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Design and Development of an Adaptive Workflow-Enabled Spatial-Temporal Analytics Framework

Design and Development of an Adaptive Workflow-Enabled Spati...

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international conference on parallel and distributed systems (ICPADS)

作者： Xiaorong Li Rodrigo N. Calheiros Sifei Lu Long Wang Henry Palit Qin Zheng Rajkumar Buyya Institute of High Performance Computing A∗STAR Institute Singapore Department of Computing and Information Systems The University of Melbourne Australia

Cloud computing is a suitable platform for execution of complex computational tasks and scientific simulations that are described in the form of workflows. Such applications are managed by Workflow Management System (WfMS). Because existing WfMSs are not able to autonomically provision resources to real-time applications and schedule them while supporting fault tolerance and data privacy, we present a highly-scalable workflow-enabled analytics system that manages inter-dependable analytics tasks adaptively with varying operational requirements on a common platform and enables visualization of multidimensional datasets of real world phenomena. In this paper, we present the architecture of such a WfMS and evaluate it in terms of performance for execution of workflows in Clouds. A real world application of climate-associated dengue fever prediction was evaluated on public, private, and hybrid Clouds and experienced effective speedup in all the environments.

关键词： Cloud computing Computer architecture Real-time systems Resource management Security Data privacy Data visualization

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e-Science in the cloud with CARMEN

e-Science in the cloud with CARMEN

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18th international conference on parallel and distributed computing, Applications and Technologies, PDCAT 2007

作者： Watson, Paul School of Computing Science Newcastle University United Kingdom North East Regional e-Science Centre United Kingdom Department of Computer Science Newcastle University United Kingdom North East Regional e-Science Centre British Computer Society UK Computing Research Committee

ISBN: (纸本)0769530494

Understanding how the brain works is a major scientific challenge which will benefit medicine, biology and computer science. It requires knowledge of how information is encoded, accessed, analysed, archived and decoded by networks of neurons. Globally, over 100,000 neuroscientists are working on this problem. However, the data that forms the basis for their work is rarely shared even though it is difficult and expensive to produce. One of the main reasons for this is that vast amounts of data are produced in a variety of formats;this is then locally described and curated. One consequence is a shortage of analysis techniques that can be applied across neuronal systems. Further, there is only a limited amount of interaction between research centres with complementary expertise. the CARMEN project (***) is addressing these challenges. It enables data sharing, integration, and analysis supported by metadata. An expandable range of services are provided to extract value from raw and transformed data. the project's approach is to design and build a generic e-science platform in the cloud. this provides functionality to neuroscientists, who access it over the web. Scientists upload the data they generate into the system (called a CAIRN) and describe it with metadata. Internally, the CAIRN is built as a set of Web Services. these include a workflow enactment service which allows scientists to analyze data by running workflows that utilise the analysis services also held in the CAIRN. Users can browse the catalogue of existing workflows to select one that is appropriate for the task they are trying to accomplish. More expert users can build their own workflows from the available services. Even more sophisticated users can create their own services to use in workflows. A novel feature of the architecture is that the services are stored in a repository in the CAIRN and scheduled on a grid as required by the execution of workflows. this promotes the sharing of ana

关键词： Metadata

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Proceedings. 18th international conference on systems Engineering

Proceedings. 18th International Conference on Systems Engine...

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IEEE international conference on systems Engineering

the following topics are dealt with: avionics; computer algorithms, databases, parallel and distributed systems, networks; control theory, system identification and adaptive control, nonlinear controls; digital systems and architecture; environmental systems and energy systems; expert systems and artificial intelligence; finance engineering; information theory and communication systems; neural network and applications; requirements processes; signal processing; computer infrastructure for systems biology; data fusion; risk management; system architecture; systems engineering education; systems engineering metrics; standards and testing; systems engineering paradigms, standards, and challenges; and transportation systems.

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A centralized HIDS framework for private cloud

A centralized HIDS framework for private cloud

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ACIS international conference on Software Engineering, Artificial Intelligence, Networking, and parallel/distributed computing (SNPD)

作者： Zhijian Wang Yanqin Zhu School of Computer Science Technology Soochow University Suzhou China

ISBN: (纸本)9781509055050

Cloud computing is more convenient and efficient than traditional on-premise computing for users, as it provides large scale resources, software, and information to each customer. However, cloud computing systems can be easily threatened by various cyber attacks. therefore, an Intrusion Detection System (IDS) is very necessary for cloud computing system. there is a serious problem which traditional host-based IDS for cloud computing consumes a large amount of system resources. In this paper, we propose a centralized host-based IDS framework to reduce the use of the resources. Using logstash tool to collect the system logs from each virtual machine, and storing them into elasticsearch cluster centrally. After that, we analyze all these logs in the detection center and send the results to each virtual machine. We have validated our framework in the openstack platform. the results show a good performance in reducing the CPU and memory usage.

关键词： Cloud computing Virtual machining Intrusion detection Computational modeling Data collection Real-time systems

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Globally distributed computation over the Internet-the POPCORN project

Globally distributed computation over the Internet-the POPCO...

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international conference on distributed computing systems

作者： N. Nisan S. London O. Regev N. Camiel Inst. of Comput. Sci. Hebrew Univ. Jerusalem Israel Institute of Computer Science Hebrew University Jerusalem Israel

the POPCORN project provides an infrastructure for globally distributed computation over the whole Internet. It provides any programmer connected to the Internet with a single huge virtual parallel computer composed of all processors on the Internet which care to participate at any given moment. the system provides a market-based mechanism of trade in CPU time to motivate processors to provide their CPU cycles for other peoples' computations. Selling CPU time is as easy as visiting a certain Web site with a Java-enabled browser. Buying CPU time is done by writing a parallel program, using our programming paradigm (and libraries). this paradigm was designed to fit the situation of global computation. A third entity in our system is a market for CPU time, which is where buyers and sellers meet and trade. the system has been implemented and may be visited and used on our Web site: http://***/-popcorn.

关键词： distributed computing Internet

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DASH: A C++ PGAS Library for distributed Data Structures and parallel Algorithms

DASH: A C++ PGAS Library for Distributed Data Structures and...

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IEEE international conference on High Performance computing and Communications

作者： Karl Fuerlinger Tobias Fuchs Roger Kowalewski Comput. Sci. Dept. Ludwig-Maximilians-Univ. (LMU) Munich Munich Germany

ISBN: (纸本)9781509042982

We present DASH, a C++ template library that offers distributed data structures and parallel algorithms and implements a compiler-free PGAS (partitioned global address space) approach. DASH offers many productivity and performance features such as global-view data structures, efficient support for the owner-computes model, flexible multidimensional data distribution schemes and inter-operability with STL (standard template library) algorithms. DASH also features a flexible representation of the parallel target machine and allows the exploitation of several hierarchically organized levels of locality through a concept of Teams. We evaluate DASH on a number of benchmark applications and we port a scientific proxy application using the MPI two-sided model to DASH. We find that DASH offers excellent productivity and performance and demonstrate scalability up to 9800 cores.

关键词： Structures parallel Algorithms

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Pipelined parallel LZSS for Streaming Data Compression on GPGPUs

Pipelined Parallel LZSS for Streaming Data Compression on GP...

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international conference on parallel and distributed systems (ICPADS)

作者： Adnan Ozsoy Martin Swany Arun Chauhan School of Informatics and Computing Indiana University Bloomington

In this paper, we present an algorithm and provide design improvements needed to port the serial Lempel-Ziv-Storer-Szymanski (LZSS), lossless data compression algorithm, to a parallelized version suitable for general purpose graphic processor units (GPGPU), specifically for NVIDIA's CUDA Framework. the two main stages of the algorithm, substring matching and encoding, are studied in detail to fit into the GPU architecture. We conducted detailed analysis of our performance results and compared them to serial and parallel CPU implementations of LZSS algorithm. We also benchmarked our algorithm in comparison with well known, widely used programs, GZIP and ZLIB. We achieved up to 34x better throughput than the serial CPU implementation of LZSS algorithm and up to 2.21x better than the parallelized version.

关键词： Graphics processing units Instruction sets History Data compression Algorithm design and analysis Encoding Software algorithms

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GPGPU for real-time data analytics

GPGPU for real-time data analytics

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international conference on parallel and distributed systems (ICPADS)

作者： Bingsheng He Huynh Phung Huynh Rick Goh Siow Mong Nanyang Technological University Singapore A*STAR Institute of High Performance Computing Singapore

the demand for real-time data analytics (RTDA) has been on the rise in the past decades and is ever-growing with the proliferation of different data collection *** (General-Purpose computation on Graphics Processing Units) is an emerging research area in HPC (high performance computing). With the massive computation power and high memory bandwidth, GPUs have become a sharp weapon to address the performance requirement of RTDA. Designed as co-processors, GPUs pose a number of technical challenges for RTDA in terms of efficiency and programmability. On the one hand, while new generation GPUs can have over an order of magnitude higher memory bandwidth and higher computation power (in terms of GFLOPS) than CPUs, novel GPGPU algorithmic design and implementation are a must to unleash the hardware power. On the other hand, writing a correct and efficient GPU program is still challenging in general, and even more difficult for RTDA with streaming updates and real-time multi-tasking.

关键词： USA Councils Tutorials Helium Graphics Real-time systems Graphics processing units

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A Demo Paper: An Analytic Workflow Framework for Green Campus

A Demo Paper: An Analytic Workflow Framework for Green Campu...

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international conference on parallel and distributed systems (ICPADS)

作者： Chonho Lee Sivadon Chaisiri Bong Zoebir Changbing Chen Bu-Sung Lee School of Computer Engineering Nanyang Technological University Singapore

this paper proposes a multi-tenant workflow framework that allows users to create data analytic workflows whose tasks are efficiently scheduled and distributed in cloud computing environment. We provide a demo of an event room assignment (ERA) as a test application of the framework. the ERA dynamically and automatically assigns registered events (e.g., meetings, classes, conferences, etc.) to available rooms meeting the user requirements such as the event size, purpose, reservation period, etc. the assignment will lead to the energy efficiency with respect to the power usage (e.g., lighting, ventilation, devices, etc.), and the energy savings can be achieved without affecting people's comfort. We run the ERA with power consumption data (whose size is approximately 50GB) collected from each of over 200 rooms in a building at Dept. of Engineering, Tokyo University. through the demonstration, we will show that the proposed framework accelerates the speed of data analysis by providing user-friendly workflow composition and parallel processing features utilizing cloud computing technologies.

关键词： Power demand XML Real-time systems Computer architecture Educational institutions Cloud computing Buildings

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Enhancing Cloud Object Storage Performance Using Dynamic Replication Approach

Enhancing Cloud Object Storage Performance Using Dynamic Rep...

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international conference on parallel and distributed systems (ICPADS)

作者： Kanatorn Jindarak Putchong Uthayopas HPCNC Kasetsart University Bangkok Thailand

the cloud storage is a new paradigm of data storage. Because of the internet connection speed increasing, everyone can store data on the cloud storage. Some data is shared for many user accesses, some data is private data. It has different characteristic of access pattern. In this work, the adaptive dynamic replication is presented. the model of dynamic replication is discussed. We propose the object-based storage as our cloud storage architecture. the storage object life time is used for handle our dynamic replication mechanism. the experimental results show the distribution of storage object workload that has some characteristic that relate with storage object life time and other factors.

关键词： Servers Cloud computing Educational institutions Computer architecture Aerospace electronics Market research

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