Intelligent Sensor-to-Mission Assignment

This discusses the sensor-mission assignment problems in the presence of different constraints. It considers the problem of assigning directional sensors to missions in wireless sensor networks. As energy is a critical resource in wireless sensor networks, the chapter discusses an energy-aware exten...

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Published inIntelligent Sensor Networks pp. 115 - 152
Main Author Rowaihy, Hosam
Format Book Chapter
LanguageEnglish
Published CRC Press 2013
Edition1
Subjects
Online AccessGet full text
ISBN1138199745
9781439892817
1439892814
9781138199743
DOI10.1201/b14300-7

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Abstract This discusses the sensor-mission assignment problems in the presence of different constraints. It considers the problem of assigning directional sensors to missions in wireless sensor networks. As energy is a critical resource in wireless sensor networks, the chapter discusses an energy-aware extension to the distributed algorithm that extends network lifetime. The chapter also discusses an energy-aware extension to the dynamic algorithm that helps in prolonging the network lifetime. The periodic updates increase the communication overhead, but as is shown in the following section, this increase is very high. The use of analogy in problem solving allows an intelligent system to connect different knowledge domains via method, strategy, or context to an unfamiliar problem. While the study of sensor network design for the state estimation problem is fairly widespread, their use in distributed, large-scale systems for managing complexity and uncertainty, as well as real-time decentralized control and monitoring is seen as an increasingly important avenue of research.
AbstractList This discusses the sensor-mission assignment problems in the presence of different constraints. It considers the problem of assigning directional sensors to missions in wireless sensor networks. As energy is a critical resource in wireless sensor networks, the chapter discusses an energy-aware extension to the distributed algorithm that extends network lifetime. The chapter also discusses an energy-aware extension to the dynamic algorithm that helps in prolonging the network lifetime. The periodic updates increase the communication overhead, but as is shown in the following section, this increase is very high. The use of analogy in problem solving allows an intelligent system to connect different knowledge domains via method, strategy, or context to an unfamiliar problem. While the study of sensor network design for the state estimation problem is fairly widespread, their use in distributed, large-scale systems for managing complexity and uncertainty, as well as real-time decentralized control and monitoring is seen as an increasingly important avenue of research.
Author Rowaihy, Hosam
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Copyright 2013 by Taylor & Francis Group, LLC
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Hu, Fei
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Keywords Mission Leader
Sensor Networks
Greedy Algorithm
Centralized Algorithm
Communication Overhead
Wireless Sensor Networks
Optimal Fractional Solution
Missions Arrive
Nearby Sensors
Arrival Rate
Sensor Assignment
LP Relaxation
Assignment Decisions
Gap
Mission Profit
Success Threshold
Cognitive Wireless Sensor Networks
Network Lifetime
Online Algorithm
Intelligent Sensor Networks
Proposal Algorithm
Sensing Resources
Target Lifetime
Mission’s Demand
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PublicationSubtitle The Integration of Sensor Networks, Signal Processing and Machine Learning
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