Low-power wireless sensor networks

By R. Min, Manish Bhardwaj, Seong-Hwan Cho, Eugene Shih, A. Sinha, Alice Wang, Anantha P. Chandrakasan. VLSI Design 2001. Fourteenth International Conference on VLSI Design, 2001

479 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/e9438818358513969aa736917d6af1dd71940b3f

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In Biomedical Engineering

In Computer Networks and Communications

In Electrical and Electronic Engineering

Citations in the corpus

A survey on routing protocols for wireless sensor networks (2005, background): “Such sensors are generally equipped with data processing and communication capabilities.”
A survey on clustering algorithms for wireless sensor networks (2007, background): “Therefore, sensors are expected to be deployed randomly in the area of interest by a relatively uncontrolled means, e.g. dropped by a helicopter, and to collectively form a network in an ad-hoc manner [8,9].”
Network coverage using low duty-cycled sensors: random & coordinated sleep algorithms (2004, background): “This is because switching between on and off states itself consumes energy and adds latency [8].”
Efficient algorithms for maximum lifetime data gathering and aggregation in wireless sensor networks (2003, background): “The recent advances in micro-sensor technology and low-power analog/digital electronics, have led to the development of distributed, wireless networks of sensor devices [11,18,19].”
An efficient clustering-based heuristic for data gathering and aggregation in sensor networks (2003, background): “The recent advances in micro‐sensor technology and low‐power analog/digital electronics, have led to the development of distributed, wireless networks of sensor devices [7], [ 14 ], [15].”
Modelling Data-Centric Routing in Wireless Sensor Networks (2002, background): “Of particular note are UC Berkeley’s Smart Dust Motes [19], TinyOS [16], and the PicoRadio [29] project; the Wireless Integrated Network Sensors (WINS) project [28] and PC-104 based sensors [4] developed at University of California Los Angeles; and the µAMPS project at MIT [ 23 ].”
Protocols for self-organization of a wireless sensor network (2000, background): “Since the network consists solely of mobile nodes, the tasks of routing and mobility within the MANET are generally handled jointly.”
Embedding damage detection algorithms in a wireless sensing unit for operational power efficiency (2004, background): “Other research teams in both academia and industry are producing wireless sensing networks for a variety of applications [8–11].”
Optimal Energy Aware Clustering in Sensor Networks (2002, background): “[1,7,13] emphasize the importance of low power communication, computation and partitioning (clustering) in sensor networks.”
Low energy adaptive clustering hierarchy with deterministic cluster-head selection (2002, background): “Distributed wireless microsensor networks are an important component of the world of Ubiquitous Computing [2],[3].”
The impact of data aggregation in wireless sensor networks (2002, background): “Of particular note are UC Berkeley's Smart Dust Motes [14], TinyOS [12], and the PicoRadio [19] project; the Wireless Integrated Network Sensors (WINS) project [18] and PC-104 based sensors [3] developed at University of California Los Angeles; and the µAMPS project at MIT [16].”
Energy efficient schemes for wireless sensor networks with multiple mobile base stations (2003, background): “Sensor network models considered by most researchers have a single static base station located on the periphery of the sensor network [5], [7], [9], [ 12 ].”