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	<title>ClusterCenter RSS Feed: distributed</title>
	<link>http://clustercenter.org</link>
	<description>Pligg Web 2.0 Content Management System</description>
	<pubDate>Tue, 24 Feb 2009 10:12:23 CST</pubDate>
	<language>en</language>
	<item>
		<title><![CDATA[Using the Cloud to build highly-efficient systems - All Things Distributed]]></title>
		<link>http://clustercenter.org/loadbalancing/Using-Cloud-to-build-highly-efficient-systems--All-Things-Distributed/</link>
		<comments>http://clustercenter.org/loadbalancing/Using-Cloud-to-build-highly-efficient-systems--All-Things-Distributed/</comments>
		<pubDate>Tue, 24 Feb 2009 10:12:23 CST</pubDate>
		<dc:creator>wensong</dc:creator>
		<category>loadbalancing</category>
		<guid>http://clustercenter.org/loadbalancing/Using-Cloud-to-build-highly-efficient-systems--All-Things-Distributed/</guid>
		<description><![CDATA[Werner Vogels, CTO of Amazon.com, explained clearly why the Cloud is used to build highly-efficient systems.&quot;By using infrastructure as a service, basic IT costs are moved from a capital expense  ]]></description>
	</item>

	<item>
		<title><![CDATA[The Chubby Lock Service for Loosely-Coupled Distributed Systems]]></title>
		<link>http://clustercenter.org/software/Chubby-Lock-Service-Loosely-Coupled-Distributed-Systems/</link>
		<comments>http://clustercenter.org/software/Chubby-Lock-Service-Loosely-Coupled-Distributed-Systems/</comments>
		<pubDate>Tue, 05 Feb 2008 11:55:46 CST</pubDate>
		<dc:creator>wensong</dc:creator>
		<category>software</category>
		<guid>http://clustercenter.org/software/Chubby-Lock-Service-Loosely-Coupled-Distributed-Systems/</guid>
		<description><![CDATA[We describe our experiences with the Chubby lock service, which is intended to provide coarse-grained locking as well as reliable (though low-volume) storage for a loosely-coupled distributed system. ]]></description>
	</item>

	<item>
		<title><![CDATA[Google Scalability Conference Trip Report: GFS, MapReduce, and BigTable]]></title>
		<link>http://clustercenter.org/architecture/Google-Scalability-Conference-Trip-Report-GFS-MapReduce-BigTable/</link>
		<comments>http://clustercenter.org/architecture/Google-Scalability-Conference-Trip-Report-GFS-MapReduce-BigTable/</comments>
		<pubDate>Thu, 29 Nov 2007 00:41:50 CST</pubDate>
		<dc:creator>wensong</dc:creator>
		<category>architecture</category>
		<guid>http://clustercenter.org/architecture/Google-Scalability-Conference-Trip-Report-GFS-MapReduce-BigTable/</guid>
		<description><![CDATA[In a blog post, Microsoft's Dare Obasanjo shared his notes from the keynote session MapReduce, BigTable, and Other Distributed System Abstractions for Handling Large Datasets by Jeff Dean.rnrnThe ]]></description>
	</item>

	<item>
		<title><![CDATA[Hbase: Bigtable-like structured storage for Hadoop HDFS]]></title>
		<link>http://clustercenter.org/software/Hbase-Bigtable-like-structured-storage-Hadoop-HDFS/</link>
		<comments>http://clustercenter.org/software/Hbase-Bigtable-like-structured-storage-Hadoop-HDFS/</comments>
		<pubDate>Sat, 17 Nov 2007 12:55:53 CST</pubDate>
		<dc:creator>wensong</dc:creator>
		<category>software</category>
		<guid>http://clustercenter.org/software/Hbase-Bigtable-like-structured-storage-Hadoop-HDFS/</guid>
		<description><![CDATA[Google's Bigtable, a distributed storage system for structured data, is a very effective mechanism for storing very large amounts of data in a distri ]]></description>
	</item>

	<item>
		<title><![CDATA[Bigtable: A Distributed Storage System for Structured Data]]></title>
		<link>http://clustercenter.org/storage/Bigtable-Distributed-Storage-System-Structured-Data-1/</link>
		<comments>http://clustercenter.org/storage/Bigtable-Distributed-Storage-System-Structured-Data-1/</comments>
		<pubDate>Sun, 04 Nov 2007 23:44:15 CST</pubDate>
		<dc:creator>wensong</dc:creator>
		<category>storage</category>
		<guid>http://clustercenter.org/storage/Bigtable-Distributed-Storage-System-Structured-Data-1/</guid>
		<description><![CDATA[Bigtable is a distributed storage system for managing structured data that is designed to scale to a very large size: petabytes of data across thousa ]]></description>
	</item>

	<item>
		<title><![CDATA[The Google File System]]></title>
		<link>http://clustercenter.org/storage/Google-File-System/</link>
		<comments>http://clustercenter.org/storage/Google-File-System/</comments>
		<pubDate>Mon, 22 Oct 2007 00:16:31 CST</pubDate>
		<dc:creator>wensong</dc:creator>
		<category>storage</category>
		<guid>http://clustercenter.org/storage/Google-File-System/</guid>
		<description><![CDATA[The Google File System is a scalable distributed file system for large distributed data-intensive applications. It provides fault tolerance while run ]]></description>
	</item>

	<item>
		<title><![CDATA[Hadoop: a distributed computing platform]]></title>
		<link>http://clustercenter.org/software/Hadoop-distributed-computing-platform/</link>
		<comments>http://clustercenter.org/software/Hadoop-distributed-computing-platform/</comments>
		<pubDate>Thu, 04 Oct 2007 13:42:26 CST</pubDate>
		<dc:creator>wensong</dc:creator>
		<category>software</category>
		<guid>http://clustercenter.org/software/Hadoop-distributed-computing-platform/</guid>
		<description><![CDATA[Hadoop is a software platform that lets one easily write and run applications that process vast amounts of data.rnrnHere's what makes Hadoop esp ]]></description>
	</item>

	<item>
		<title><![CDATA[MapReduce: Simplified Data Processing on Large Clusters]]></title>
		<link>http://clustercenter.org/software/MapReduce-Simplified-Data-Processing-on-Large-Clusters/</link>
		<comments>http://clustercenter.org/software/MapReduce-Simplified-Data-Processing-on-Large-Clusters/</comments>
		<pubDate>Wed, 25 Apr 2007 10:22:54 CST</pubDate>
		<dc:creator>zhaofu</dc:creator>
		<category>software</category>
		<guid>http://clustercenter.org/software/MapReduce-Simplified-Data-Processing-on-Large-Clusters/</guid>
		<description><![CDATA[MapReduce is a programming model and an associated implementation for processing and generating large data sets. Users specify a map function that pr ]]></description>
	</item>

	<item>
		<title><![CDATA[LiveJournal's Backend: A history of scaling]]></title>
		<link>http://clustercenter.org/loadbalancing/LiveJournals-Backend-history-scaling/</link>
		<comments>http://clustercenter.org/loadbalancing/LiveJournals-Backend-history-scaling/</comments>
		<pubDate>Sat, 17 Mar 2007 09:34:46 CST</pubDate>
		<dc:creator>wensong</dc:creator>
		<category>loadbalancing</category>
		<guid>http://clustercenter.org/loadbalancing/LiveJournals-Backend-history-scaling/</guid>
		<description><![CDATA[Brad Fitzpatrick, President and CTO of LiveJournal.com, has a very good presentation about LiveJournal's backend systems. The presentation has 80 sli ]]></description>
	</item>

	<item>
		<title><![CDATA[InfoQ: 
		
    	Introduction to OpenTerracotta]]></title>
		<link>http://clustercenter.org/loadbalancing/InfoQ------Introduction-to-OpenTerracotta/</link>
		<comments>http://clustercenter.org/loadbalancing/InfoQ------Introduction-to-OpenTerracotta/</comments>
		<pubDate>Mon, 05 Mar 2007 22:24:03 CST</pubDate>
		<dc:creator>wensong</dc:creator>
		<category>loadbalancing</category>
		<guid>http://clustercenter.org/loadbalancing/InfoQ------Introduction-to-OpenTerracotta/</guid>
		<description><![CDATA[OpenTerracotta is an open source enterprise-class JVM clustering solution that can take multi-threaded single-JVM apps and have them run across multi ]]></description>
	</item>

	<item>
		<title><![CDATA[InfoQ: Distributed Caching Essential Lessons]]></title>
		<link>http://clustercenter.org/caching/InfoQ-Distributed-Caching-Essential-Lessons/</link>
		<comments>http://clustercenter.org/caching/InfoQ-Distributed-Caching-Essential-Lessons/</comments>
		<pubDate>Sun, 04 Mar 2007 19:43:03 CST</pubDate>
		<dc:creator>wensong</dc:creator>
		<category>caching</category>
		<guid>http://clustercenter.org/caching/InfoQ-Distributed-Caching-Essential-Lessons/</guid>
		<description><![CDATA[In this presentation, recorded at Javapolis, Cameron Purdy shows how to improve application performance &amp; scalability via caching architectures to re ]]></description>
	</item>

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