Pirates and Samaritans: A Decade of Measurements on Peer Production and their Implications for Net Neutrality and Copyright

This study traces the evolution of commons-based peer production by a measurementbased analysis of case studies and disusses the impact of peer production on net neutrality and copyright law. The measurements include websites such asSuprnova. org, Youtube.com, and Facebook.com, and the Peer-to-Peer (P2P) systems Kazaa, Bittorrent, and Tribler. The measurements show the two sides of peer production, the pirate side with free availability of Hollywood movies on these P2P systems and the samaritan side exhibited by the quick joining of 400,000+ people in a community to organize protests against events in Burma. The telecommunications and content industry are disrupted by this way of peer production. As a consequence, revenues of both industries are likely to suffer in the coming years. On the other hand, innovative P2P systems could win the battle on merit over classical distribution technologies. As a result, a continuation is expected of both legal actions against P2P and possible blocking actions of P2P traffic, violating net neutrality. It is argued that this hinders innovation and causes a large discrepancy between legal and user perspectives. A reform of copyright laws are clearly needed, otherwise they will be unenforceable around 2010. Key words: P2P, collaboration, commons-based peer production, copyright

Design space exploration for providing QoS within the HARMONY framework

ABSTRACT The HARMONY architectur

The distributed ASCI supercomputer project

The Distributed ASCI Supercomputer (DAS) is a homogeneous wide-area distributed system consisting of four cluster computers at different locations. DAS has been used for research on communication software, parallel languages and programming systems, schedulers, parallel applications, and distributed applications. The paper gives a preview of the most interesting research results obtained so far in the DAS project

An Evaluation of the Close-to-Files Processor and Data Co-Allocation Policy in Multiclusters

In multicluster systems, and more generally, in grids, jobs may require co-allocation, i.e., the simultaneous allocation of resources such as processors and input files in multiple clusters. While such jobs may have reduced runtimes because they have access to more resources, waiting for processors in multiple clusters and for the input files to become available in the right locations may introduce inefficiencies. In previous work, we have studied through simulations only processor co-allocation. Here, we extend this work with an analysis of the performance in a real testbed of our prototype Processor and Data Co-Allocator with the Close-to-Files (CF) job-placement algorithm. CF tries to place job components on clusters with enough idle processors which are close to the sites where the input files reside. We present a comparison of the performance of CF and the Worst-Fit job-placement algorithm, with and without file replication, achieved with our prototype. Our most important findings are that CF with replication works best, and that the utilization in our testbed can be driven to about 80%.