Provided by: Israel Institute of Technology
Topic: Big Data
Date Added: Feb 2010
Low overhead analysis of large distributed data sets is necessary for current data centers and for future sensor networks. In such systems, each node holds some data value, e.g., a local sensor read, and a concise picture of the global system state needs to be obtained. To this end, the authors define the distributed classification problem, in which numerous interconnected nodes compute a classification of their data, i.e., partition these values into multiple collections, and describe each collection concisely.