Article

An optimization framework for joint sensor deployment, link scheduling and routing in underwater sensor networks

Authors:

M. Mastrogiovanni,

M. ZorziAuthors Info & Claims

WUWNet '06: Proceedings of the 1st International Workshop on Underwater Networks

Pages 56 - 63

https://doi.org/10.1145/1161039.1161051

Published: 25 September 2006 Publication History

Abstract

Underwater sensor networks are a very interesting case of wireless communication in extreme conditions. They exploit acoustic communication in sea water and are nowadays used in surveillance and monitoring applications. These networks present very challenging aspects, such as low data rates and large delays, as well as the special propagation characteristics of the underwater medium. We propose an integer-linear programming approach to jointly optimize routing, link-scheduling and node placement in such a scenario. Accounting for these special aspects of underwater wireless communications leads to re-thinking traditional approaches; this results in original solutions, which highlight novel directions for further research in this area.

References

[1]

Akyildiz, I. F., Pompili, D., and Melodia, T. Underwater acoustic sensor networks: Research challenges. Elsevier's Ad Hoc Networks 3, 3 (May 2005), 257--279.

[2]

Alonso, J., and Fall, K. A linear programming formulation of flows over time with piecewise constant capacity and transit times. TR IRB-TR-03-007, Intel Research, 2003.

[3]

Bhardwaj, M., and Chandrakasan, A. P. Bounding the lifetime of sensor networks via optimal role assignments. In Proc. IEEE INFOCOM (2002), vol. 3, pp. 1587--1596.

[4]

Chang, J.-H., and Tassiulas, L. Maximum lifetime routing in wireless sensor networks. IEEE/ACM ToN 12, 4 (2004), 609--619.

Digital Library

[5]

Codiga, D., Rice, J., and Baxley, P. Networked acoustic modems for real-time data delivery from distributed subsurface instruments in the coastal ocean: Initial system development and performance. J. Atmos. Oceanic Tech. 21, 2 (2004), 331--346.

[6]

GNU. glpk 4.8, 2006. http://www.gnu.org/software/glpk/.

[7]

Gupta, P., and Kumar, P. R. The capacity of wireless networks. IEEE Trans. on Information Theory 46, 2 (2000).

Digital Library

[8]

Jain, K., Padhye, J., Padmanabhan, V. N., and Qiu, L. Impact of interference on multi-hop wireless network performance. In Proc. ACM Mobicom (2003), pp. 66--80.

Digital Library

[9]

Kodialam, M., and Nandagopal, T. Characterizing achievable rates in multi-hop wireless networks: the joint routing and scheduling problem. In Proc. ACM Mobicom (2003), pp. 42--54.

Digital Library

[10]

Kodialam, M., and Nandagopal, T. Characterizing the capacity region in multi-radio multi-channel wireless mesh networks. In Proc. ACM Mobicom (2005), pp. 73--87.

Digital Library

[11]

Kotnyek, B. An annotated overview of dynamic network flows. TR RR-4936, INRIA, 2003.

[12]

Kumar, V. S. A., Marathe, M. V., Parthasarathy, S., and Srinivasan, A. Algorithmic aspects of capacity in wireless networks. In Proc. ACM SIGMETRICS/ (2005), pp. 133--144.

Digital Library

[13]

Lindsey, S., Raghavendra, C., and Sivalingam, K. M. Data gathering algorithms in sensor networks using energy metrics. IEEE TPDS 13, 9 (Sept. 2002), 924--935.

Digital Library

[14]

LinkQuest Inc. Underwater acoustic modems data sheets. Last accessed on July 2006 at http://www.link-quest.com/html/uwm_hr.pdf.

[15]

Madan, R., and Lall, S. Distributed algorithms for maximum lifetime routing in wireless sensor networks. In Proc. IEEE Globecom (2004), pp. 748--753.

[16]

Marina, M. K., and Das, S. R. A topology control approach for utilizing multiple channels in multi-radio wireless mesh networks. In Proc. Broadnets Symposium (2005).

[17]

Singh, S., Woo, M., and Raghavendra, C. S. Power-aware routing in mobile ad hoc networks. In Proc. ACM/IEEE Mobicom (1998), pp. 181--190.

Digital Library

[18]

Sozer, E. M., Stojanovic, M., and Proakis, J. G. Underwater acoustic networks. IEEE Journal of Oceanic Engineering 25 (2000), 72--83.

[19]

Urick, R. J. Principles of Underwater Sound. McGraw-Hill, 1983.

[20]

Wattenhofer, R., Li, L., Bahl, P., and Wang, Y.-M. Distributed topology control for power efficient operation in multihop wireless ad hoc networks. In Proc. ACM/IEEE INFOCOM (2001).

[21]

Yu, Y., Krishnamachari, B., and Prasanna, V. K. Energy-latency tradeoffs for data gathering in wireless sensor networks. In Proc. IEEE INFOCOM (2004), vol. 1.

Cited By

Wang CZhao WBi ZWan Y(2022)A Joint Power Allocation and Scheduling Algorithm Based on Quasi-Interference Alignment in Underwater Acoustic NetworksOCEANS 2022 - Chennai10.1109/OCEANSChennai45887.2022.9775242(1-6)Online publication date: 21-Feb-2022
https://doi.org/10.1109/OCEANSChennai45887.2022.9775242
Guan ZKulhandjian HMelodia T(2021)Stochastic Channel Access in Underwater Networks With Statistical Interference ModelingIEEE Transactions on Mobile Computing10.1109/TMC.2020.299302620:10(3020-3033)Online publication date: 1-Oct-2021
https://dl.acm.org/doi/10.1109/TMC.2020.2993026
Yildiz H(2019)Investigation of maximum lifetime and minimum delay trade‐off in underwater sensor networksInternational Journal of Communication Systems10.1002/dac.392432:7Online publication date: 19-Feb-2019
https://doi.org/10.1002/dac.3924
Show More Cited By

Index Terms

An optimization framework for joint sensor deployment, link scheduling and routing in underwater sensor networks
1. Networks
  1. Network protocols

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Published In

cover image ACM Conferences

WUWNet '06: Proceedings of the 1st International Workshop on Underwater Networks

September 2006

126 pages

ISBN:1595934847

DOI:10.1145/1161039

General Chairs:
Jun-Hong Cui
University of Connecticut
,
Urbashi Mitra
University of Southern California
,
Program Chairs:
Kevin Fall
Intel Research, Berkeley
,
Milica Stojanovic
Massachusetts Institute of Technology

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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Publication History

Published: 25 September 2006

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DIWANS06

Sponsor:

DIWANS06: Workshop on Dependability Issues in Wireless Ad Hoc Networks and Sensor Networks 2006

September 25, 2006

CA, Los Angeles, USA

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Overall Acceptance Rate 84 of 180 submissions, 47%

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Cited By

Wang CZhao WBi ZWan Y(2022)A Joint Power Allocation and Scheduling Algorithm Based on Quasi-Interference Alignment in Underwater Acoustic NetworksOCEANS 2022 - Chennai10.1109/OCEANSChennai45887.2022.9775242(1-6)Online publication date: 21-Feb-2022
https://doi.org/10.1109/OCEANSChennai45887.2022.9775242
Guan ZKulhandjian HMelodia T(2021)Stochastic Channel Access in Underwater Networks With Statistical Interference ModelingIEEE Transactions on Mobile Computing10.1109/TMC.2020.299302620:10(3020-3033)Online publication date: 1-Oct-2021
https://dl.acm.org/doi/10.1109/TMC.2020.2993026
Yildiz H(2019)Investigation of maximum lifetime and minimum delay trade‐off in underwater sensor networksInternational Journal of Communication Systems10.1002/dac.392432:7Online publication date: 19-Feb-2019
https://doi.org/10.1002/dac.3924
Diamant RCasari PCampagnaro FZorzi M(2017)Leveraging the Near–Far Effect for Improved Spatial-Reuse Scheduling in Underwater Acoustic NetworksIEEE Transactions on Wireless Communications10.1109/TWC.2016.264668216:3(1480-1493)Online publication date: 1-Mar-2017
https://dl.acm.org/doi/10.1109/TWC.2016.2646682
Zhang HWang WZhou YWang CFan RXie G(2017)CSMA/CA-based electrocommunication system design for underwater robot groups2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)10.1109/IROS.2017.8206056(2415-2420)Online publication date: 24-Sep-2017
https://dl.acm.org/doi/10.1109/IROS.2017.8206056
Diamant RCasari PZorzi M(2016)A TDMA-based MAC protocol exploiting the near-far effect in underwater acoustic networksOCEANS 2016 - Shanghai10.1109/OCEANSAP.2016.7485470(1-5)Online publication date: Apr-2016
https://doi.org/10.1109/OCEANSAP.2016.7485470
Lmai SChitre MLaot CHoucke S(2015)Throughput-Maximizing Transmission Schedules for Underwater Acoustic Multihop Grid NetworksIEEE Journal of Oceanic Engineering10.1109/JOE.2015.247445540:4(853-863)Online publication date: Oct-2015
https://doi.org/10.1109/JOE.2015.2474455
Rahman RBenson CJiang FFrater M(2013)LOARP: A Low Overhead Routing Protocol for Underwater Acoustic Sensor NetworksJournal of Networks10.4304/jnw.8.2.317-3308:2Online publication date: 1-Feb-2013
https://doi.org/10.4304/jnw.8.2.317-330
Yadav STomar S(2013)A load balanced clustering architecture with two cluster heads2013 Tenth International Conference on Wireless and Optical Communications Networks (WOCN)10.1109/WOCN.2013.6616205(1-5)Online publication date: Jul-2013
https://doi.org/10.1109/WOCN.2013.6616205
Cao JDou JGuo ZDong SXu H(2013)ELTProceedings of the 2013 IEEE 9th International Conference on Mobile Ad-hoc and Sensor Networks10.1109/MSN.2013.73(133-139)Online publication date: 11-Dec-2013
https://dl.acm.org/doi/10.1109/MSN.2013.73
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