Approximation Algorithms for Massive High-Rate Data Streams

This paper complements our line of research on effectively and efficiently processing massive high-rate data streams via intelligent compression techniques. In particular, here we provide approximation algorithms adhering to the so-called non-linear data stream compression paradigm. This paradigm demonstrates its feasibility and reliability in the context of emerging data stream applications, such as environmental sensor networks.