Flow Control in ServerNet® Clusters
The Journal of Supercomputing
Flow Control in ServerNetR Clusters
Euro-Par '00 Proceedings from the 6th International Euro-Par Conference on Parallel Processing
On learning to predict web traffic
Decision Support Systems - Special issue: Web data mining
A pattern-based prediction: An empirical approach to predict end-to-end network latency
Journal of Systems and Software
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The management of networks has often been ignored in network-based computing systems due to the difficulty of estimating application programs' network latency and bandwidth requirements, and the difficulty of predicting the system network load. To help address this deficiency, and thereby support dynamic network resource scheduling, we propose the Network Status Predictor (NSP). This tool is a general and extensible network load monitor that introduces lower and upper latency prediction bounds. We evaluate its ability to dynamically predict TCP/IP end-to-end latency with varying network loads using a cluster of SGI multiprocessors interconnected with a Fibre Channel network. Our results show that a combination of numerical predictors can be dynamically selected based on the network's recent state to produce better predictions than when using a single predictor alone.