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Distributed Computing Systems Workshops (ICDCSW), 2012 32nd International Conference on

Date 18-21 June 2012

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Displaying Results 1 - 25 of 115
  • [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 - xii
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  • Message from the Workshops Co-Chairs

    Page(s): xiii
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  • Welcome message from the DCPerf 2012 Program Chairs

    Page(s): xiv
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  • DCPerf 2012 Committees

    Page(s): xv - xvi
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  • Welcome message from the PhoneCom 2012 Chairs

    Page(s): xvii
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  • PhoneCom 2012 Committees

    Page(s): xviii
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  • Welcome message from the HotPOST 2012 Chairs

    Page(s): xix
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  • HotPOST 2012 Committees

    Page(s): xx
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  • Welcome message from the WWASN 2012 Chairs

    Page(s): xxi
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  • WWASN 2012 Committees

    Page(s): xxii
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  • Welcome from the CPNS 2012 Chairs

    Page(s): xxiii
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  • CPNS 2012 Committees

    Page(s): xxiv - xxv
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  • Welcome from the ADSN 2012 Chairs

    Page(s): xxvi
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  • ADSN 2012 Committees

    Page(s): xxvii - xxviii
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  • Welcome from the SPCC 2012 Chairs

    Page(s): xxix
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  • SPCC 2012 Committees

    Page(s): xxx
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  • Welcome message from the NFSP 2012 Chairs

    Page(s): xxxi
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  • NFSP 2012 Committees

    Page(s): xxxii
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  • A Comparison Study of Energy Proportionality of Data Center Network Architectures

    Page(s): 1 - 7
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (225 KB) |  | HTML iconHTML  

    Today's data center networks consume a great amount of energy, which significantly aggravates the operational cost of data centers and the carbon footprint. It is an ideal objective for operators to make the power consumption of data center networks proportional to the amount of network loads they carry. To this end, many recent researches are focusing on two representative methods: device-level sleeping technology and network-wide energy aware routing. It is important for operators to understand what effects these energy conservation methods have on improving the network energy proportionality. In the paper, we make a comparison study on the energy proportionality of data center networks, based on regular routing and energy-aware routing. Specifically, we first choose several typical data center network architectures and equalize their network performance. Afterwards, we analyze the maximum power consumption of data center networks without using any energy conservation strategy, and compare their energy proportionality when employing the sleeping technology and energy-aware routing respectively. View full abstract»

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  • Poincaré: A Hyperbolic Data Center Architecture

    Page(s): 8 - 16
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (824 KB) |  | HTML iconHTML  

    Current trends in cloud computing suggest that both large, public clouds and small, private clouds will proliferate in the near future. Operational requirements, such as high bandwidth, dependability and smooth manageability, are similar for both types of clouds and their underlying data center architecture. Such requirements can be satisfied with utilizing fully distributed, low-overhead mechanisms at the algorithm level, and an efficient layer 2 implementation at the practical level. Adding to this, owners of evolving private data centers are in dire need of an incrementally upgradeable architecture which supports a small roll-out and continuous expansion in small quanta. In order to satisfy both requirements, we propose Poincare, a data center architecture inspired by hyperbolic tessellations, which utilizes low-overhead, greedy routing. On one hand, we show that Poincare scales to support large data centers with low diameter, high bisection bandwidth, inherent multipath and multicast capabilities, and efficient error recovery. On the other hand, Poincare supports incremental plug & play upgradability with regard to both servers and switches. View full abstract»

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  • Dynamic Random Access for Hadoop Distributed File System

    Page(s): 17 - 22
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (501 KB) |  | HTML iconHTML  

    Recently, Hadoop Distributed File System (HDFS) has been widely used to manage the large-scale data due to its high scalability. HDFS can natively support sequential queries, which are the most common queries in the applications. However, there still exist many applications that need to apply random queries of large-scale data. So the random queries in large-scale data are becoming more and more important. Unfortunately, the HDFS is not optimized for random reads, hence there are many disadvantages in random access to HDFS. In this paper, we present three methods to solve these issues, which can optimize the random accesses to HDFS and guarantee the sequential access performance at the same time. The methods are as follows: 1) proposing dynamic methods to set the size of data packet in transmission, 2) reusing the TCP connections in localized random accesses, 3) transferring the random accesses to the same server to make full use of the TCP connections. Experimental evaluations based on real world data show that our works are effective and our solutions efficiently support sequential access and random access compared to the original methods. View full abstract»

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