Analyzing network traces to identify long-term high rate flows
In-Koo Kim · 2001
Analyzing Network Traces to Identify Long-Term High Rate Flows. (May 2001) In-koo Kim, B.S., Seoul National University Chair of Advisory Committee: Dr. A. L. Narasimha Reddy In this thesis we look at a scalable way of identifying long-term high rate flows without maintaining per flow state information proportional to the number of flows. Identification of high-rate flows is useful at the time of congestion. This thesis proposes and evaluates a scheme for identifying high-rate flows without explicitly measuring the rates of the flows. Typical Internet trace consists of a large fraction of flows that are ON/OFF in nature. Maintaining state information for every flow is unnecessary and expensive. We observe that this is a situation similar to the cache memory management in that we want to maintain information only on high rate flows (corresponding to frequently referenced data items) using fixed space. We apply the LRU (least recent used) policy in selecting the high rate ows only.