Article

Energy-aware geographic routing in lossy wireless sensor networks with environmental energy supply

Authors:

Patrick J. MoranAuthors Info & Claims

QShine '06: Proceedings of the 3rd international conference on Quality of service in heterogeneous wired/wireless networks

Pages 8 - es

https://doi.org/10.1145/1185373.1185384

Published: 07 August 2006 Publication History

Abstract

Wireless sensor networks are characterized by multihop wireless lossy links and resource constrained nodes. Energy efficiency is a major concern in such networks. In this paper, we study Geographic Routing with Environmental Energy Supply (GREES) and propose two protocols, GREES-L and GREES-M, which combine geographic routing and energy-aware routing techniques and take into account the realistic lossy wireless channel condition and the renewal capability of environmental energy supply when making routing decisions. Simulation results show that GREESs are more energy efficient than the corresponding residual energy based protocols and geographic routing protocols without energy awareness. GREESs can maintain higher mean residual energy on nodes, and achieve better load balancing in terms of having smaller standard deviation of residual energy on nodes. Both GREES-L and GREES-M exhibit graceful degradation on end-to-end delay, but do not compromise the end-to-end throughput performance.

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Cited By

Borhani MAvgouleas ILiyanage MGurtov A(2023)KDC Placement Problem in Secure VPLS NetworksIEEE Transactions on Information Forensics and Security10.1109/TIFS.2023.325444718(1951-1962)Online publication date: 2023
https://doi.org/10.1109/TIFS.2023.3254447
Del-Valle-Soto CRodríguez AAscencio-Piña C(2023)A survey of energy-efficient clustering routing protocols for wireless sensor networks based on metaheuristic approachesArtificial Intelligence Review10.1007/s10462-023-10402-w56:9(9699-9770)Online publication date: 11-Feb-2023
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Koufoudakis GOikonomou KTsoumanis G(2018)Adapting Probabilistic Flooding in Energy Harvesting Wireless Sensor NetworksJournal of Sensor and Actuator Networks10.3390/jsan70300397:3(39)Online publication date: 6-Sep-2018
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Index Terms

Energy-aware geographic routing in lossy wireless sensor networks with environmental energy supply

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Published In

cover image ACM Conferences

QShine '06: Proceedings of the 3rd international conference on Quality of service in heterogeneous wired/wireless networks

August 2006

499 pages

ISBN:1595935371

DOI:10.1145/1185373

General Chair:
Jon Mark
University of Waterloo, Canada

Copyright © 2006 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 07 August 2006

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Cited By

Borhani MAvgouleas ILiyanage MGurtov A(2023)KDC Placement Problem in Secure VPLS NetworksIEEE Transactions on Information Forensics and Security10.1109/TIFS.2023.325444718(1951-1962)Online publication date: 2023
https://doi.org/10.1109/TIFS.2023.3254447
Del-Valle-Soto CRodríguez AAscencio-Piña C(2023)A survey of energy-efficient clustering routing protocols for wireless sensor networks based on metaheuristic approachesArtificial Intelligence Review10.1007/s10462-023-10402-w56:9(9699-9770)Online publication date: 11-Feb-2023
https://doi.org/10.1007/s10462-023-10402-w
Koufoudakis GOikonomou KTsoumanis G(2018)Adapting Probabilistic Flooding in Energy Harvesting Wireless Sensor NetworksJournal of Sensor and Actuator Networks10.3390/jsan70300397:3(39)Online publication date: 6-Sep-2018
https://doi.org/10.3390/jsan7030039
Tan QAn WHan YLuo HLiu YCi STang H(2016)Achieving energy-neutral data transmission by adjusting transmission power for energy-harvesting wireless sensor networksWireless Communications & Mobile Computing10.1002/wcm.266916:14(2083-2097)Online publication date: 10-Oct-2016
https://dl.acm.org/doi/10.1002/wcm.2669
Song JAn WHu YZhang YZhou XXu Z(2015)Balancing harvesting energy consumption with potential field in wireless sensor networks2015 IEEE 26th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)10.1109/PIMRC.2015.7343629(2014-2019)Online publication date: Aug-2015
https://doi.org/10.1109/PIMRC.2015.7343629
Zefreh MTodd T(2014)Energy Provisioning in Green Mesh Networks Using Positional AwarenessIEEE Transactions on Vehicular Technology10.1109/TVT.2012.223658263:8(4064-4076)Online publication date: Oct-2014
https://doi.org/10.1109/TVT.2012.2236582
Kavvadia EKoufoudakis GOikonomou K(2014)Robust probabilistic information dissemination in energy harvesting wireless sensor networks2014 13th Annual Mediterranean Ad Hoc Networking Workshop (MED-HOC-NET)10.1109/MedHocNet.2014.6849106(63-70)Online publication date: Jun-2014
https://doi.org/10.1109/MedHocNet.2014.6849106
Bhunia SDas BMukherjee N(2014)EMCR : Routing in WSN Using Multi Criteria Decision Analysis and Entropy WeightsInternet and Distributed Computing Systems10.1007/978-3-319-11692-1_28(325-334)Online publication date: 2014
https://doi.org/10.1007/978-3-319-11692-1_28
MOON SYOO JKIM JPARK K(2013)MAC Protocol for Energy Efficiency and Service Differentiation with High Goodput in Wireless Sensor NetworksIEICE Transactions on Communications10.1587/transcom.E96.B.1444E96.B:6(1444-1458)Online publication date: 2013
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Dang NBozorgzadeh EVenkatasubramanian N(2012)Energy Harvesting for Sustainable Smart SpacesAdvances in Computers Volume 8710.1016/B978-0-12-396528-8.00006-7(203-251)Online publication date: 2012
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