Power management algorithms for wireless sensor networks
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Lieferung aus: Deutschland, Versandkostenfrei.
Von Händler/Antiquariat, AHA-BUCH GmbH [51283250], Einbeck, Germany.
This item is printed on demand - Print on Demand Neuware - Wireless Sensor Networks (WSN) comprise of highly constrained nodes in terms of processing power, memory, size and most importantly, power is supplied by batteries that are not rechargeable or replaceable. In addition, the nodes have to be self configurable and autonomous thus requiring considerable intelligence. To this end, managing the limited resources of the nodes and the development of low foot print artificial intelligence based agents have been major areas of research. Power Management Algorithms for Wireless Sensor Networks is an in-depth study of artificial intelligence based techniques applicable to these highly constrained network nodes. The algorithms focus on two main areas of power wastage in WSN namely, the transceiver and media access. The author explores a number of environments in which the nodes operate and using sound theory for proof of optimality in combination with empirical work, develop agents that converge on policies that are optimal and able to operate in these highly constrained networks. This book is a major resource for those working in the field of resource management for intelligent autonomous self configuring low power sensor networks. 288 pp. Englisch.

Lieferung aus: Deutschland, Lieferzeit: 5 Tage.
Wireless Sensor Networks (WSN) comprise of highly constrained nodes in terms of processing power, memory, size and most importantly, power is supplied by batteries that are not rechargeable or replaceable. In addition, the nodes have to be self configurable and autonomous thus requiring considerable intelligence. To this end, managing the limited resources of the nodes and the development of low foot print artificial intelligence based agents have been major areas of research. Power Management Algorithms for Wireless Sensor Networks is an in-depth study of artificial intelligence based techniques applicable to these highly constrained network nodes. The algorithms focus on two main areas of power wastage in WSN namely, the transceiver and media access. The author explores a number of environments in which the nodes operate and using sound theory for proof of optimality in combination with empirical work, develop agents that converge on policies that are optimal and able to operate in these highly constrained networks. This book is a major resource for those working in the field of resource management for intelligent autonomous self configuring low power sensor networks.

Lieferung aus: Deutschland, Versandkostenfrei.
Power management algorithms for wireless sensor networks: Wireless Sensor Networks (WSN) comprise of highly constrained nodes in terms of processing power, memory, size and most importantly, power is supplied by batteries that are not rechargeable or replaceable. In addition, the nodes have to be self configurable and autonomous thus requiring considerable intelligence. To this end, managing the limited resources of the nodes and the development of low foot print artificial intelligence based agents have been major areas of research. Power Management Algorithms for Wireless Sensor Networks is an in-depth study of artificial intelligence based techniques applicable to these highly constrained network nodes. The algorithms focus on two main areas of power wastage in WSN namely, the transceiver and media access. The author explores a number of environments in which the nodes operate and using sound theory for proof of optimality in combination with empirical work, develop agents that converge on policies that are optimal and able to operate in these highly constrained networks. This book is a major resource for those working in the field of resource management for intelligent autonomous self configuring low power sensor networks. Englisch, Taschenbuch.

Von Händler/Antiquariat, English-Book-Service Mannheim [1048135], Mannheim, Germany.
This item is printed on demand for shipment within 3 working days.

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