Authors:
Paul Cotofrei
;
Ionel Tudor Calistru
and
Kilian Stoffel
Affiliation:
University of Neuchatel, Switzerland
Keyword(s):
Sensor Networks, Semantic Sensor Web, Network Topology, Energy-aware Routing, Routing protocols, Data Mining, Clustering, DBSCAN.
Related
Ontology
Subjects/Areas/Topics:
Architectural Concepts
;
Artificial Intelligence
;
Biomedical Engineering
;
Business Analytics
;
Data Engineering
;
Data Management and Quality
;
Data Mining
;
Databases and Information Systems Integration
;
Datamining
;
Enterprise Information Systems
;
Health Information Systems
;
Management of Sensor Data
;
Sensor Networks
;
Signal Processing
;
Soft Computing
Abstract:
Sensor networks are a primary source of massive amounts of data about the real world that surrounds us, measuring a wide range of physical parameters in real time. Given the hardware limitations and physical environment in which the sensors must operate, along with frequent changes of network topology, algorithms and protocols must be designed to provide a robust and energy efficient communications mechanism. With a view to addressing these constraints, this paper proposes a routing technique that is based on density based spatial clustering of applications with noise (DBSCAN) algorithm. This technique reveals several network topology semantics, enables the splitting of sensors responsibilities (communication/routing and sensing/monitoring), reduces the level of energy wasted on sending messages through the network by data aggregation only in cluster-head nodes and last but not the least, brings along very good results prolonging the network lifetime.