detection and Mitigation...

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10th international conference on Utility and Cloud computing (UCC) / 4th international conference on Big Data computing, applications and technologies (BDCAT)

作者： Villalobos, J. J. Rodero, Ivan Parashar, Manish Rutgers Univ State Univ New Jersey Rutgers Discovery Informat Inst Piscataway NJ 08854 USA

ISBN: (纸本)9781450355490

A distributed Denial of Service (DDoS) attack is an attempt to make an online service, a network, or even an entire organization, unavailable by saturating it with traffic from multiple sources. DDoS attacks are among the most common and most devastating threats that network defenders have to watch out for. DDoS attacks are becoming bigger, more frequent, and more sophisticated. Volumetric attacks are the most common types of DDoS attacks. A DDoS attack is considered volumetric, or high-rate, when within a short period of time it generates a large amount of packets or a high volume of traffic. High-rate attacks are well-known and have received much attention in the past decade;however, despite several detection and mitigation strategies have been designed and implemented, high-rate attacks are still halting the normal operation of information technology infrastructures across the Internet when the protection mechanisms are not able to cope with the aggregated capacity that the perpetrators have put together. With this in mind, the present paper aims to propose and test a distributed and collaborative architecture for online high-rate DDoS attack detection and mitigation based on an in-memory distributed graph data structure and unsupervised machine learning algorithms that leverage real-time streaming data and analytics. We have successfully tested our proposed mechanism using a real-world DDoS attack dataset at its original rate in pursuance of reproducing the conditions of an actual large scale attack.

关键词： DDoS Detection DDoS Mitigation Machine Learning distributed Big Data Analytics

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ECCount: Efficient and Consistent Counter for high-speed network devices 15

ECCount: Efficient and Consistent Counter for high-speed net...

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15th IEEE international Symposium on parallel and distributed Processing with applications (ISPA) / 16th IEEE international conference on Ubiquitous computing and Communications (IUCC)

作者： Wang, Junchang He, Wen Zhou, Ningning Li, Tao Fu, Xiong Nanjing Univ Posts & Telecommun Sch Comp Sci Jiangsu Key Lab Big Data Secur & Intelligent Proc Nanjing 210023 Jiangsu Peoples R China

ISBN: (纸本)9781538637906

Nowadays, 10Gbps and higher speed network devices have become ubiquitous. these devices typically exploit multiple CPU cores to process packets to avoid overwhelming a single CPU core. the involving of multiple cores, however, brings tricky parallel programming issues. One of them is the miscount in statistical counter, which is the algorithm that has been widely used in high-speed network devices to track fundamental information such as the number of packets received and transmitted. As a result, modern high-speed network devices merely provides weak consistency guarantee on the counting results it returns;that is, the returned results may be inaccurate. this paper first analyses the miscount issue in modern high-speed network devices. then we present ECCount, a novel counting algorithm which (1) is competitive to the best known solutions in performance, and (2) provides strong consistency guarantee in counting results returned. Experiments show that it takes ECCount 10ns and 1,500ns to perform an update operation and a read operation, respectively. And the counting results returned are accurate.

关键词： lock-free counting algorithm strong consistency

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Profit-aware workload management for geo-distributed data centers 18

Profit-aware workload management for geo-distributed data ce...

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18th international conference on parallel and distributed computing, applications and technologies, PDCAT 2017

作者： Gao, Yongqiang Wei, Hengchao College of Computer Science Inner Mongolia University Hohhot China

ISBN: (纸本)9781538631515

With the rising demand on internet online services, more and more individuals and organizations migrate their data and services from local to geographically distributed internet data centers for reliability, management, and cost benefits. From internet data center operators' perspective, profit is one of the most significant factors which are to be taken into account and it is mainly determined by the quality of service and the electricity cost. In this work, we jointly take the diversity of time-varying electricity prices, the quality of service and the power usage effectiveness of data centers into consideration and propose a profit optimization framework that includes three important decisions: requests dispatching, the number of active servers and frequency adjustment. An efficient heuristic algorithm is then developed to provide internet data center operators with the advice on these decisions to achieve profit maximization for geographically distributed data centers. through extensive trace-driven simulations, we demonstrate the effectiveness and superiority of our solution. © 2017 IEEE.

关键词： Quality of service

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Joint operator replication and placement optimization for distributed streaming applications 10

Joint operator replication and placement optimization for di...

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10th EAI international conference on Performance Evaluation Methodologies and Tools, ValueTools 2016

作者： Cardellini, Valeria Grassi, Vincenzo Lo Presti, Francesco Nardelli, Matteo Department of Civil Engineering and Computer Science Engineering University of Rome Tor Vergata Italy

ISBN: (纸本)9781631901416

In the last few years, several processing approaches have emerged to deal with Big Data. Exploiting on-the-fly computation, Data Stream Processing (DSP) applications can process unbounded streams of data to extract valuable information in a near real-time fashion. To keep up with the high volume of daily produced data, the operators that compose a DSP application can be replicated and placed on multiple, possibly distributed, computing nodes, so to process the incoming data flow in parallel. In this paper, we present Optimal DSP Replication and Placement (ODRP), a unified general formulation of the operator replication and placement problem that takes into account the heterogeneity of application requirements and infrastructural resources. A key feature of ODRP is the joint optimization of the operators replication and their placement. We evaluate the proposed model through a set of numerical experiments that demonstrates its flexibility and the benefits that derive from the joint optimization. Copyright © 2016 EAI.

关键词： Big data

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Refactoring the Molecular Docking Simulation for Heterogeneous, Manycore Processors Systems 15

Refactoring the Molecular Docking Simulation for Heterogeneo...

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15th IEEE international Symposium on parallel and distributed Processing with applications (ISPA) / 16th IEEE international conference on Ubiquitous computing and Communications (IUCC)

作者： Chen, Junshi Lin, Han Liang, Weihao Yu, Yang Han, Wenting An, Hong Chen, Yong Liu, Xin Univ Sci & Technol China Sch Comp Sci & Technol Hefei Anhui Peoples R China Texas Tech Univ Dept Comp Sci Lubbock TX 79409 USA Natl Res Ctr Parallel Comp Engn & Technol Beijing Peoples R China

ISBN: (纸本)9781538637906

this paper presents a scalable design and implementation of the molecular docking application DOCK for a large-scale high performance computing system, the Sunway TaihuLight supercomputer, which provisions a heterogeneous, manycore processor architecture that consists of management processing elements (MPEs) and clusters of computing processing elements (CPEs). the key innovation is a novel refactoring of DOCK on the CPEs. Optimization techniques for data redundancy minimization to fit data in cache, software-controlled prefetching into scratchpads, memory access coalescing, software caches, vectorization and loop unrolling are employed to improve the exploitation of the computational resources. For a single docking process, the refactored version using both the MPE and CPE cluster achieved 260x to 402x speedup compared against the original ported version using MPE only. To scale the DOCK to the full Sunway Taihulight system with 10,649,600 cores (including all MPE and CPE cores), we present an MPI communication domain partition scheme as well. For docking 9 million small compounds to a Zika virus target protein, we manage to scale to 131,072 MPEs, and 8,388,608 CPEs, with a total of 8,519,680 cores.

关键词： molecular docking Sunway TaihuLight Supercomputer heterogeneous manycore optimization

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Performance Analysis of Large Scale distributed Systems by Ranking Dominant Features 17

Performance Analysis of Large Scale Distributed Systems by R...

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10th international conference on Utility and Cloud computing (UCC) / 4th international conference on Big Data computing, applications and technologies (BDCAT)

作者： Fesehaye, Debessay Singaravelu, Lenin Banerjee, Amitabha Zhou, Ruijin Huang, Xiaobo Chen, Chien-Chia Somasundaran, Rajesh Google Inc Mountain View CA 94043 USA

ISBN: (纸本)9781450355490

Large scale distributed systems generate so many metrics/features to monitor and analyze their performances. Most of the analysis to detect performance regressions and root causes of the regressions is done by manually looking at graphs of the metric values. this approach is error prone and doesn't scale. there are some recent works to automate root cause analysis. However these schemes either rely on specific network metrics or aggregate values such as median. Such approach, which doesn't use various physical and virtual device specific metrics, is ineffective in detecting anomalies and their root causes for large scale distributed systems/clusters such as VMware Virtual Storage Area Network (vSAN) and vSphere. In this paper we present the design and analysis of various system anomaly and root cause metric identification algorithms. these algorithms rely on identifying and ranking dominant performance metrics. We implemented these algorithms by extending a widely used machine learning tool. We validated and tested our algorithms using standard test benchmarks in the VMware vSAN. Our implementation prototype also consists of a D3 based visualizer which shows the metric rankings. In the real world regression experiments we conducted, most of our algorithms find the performance root cause metrics in the top 5 out of about 500 metrics. In 10 out of 12 experiments conducted on vSAN, two of our algorithms found the root cause metrics in the top 5 out of about 500 metrics. Our algorithms metric ranking outperform a correlation based metric ranking algorithm, which we also implemented in our work.

关键词： Metric ranking dominant features root cause

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Join Operations to Enhance Performance in Hadoop MapReduce Environment 5th

Join Operations to Enhance Performance in Hadoop MapReduce E...

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5th international conference on Frontiers in Intelligent computing - theory and applications (FICTA)

作者： Pagadala, Pavan Kumar Vikram, M. Eswarawaka, Rajesh Reddy, P. Srinivasa JNTUH Bharat Inst Engn Technol Hyderabad India JNTUA Sri Venkateswara Coll Engn Anantapur Andhra Pradesh India Dayananda Sagar Univ Bangalore Karnataka India

ISBN: (纸本)9789811031564;9789811031557

Analyzing large data sets is gaining more importance because of its wide variety of applications in parallel and distributed environment. Hadoop environment gives more flexibility to programmers in parallel computing. One of the advantages of Hadoop is query evaluation over large datasets. Join operations in query evaluation plays a major role over the large data. this paper Ferret outs the earlier solutions, prolongs them and recommends a new approach for the implementation of joins in Hadoop.

关键词： Hadoop Query evaluation distributed environment Performance analysis Optimization

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A parallel pairwise alignment with pruning for large genomic sequences 18

A parallel pairwise alignment with pruning for large genomic...

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18th international conference on parallel and distributed computing, applications and technologies, PDCAT 2017

作者： Zhu, Xiangyuan Li, Bing Li, Kenli Shao, Ping Pan, Yi School of Computer Science Zhaoqing University Zhaoqing526061 China Department of Computer Science Georgia State University AtlantaGA30302 United States College of Information Science and Engineering Hunan University Changsha410082 China

ISBN: (纸本)9781538631515

Pairwise sequence alignment is a common and fundamental task in Computational Biology, which constitutes the basis for many Bioinformatics applications. In the post-genomic era, there is an increasing demand to align long DNA sequences to discover their functions. In this paper, we propose a parallel pairwise alignment algorithm for large genomic sequences by recursively dividing the whole genomic sequences into small pieces, with an effective pruning strategy to reduce search and computation space. We implemented rigorous tests on a 4-core computer using real genomic sequences and artificially generated sequences. the results show that our implementation can achieve speedup 10.64 with 99.75% accuracy compared to the sequential algorithm. As far as we know, this is the first time that MBP (mega base-pairs) sequences are globally aligned with an affine gap penalty. © 2017 IEEE.

关键词： DNA sequences

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Human action recognition using wavelets of derived beta distributions 18

Human action recognition using wavelets of derived beta dist...

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18th international conference on parallel and distributed computing, applications and technologies, PDCAT 2017

作者： Jaouedi, Neziha Boujnah, Noureddine Bouhlel, Mohamed Salim National Engineering School Gabes Tunisia Sciences and Technologies of Image and Telecommunications High Institute of Biotechnology Sfax Tunisia Faculty of Sciences Gabes Tunisia

ISBN: (纸本)9781538631515

In the framework of human machine interaction systems enhancement, we focus throw this paper on human behavior analysis and action recognition. Human behavior is characterized by actions and reactions duality (movements, psychological modification, verbal and emotional expression. Its worth noting that many information are hidden behind gesture, sudden motion points trajectories and speeds, many research works reconstructed an information retrieval issues. In our work we will focus on motion extraction, tracking and action recognition using wavelet network approaches. Our contribution uses an analysis of human subtraction by Gaussian Mixture Model (GMM) and body movement through trajectory models of motion constructed from kalman filter. these models allow to remove the noise using the extraction of the main motion features and constitute a stable base to identify the evolutions of human *** modality is used to recognize a human action using wavelets of derived beta distributions approach. the proposed approach has been validated successfully on a subset of Kth and UCF sport database. © 2017 IEEE.

关键词： Extraction

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