Distributed Data Clustering in Sensor Networks

Provided by: Springer Healthcare
Topic: Big Data
Format: PDF
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. In resource-constrained environments like sensor networks, this needs to be done without collecting all the data at any location, i.e., in a distributed manner. To this end, the authors address the distributed clustering problem, in which numerous interconnected nodes compute a clustering of their data, i.e., partition these values into multiple clusters, and describe each cluster concisely.

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