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Cloud and Green Computing (CGC), 2012 Second International Conference on

Date 1-3 Nov. 2012

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Displaying Results 1 - 25 of 145
  • [Cover art]

    Page(s): C4
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  • [Title page i]

    Page(s): i
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  • [Title page iii]

    Page(s): iii
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  • [Copyright notice]

    Page(s): iv
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  • Table of contents

    Page(s): v - xiii
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  • Message from the CGC2012 Chairs

    Page(s): xiv
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  • CGC2012 Organizing and Program Committees

    Page(s): xv - xix
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  • Message from the SCA2012 Chairs

    Page(s): xx
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  • SCA2012 Organizing and Program Committees

    Page(s): xxi - xxiv
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  • Message from the WMSC2012 Workshop Chairs

    Page(s): xxv
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  • WMSC2012 Organizing and Program Committees

    Page(s): xxvi
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  • Message from the PriSecCSN2012 Workshop Chairs

    Page(s): xxvii
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  • PriSecCSN2012 Organizing and Program Committees

    Page(s): xxviii
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  • Message from the BigDataMR2012 Workshop Chairs

    Page(s): xxix
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  • BigDataMR2012 Organizing and Program Committees

    Page(s): xxx
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  • SNAIDM2012 Organizing and Program Committees

    Page(s): xxxi
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  • SNAIDM2012 Organizing and Program Committees

    Page(s): xxxii
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  • Message from the WW2012 Workshop Chairs

    Page(s): xxxiii
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  • WW2012 Organizing and Program Committees

    Page(s): xxxiv
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  • Message from the SNSDB2012 Workshop Chairs

    Page(s): xxxv
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  • SNSDB2012 Organizing and Program Committees

    Page(s): xxxvi
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  • An Energy Model for Applications Running on Multicore Systems

    Page(s): 1 - 8
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (194 KB) |  | HTML iconHTML  

    Researchers and developers use energy models to map out what an application or device's energy usage will be. Application developers most often do not have the capability to manipulate the CPU characteristics that most of these energy models and schedules use as their defining aspect. We present an energy model for multiprocess applications that centers around the CPU utilization, which application developers can actively affect with the design of their application. View full abstract»

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  • An Ad-hoc Distributed Reasoning Scheme for Content Centric Networking

    Page(s): 9 - 16
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (250 KB) |  | HTML iconHTML  

    Intelligently discovering knowledge and principles hidden in massive amounts of distributed and dynamic sources is a challenging issue, since the connectivity of sources and mobility of contents are frequent changing. For achieving intelligently discovering knowledge and principles in network environments, it requires a strong adaptive mechanism of distributed reasoning to discover the indirect and dynamic semantics in content-centric networking. In this paper, we propose a novel ad-hoc scheme for distributed reasoning by extending the name-based routing mechanism in content centric networking. The ad-hoc scheme of distributed reasoning is a native process of the content-centric networking. First, a two-stage reasoning mechanism is presented for reasoning query forwarding and knowledge reasoning. And then for guiding original or evolved queries to all right sources and supporting the knowledge integration in the way back, a recursive reasoning procedure and various reasoning rules are introduced. View full abstract»

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  • A General Approach to Service Deployment in Cloud Environments

    Page(s): 17 - 24
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (653 KB) |  | HTML iconHTML  

    The cloud computing landscape has recently developed into a spectrum of cloud architectures, leading to a broad range of management tools for similar operations but specialized for certain deployment scenarios. This both hinders the efficient reuse of algorithmic innovations within cloud management operations and increases the heterogeneity between different management systems. Our overarching goal is to overcome these problems by developing tools general enough to support the full range of popular architectures. In this contribution, we analyze commonalities in recently proposed cloud models (private clouds, multi-clouds, bursted clouds, federated clouds, etc.), and demonstrate how a key management functionality - service deployment - can be uniformly performed in all of these by a carefully designed system. The design of our service deployment framework is validated through a demonstration of how it can be used to deploy services, perform bursting and brokering, as well as mediate a cloud federation in the context of the OPTIMIS Toolkit. View full abstract»

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  • Implementing Smith-Waterman Algorithm with Two-Dimensional Cache on GPUs

    Page(s): 25 - 30
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (215 KB) |  | HTML iconHTML  

    Finding regions of similarity between two data streams is a computational intensive and memory consuming problem, which refers to as sequence alignment for biological sequence. Smith-Waterman algorithm is an optimal method to find the local sequence alignment. It requires a large amount of computation and memory, and is also constrained by the memory access speed when accelerated by using Graphics Processing Units (GPUs). A new method to implement Smith-Waterman algorithm with two-dimensional cache is proposed, which aims at accelerating the first stage of Smith-Waterman algorithm and coalesced writing back the corresponding results to GPU global memory. Our proposal is implemented over NVIDIA Geforce GTX295 GPU, and compared with CUDASW++ 2.0. Experimental results show that our approach outperforms CUDASW++ 2.0 in the datasets chosen from NCBI. View full abstract»

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