Low power signal processing architectures for network microsensors

Abstract

Low power signal processing systems are required for distributed network microsensor technology.Network microsensors now provide a new monitoring and control capability for civil and military applications in transportation, manufacturing, biomedical technology, environmental management, and safety and security systems. Signal processing methods for event detection have been developed with low power, parallel architectures that optimize performance for unique sensor system requirements. Implementation of parallel datapatbs with shared arithmetic elements enables high throughput at low clock rate. This method has been used to implement a microsensor spectrum analyzer for a 200 sample/s measurement system. This 0.8p CMOS device operates with a 1M drain current at a 3V supply bias.

Review on Clustering and Data Aggregation in Wireless Sensor Network

“…Data travels from a lower clustered layer to a higher one. Data still hops from one node to another, but since it hops from one layer to another it covers larger distances and moves the data faster to the base station than in the multi hop model [17], [18], [19], [20].…”

An efficient multi-level clustering approach for a heterogeneous wireless sensor network using link correlation

“…Due to the recent technology advancement, the sensor nodes are available in a very low cost [2,3]. In WSN, these lowcost sensor nodes are deployed in large numbers either regularly or randomly.…”

Energy Saving in Wireless Sensor Networks

“…Recent advances in micro-electro-mechanical systems (MEMS), low power and highly integrated digital electronics have led to the development of micro sensors [1,17]. A wireless sensor network consists of sensor nodes deployed over a geographical area for monitoring physical phenomena like temperature, humidity, vibrations, seismic events, and so on [2].…”