Difference between revisions of "Koushanfar2007"

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|abstract=Distributed wireless systems (DWSs) are emerging as the enabler for next-generation wireless applications. There is a consensus that DWS-based applications, such as pervasive computing, sensor networks, wireless information networks, and speech and data communication networks, will form the backbone of the next technological revolution. Simultaneously, with great economic, industrial, consumer, and scientific potential, DWSs pose numerous technical challenges. Among them, two are widely considered as crucial: autonomous localized operation and minimization of energy consumption. We address the fundamental problem of how to maximize the lifetime of the network using only local information, while preserving network connectivity. We start by introducing the care-free sleep (CS) Theorem that provides provably optimal conditions for a node to go into sleep mode while ensuring that global connectivity is not affected. The CS theorem is the basis for an efficient localized algorithm that decides which nodes will go to into sleep mode and for how long. We have also developed mechanisms for collecting neighborhood information and for the coordination of distributed energy minimization protocols. The effectiveness of the approach is demonstrated using a comprehensive study of the performance of the algorithm over a wide range of network parameters. Another important highlight is the first mathematical and Monte Carlo analysis that establishes the importance of considering nodes within a small number of hops in order to preserve energy.
|abstract=Distributed wireless systems (DWSs) are emerging as the enabler for next-generation wireless applications. There is a consensus that DWS-based applications, such as pervasive computing, sensor networks, wireless information networks, and speech and data communication networks, will form the backbone of the next technological revolution. Simultaneously, with great economic, industrial, consumer, and scientific potential, DWSs pose numerous technical challenges. Among them, two are widely considered as crucial: autonomous localized operation and minimization of energy consumption. We address the fundamental problem of how to maximize the lifetime of the network using only local information, while preserving network connectivity. We start by introducing the care-free sleep (CS) Theorem that provides provably optimal conditions for a node to go into sleep mode while ensuring that global connectivity is not affected. The CS theorem is the basis for an efficient localized algorithm that decides which nodes will go to into sleep mode and for how long. We have also developed mechanisms for collecting neighborhood information and for the coordination of distributed energy minimization protocols. The effectiveness of the approach is demonstrated using a comprehensive study of the performance of the algorithm over a wide range of network parameters. Another important highlight is the first mathematical and Monte Carlo analysis that establishes the importance of considering nodes within a small number of hops in order to preserve energy.
|pages=16 - 16
|pages=16 - 16
|month=
|year=2007
|volume=6
|volume=6
|journal=ACM Transaction on Embedded Computing Systems
|journal=ACM Transaction on Embedded Computing Systems
|title=Techniques for Maintaining Connectivity Ad-hoc Networks Under Energy Constraints
|title=Techniques for Maintaining Connectivity Ad-hoc Networks Under Energy Constraints
|entry=article
|entry=article
|date=2007-20-01
}}
}}

Revision as of 03:33, 4 September 2021

Koushanfar2007
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authorF. Koushanfar and A. Daware and D. Nguyen and M. Potkonjak and A. Sangiovanni-Vincentelli
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journalACM Transaction on Embedded Computing Systems
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pages16 - 16
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titleTechniques for Maintaining Connectivity Ad-hoc Networks Under Energy Constraints
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volume6
year2007
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Email:
farinaz@ucsd.edu
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Address:
Electrical & Computer Engineering
University of California, San Diego
9500 Gilman Drive, MC 0407
Jacobs Hall, Room 6401
La Jolla, CA 92093-0407
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Lab Location: EBU1-2514
University of California San Diego
9500 Gilman Dr, La Jolla, CA 92093