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检索条件"任意字段=2nd IEEE International Conference on Cloud Computing Technology and Science, CloudCom 2010"

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Xenrelay: An efficient data transmitting approach for tracing guest domain

Xenrelay: An efficient data transmitting approach for tracin...

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2nd ieee international conference on cloud computing technology and science, cloudcom 2010

作者： Jin, Hai Cao, Wenzhi Yuan, Pingpeng Xie, Xia Cluster and Grid Computing Lab. Services Computing Technique and System Lab. Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780769543024

As the degree of virtualization is growing considerably, improving performance of virtual machine environments motivates deeper investigation of the internal processes and performance implications of virtualization. Several tools are currently available to help analyze performance in virtual machine environments. However, all of these cannot support users to add their own trace information. In this paper, we present Xenrelay, a unified, efficient, and simple mechanism for transferring large amounts of data from guest domain kernel to privileged domain user-space. Xenrelay allows users (who trace subsystems of guest domain to analyze performance) to record and fast relay data between domains. We provide a case of Xenrelay's value in revealing behavior of virtualization. We build a block trace toolkit (using Xenrelay as an engine). This toolkit is used to track the block I/O virtualization procedures and evaluates overheads in the Xen environment. Our trace results identify that the main delay is the time of request transmission and block device operation. Besides, the results reveal impact of the I/O schedules on the disk performance. © 2010 ieee.

关键词： Virtualization

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Security services lifecycle management in on-demand infrastructure services provisioning

Security services lifecycle management in on-demand infrastr...

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2nd ieee international conference on cloud computing technology and science, cloudcom 2010

作者： Demchenko, Yuri De Laat, Cees Lopez, Diego R. García-Espín, Joan A. System and Network Engineering Group University of Amsterdam Netherlands RedIRIS Spain I2CAT Foundation Spain

ISBN: (纸本)9780769543024

Modern e-science and high technology industry require high-performance and complicated network and computer infrastructure to support distributed collaborating groups of researchers and applications that should be provisioned on-demand. The effective use and management of the dynamically provisioned services can be achieved by using the Service Delivery Framework (SDF) proposed by TeleManagement Forum that provides a good basis for defining the whole services life cycle management and supporting infrastructure services. The paper discusses conceptual issues, basic requirements and practical suggestions for provisioning consistent security services as a part of the general e-science infrastructure provisioning, in particular Grid and cloud based. The proposed Security Services Lifecycle Management (SSLM) model extends the existing frameworks with additional stages such as "Reservation Session Binding" and "Registration and Synchronisation" that specifically target such security issues as the provisioned resources restoration, upgrade or migration and provide a mechanism for remote executing environment and data protection by binding them to the session context. The paper provides a short overview of the existing standards and technologies and refers to the ongoing projects and experience in developing dynamic distributed security services. © 2010 ieee.

关键词： e-science

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The two quadrillionth bit of Pi is 0! Distributed computation of Pi with Apache Hadoop

The two quadrillionth bit of Pi is 0! Distributed computatio...

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2nd ieee international conference on cloud computing technology and science, cloudcom 2010

作者： Sze, Tsz-Wo Yahoo Cloud Computing Sunnyvale CA United States

ISBN: (纸本)9780769543024

We present a new record on computing specific bits of Pi, the mathematical constant, and discuss performing such computations on Apache Hadoop clusters. The specific bits represented in hexadecimal are 0E6C1294 AED40403 F56D2D76 4026265B CA98511D 0FCFFAA1 0F4D28B1 BB5392B8. These 256 bits end at the 2,000,000,000,000,252nd bit position†, which doubles the position and quadruples the precision of the previous known record [12]. The position of the first bit is 1,999,999,999,999,997 and the value of the two quadrillionth bit is 0. The computation is carried out by a MapReduce program called DistBbp. To effectively utilize available cluster resources without monopolizing the whole cluster, we develop an elastic computation framework that automatically schedules computation slices, each a DistBbp job, as either map-side or reduce-side computation based on changing cluster load condition. We have calculated Pi at varying bit positions and precisions, and one of the largest computations took 23 days of wall clock time and 503 years of CPU time on a 1000-node cluster. © 2010 ieee.

关键词： Computer software

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Hybrid map task scheduling for GPU-based heterogeneous clusters

Hybrid map task scheduling for GPU-based heterogeneous clust...

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2nd ieee international conference on cloud computing technology and science, cloudcom 2010

作者： Shirahata, Koichi Sato, Hitoshi Matsuoka, Satoshi Tokyo Institute of Technology Japan CREST Japan Science and Technology Agency Japan National Institute of Informatics Japan

ISBN: (纸本)9780769543024

MapReduce is a programming model that enables efficient massive data processing in large-scale computing environments such as supercomputers and clouds. Such large-scale computers employ GPUs to enjoy its good peak performance and high memory bandwidth. Since the performace of each job is depending on running application characteristics and underlying computing environments, scheduling MapReduce tasks onto CPU cores and GPU devices for efficient execution is difficult. To address this problem, we have proposed a hybrid scheduling technique for GPU-based computer clusters, which minimizes the execution time of a submitted job using dynamic profiles of Map tasks running on CPU cores and GPU devices. We have implemented a prototype of our proposed scheduling technique by extending MapReduce framework, Hadoop. We have conducted some experiments for this prototype by using a K-means application as a benchmark on a supercomputer. The results show that the proposed technique achieves 1.93 times faster than the Hadoop original scheduling algorithm at 64 nodes (1024 CPU cores and 128 GPU devices). The results also indicate that the performance of map tasks, including both CPU and GPU tasks, is significantly affected by the overhead of map task invocation in the Hadoop framework. © 2010 ieee.

关键词： MapReduce

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elasticLM: A novel approach for software licensing in distributed computing infrastructures

elasticLM: A novel approach for software licensing in distri...

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2nd ieee international conference on cloud computing technology and science, cloudcom 2010

作者： Cacciari, Claudio D'Andria, Francesco Gozalo, Miriam Hagemeier, Björn Mallmann, Daniel Martrat, Josep Peréz, David García Rumpl, Angela Ziegler, Wolfgang Zsigri, Csilla CINECA 40033 Casalecchio di Reno Italy Atos Origin - Research and Innovation Barcelona 08011 Spain Gridcore AB Göteborg 411 33 Sweden Forschungszentrum Jülich GmbH 52428 Jülich Germany Foundation CESGA Santiago de Compostela 15705 Spain Fraunhofer Institute SCAI 53754 Sankt-Augustin Germany 451 Group London WC1E6HH United Kingdom

ISBN: (纸本)9780769543024

A recent survey of the 451group on cloud usage highlights software licensing as one of the top five obstacles for cloud computing, quite similar to what has been observed in the Grid already a couple of years. The reasons are the same: the current praxis of software licensing, both in terms of business models and licensing technology. As a consequence, using commercial applications that require access to a license server for authorisation at run-time has been quite limited until recently in distributed computing environments, especially when the environment stretches across administrative domains like it is the case for public clouds. In this paper we present a novel approach for managing software licenses as web service resources in distributed service oriented environments. Licenses become mobile objects, which may move to the environment where required to authorise the execution of a license protected application. © 2010 ieee.

关键词： Web services

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cloudSEC: A cloud architecture for composing collaborative security services

CloudSEC: A cloud architecture for composing collaborative s...

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2nd ieee international conference on cloud computing technology and science, cloudcom 2010

作者： Xu, Jia Yan, Jia He, Liang Su, Purui Feng, Dengguo State Key Laboratory of Information Security Institute of Software Chinese Academy of Sciences Beijing China State Key Laboratory of Information Security Graduate Unversity Chinese Academy of Sciences Beijing China

ISBN: (纸本)9780769543024

Massive Internet invasions implemented through the distributed platform fabricated by rapid diffusion of malwares, has become a significant issue in network security. We argue that the notion of "Collaborative Security" is an emerging trend in resisting distributed attacks originated from malware. Therefore, this paper proposes a new architecture: cloudSEC, for composing collaborative security-related services in clouds, such as correlated intrusion analysis, anti-spam, anti-DDOS, automated malware detection and containment. cloudSEC is modeled as a dynamic peer-to-peer overlay hierarchy with three types of top-down architectural components. Based on this architecture, both data distribution and task scheduling overlays can be simultaneously implemented in a loosely coupled fashion, which can efficiently retrieve data resources from heterogeneous network security facilities, and harness distributed collection of computational resources to process data-intensive tasks. Hence, cloudSEC endues the network security infrastructure with the capability of dynamic adaptation and collaboration on an inter-organizational scale. The results of preliminary evaluation demonstrate that, cloudSEC not only delivers a sample service of distributed intrusion correlation with high scalability and robustness, but also achieves remarkable effectiveness in data sharing and task scheduling. © 2010 ieee.

关键词： cloud computing architecture

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Fine-grained data access control systems with user accountability in cloud computing

Fine-grained data access control systems with user accountab...

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2nd ieee international conference on cloud computing technology and science, cloudcom 2010

作者： Li, Jin Zhao, Gansen Chen, Xiaofeng Xie, Dongqing Rong, Chunming Li, Wenjun Tang, Lianzhang Tang, Yong School of Computer Science and Educational Software Guangzhou University China School of Computer Science South China Normal University China Key Laboratory of Computer Networks and Information Security Xidian University China Dept. of Electrical Engineering and Computer Science Stavenger University Norway School of Software Sun Yat-sen University China

ISBN: (纸本)9780769543024

cloud computing is an emerging computing paradigm in which IT resources and capacities are provided as services over the Internet. Promising as it is, this paradigm also brings forth new challenges for data security and access control when users outsource sensitive data for sharing on cloud servers, which are likely outside of the same trust domain of data owners. To maintain the confidentiality of sensitive user data against untrusted servers, existing work usually apply cryptographic methods by disclosing data decryption keys only to authorized users. However, in doing so, these solutions inevitably introduce heavy computation overhead on the data owner for key distribution and data management when fine-grained data access control is desired, and thus do not scale well. In this paper, we present a way to implement scalable and fine-grained access control systems based on attribute-based encryption (ABE). For the purpose of secure access control in cloud computing, the prevention of illegal key sharing among colluding users is missing from the existing access control systems based on ABE. This paper addresses this challenging open issue by defining and enforcing access policies based on data attributes and implementing user accountability by using traitor tracing. Furthermore, both the user grant and revocation are efficiently supported by using the broadcast encryption technique. Extensive analysis shows that the proposed scheme is highly efficient and provably secure under existing security models. © 2010 ieee.

关键词： Access control

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LEEN: Locality/fairness-aware key partitioning for MapReduce in the cloud

LEEN: Locality/fairness-aware key partitioning for MapReduce...

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2nd ieee international conference on cloud computing technology and science, cloudcom 2010

作者： Ibrahim, Shadi Jin, Hai Lu, Lu Wu, Song He, Bingsheng Qi, Li Cluster and Grid Computing Lab Services Computing Technology and System Lab Huazhong University of Science and Technology Wuhan 430074 China School of Computer Engineering Nanyang Technological University Singapore 639798 Singapore Information and Technology Department China Development Bank Beijing 100037 China

ISBN: (纸本)9780769543024

This paper investigates the problem of Partitioning Skew1 in MapReduce-based system. Our studies with Hadoop, a widely used MapReduce implementation, demonstrate that the presence of partitioning skew causes a huge amount of data transfer during the shuffle phase and leads to significant unfairness on the reduce input among different data nodes. As a result, the applications experience performance degradation due to the long data transfer during the shuffle phase along with the computation skew, particularly in reduce phase. We develop a novel algorithm named LEEN for locality-aware and fairness-aware key partitioning in MapReduce. LEEN embraces an asynchronous map and reduce scheme. All buffered intermediate keys are partitioned according to their frequencies and the fairness of the expected data distribution after the shuffle phase. We have integrated LEEN into Hadoop-0.18.0. Our experiments demonstrate that LEEN can efficiently achieve higher locality and reduce the amount of shuffled data. More importantly, LEEN guarantees fair distribution of the reduce inputs. As a result, LEEN achieves a performance improvement of up to 40% on different workloads. © 2010 ieee.

关键词： MapReduce

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Military Reconstructive Simulation in the cloud to Aid Battlefield Excavations

Military Reconstructive Simulation in the Cloud to Aid Battl...

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4th ieee international conference on cloud computing technology and science (cloudcom)

作者： Wittek, Peter Rubio-Campillo, Xavier Univ Boras Swedish Sch Lib & Informat Sci Boras Sweden Barcelona Supercomp Ctr Comp Appl Sci & Engn Barcelona Spain

ISBN: (纸本)9781467345101;9781467345118

Archaeological studies on battlefields may see great benefits from simulated military engagements: simulations help testing hypotheses based on historical data and may also help with validating methodologies used on the site. Such methods, however, require high-performance computing expertise and considerable computational power. With the emergence of on-demand computing instances in the cloud, distributed computations have become available to technically every organization or individual. This puts large-scale battlefield simulations within the reach of archaeologists, and the cloud paradigm also lowers the required technological expertise, potentially leading to a more widespread adoption of such simulation methods.

关键词： cloud computing Computer Assisted Archaeology Battlefield Archaeology Military Simulation

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Finding tropical cyclones on a cloud computing cluster: Using parallel virtualization for large-scale climate simulation analysis

Finding tropical cyclones on a cloud computing cluster: Usin...

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2nd ieee international conference on cloud computing technology and science, cloudcom 2010

作者： Hasenkamp, D. Sim, A. Wehner, M. Wu, K. Lawrence Berkeley National Laboratory United States

ISBN: (纸本)9780769543024

Extensive computing power has been used to tackle issues such as climate changes, fusion energy, and other pressing scientific challenges. These computations produce a tremendous amount of data;however, many of the programs used to analyze this data currently only run a single processor. In this work, we explore the possibility of using the emerging cloud computing platform to parallelize such sequential data analysis tasks. As a proof of concept, we wrap a program for analyzing trends of tropical cyclones in a set of virtual machines (VMs). This approach allows the user to keep their familiar data analysis environment in the VMs, while we provide the coordination and data transfer services to ensure the necessary input and output are directed to the desired locations. This work extensively exercises the networking capability of the cloud computing systems and has revealed a number of weaknesses in the current cloud system software. In our tests, we are able to scale the parallel data analysis job to a modest number of VMs and achieve a speedup that is comparable to running the same analysis task using MPI. However, compared to MPI based parallelization, the cloud-based approach has a number of advantages. The cloud-based approach is more flexible because the VMs can capture arbitrary software dependencies without requiring the user to rewrite their programs. The cloud-based approach is also more resilient to failure;as long as a single VM is running, it can make progress while as soon as one MPI node fails the whole analysis job fails. In short, this initial work demonstrates that a cloud computing system is a viable platform for distributed scientific data analyses traditionally conducted on dedicated supercomputing systems.

关键词： Virtual machine

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