Reservoir sampling is a well-known technique for random sampling over data streams. In many streaming applications, however, an input stream may be naturally heterogeneous, i.e., c...
We present deterministic sub-linear space algorithms for a number of problems over update data streams, including, estimating frequencies of items and ranges, finding approximate ...
We study the problem of maintaining a sketch of recent elements of a data stream. Motivated by applications involving network data, we consider streams that are asynchronous, in wh...
There is growing interest in algorithms for processing and querying continuous data streams (i.e., data that is seen only once in a fixed order) with limited memory resources. In ...
Sumit Ganguly, Minos N. Garofalakis, Rajeev Rastog...
We study the problem of finding the k most frequent items in a stream of items for the recently proposed max-frequency measure. Based on the properties of an item, the maxfrequen...