Congestion avoidance and control
SIGCOMM '88 Symposium proceedings on Communications architectures and protocols
The grid
Towards Network-Aware Data Mining
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
The Integrated Delivery of Large-Scale Data Mining: The ACSys Data Mining Project
Revised Papers from Large-Scale Parallel Data Mining, Workshop on Large-Scale Parallel KDD Systems, SIGKDD
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With the emergence of high performance networks, clusters of workstations can now be connected by commodity networks (meta-clusters) or high speed networks (super-clusters) such as the very high speed Backbone Network Service (vBNS) or Internet2's Abilene. Distributed clusters are enabling a new class of data mining applications in which large amounts of data can be transferred using high performance networks and statistically and numerically intensive computations can be done using clusters of workstations. In this paper, we briefly describe a protocol called the Data Space Transfer Protocol (DSTP) for distributed data mining. With high performance networks, it becomes possible to move large amounts of data for certain queries when necessary. This paper describes the design of a high performance DSTP data server called Osiris which is designed to efficiently satisfy data requests for distributed data mining queries. In particular, we describe 1) Osiris's ability to lay out data by row or by column, 2) a scheduler intended to handle requests using standard network links and requests using network links enjoying some type of premium service, and 3) a mechanism designed to hide latency.