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Entropy has recently gained considerable significance as an important metric for network measurement. Previous research has shown its utility in clustering traffic and detecting traffic anomalies. While measuring the entropy of the traffic observed at a single point has already been studied, an interesting open problem is to measure the entropy of the(More)
This paper addresses the problem of distributed resource allocation in general fork and join processing networks. The problem is motivated by the complicated processing requirements arising from distributed data intensive computing. In such applications, the underlying data processing software consists of a rich set of semantics that include synchronous and(More)
— In today's Internet applications or sensor networks we often encounter large amounts of data spread over many physically distributed nodes. The sheer volume of the data and bandwidth constraints make it impractical to send all the data to one central node for query processing. Finding distributed icebergs—elements that may have low frequency at individual(More)
In this paper, we present an exact active statistics counter architecture called BRICK (Bucketized Rank Indexed Counters) that can efficiently store per-flow variable-width statistics counters entirely in SRAM while supporting both fast updates and lookups (e.g., 40 Gb/s line rates). BRICK exploits statistical multiplexing by randomly bundling counters into(More)
—Bloom filter and its variants have found widespread use in many networking applications. For these applications, minimizing storage cost is paramount as these filters often need to be implemented using scarce and costly (on-chip) SRAM. Besides supporting membership queries, Bloom filters have been generalized to support deletions and the encoding of(More)
The problem of maintaining efficiently a large number (say millions) of statistics counters that need to be updated at very high speeds (e.g. 40 Gb/s) has received considerable research attention in recent years. This problem arises in a variety of router management and data streaming applications where large arrays of counters are used to track various(More)
—Many network processing applications require wire-speed access to large data structures or a large amount of flow-level data, but the capacity of SRAMs is woefully inadequate in many cases. In this paper, we analyze a robust pipelined memory architecture that can emulate an ideal SRAM by guaranteeing with very high probability that the output sequence(More)
—Many emerging information processing applications require applying various fork and join type operations such as correlation, aggregation, and encoding/decoding to data streams in real-time. Each operation will require one or more simultaneous input data streams and produce one or more output streams, where the processing may shrink or expand the data(More)
The problem of efficiently maintaining a large number (say millions) of statistics counters that need to be updated at very high speeds (e.g., 40 Gb/s) has received considerable research attention in recent years. This problem arises in a variety of router management and data streaming applications where large arrays of counters are used to track various(More)
Despite its importance in today's Internet, network measurement was not an integral part of the original Internet architecture , i.e., there was (and still is) little native support for many essential measurement tasks. Targeting the inadequacy of counting/accounting capabilities of existing routers, many data streaming and sketching techniques have been(More)