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 in | Intelligent Sensor Networks pp. 115 - 152 |
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Main Author | |
Format | Book Chapter |
Language | English |
Published |
CRC Press
2013
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Edition | 1 |
Subjects | |
Online Access | Get full text |
ISBN | 1138199745 9781439892817 1439892814 9781138199743 |
DOI | 10.1201/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. |
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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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DOI | 10.1201/b14300-7 |
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DocumentTitleAlternate | Intelligent Sensor-to-Mission Assignment |
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Editor | Hao, Qi Hu, Fei |
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EndPage | 152 |
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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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