research-article

Reliable data delivery in large-scale low-power sensor networks

Authors:

Daniele Puccinelli,

Martin HaenggiAuthors Info & Claims

ACM Transactions on Sensor Networks (TOSN), Volume 6, Issue 4

Article No.: 28, Pages 1 - 41

https://doi.org/10.1145/1777406.1777407

Published: 13 July 2010 Publication History

Abstract

In data collection applications of low-end sensor networks, a major challenge is ensuring reliability without a significant goodput degradation. Short hops over high-quality links minimize per-hop transmissions, but long routes may cause congestion and load imbalance. Longer links can be exploited to build shorter routes, but poor links may have a high energy cost. There exists a complex interplay among routing performance (reliability, goodput, energy efficiency), link estimation, congestion control, and load balancing; we design a routing architecture, Arbutus, that exploits this interplay, and perform an extensive experimental evaluation on testbeds of 100-150 Berkeley motes.

References

[1]

Cerpa, A., Wong, J., Potkonjak, M., and Estrin, D. 2005. Temporal properties of low power wireless links: Modeling and implications on multi-hop routing. In Proceedings of the 4th ACM/IEEE International Symposium on Information Processing in Sensor Networks (IPSN'05).

[2]

Choi, J., Lee, J., Wachs, M., Chen, Z., and Levis, P. 2007a. Fair waiting protocol: Achieving isolation in wireless sensornets. In Proceedings of the 5th ACM Conference on Embedded Networked Sensor Systems (SenSys'07).

Digital Library

[3]

Choi, J., Lee, J., Wachs, M., Chen, Z., and Levis, P. 2007b. Opening the Sensornet black box. In Proceedings of the International Workshop on Wireless Sensornet Architecture (WWSNA'07).

Digital Library

[4]

Couto, D. D., Aguayo, D., Bicket, J., and Morris, R. 2003. A high-throughput path metric for multi-hop wireless routing. In Proceedings of the 9th Annual International Conference on Mobile Computing and Networking (MobiCom'03).

Digital Library

[5]

Filipponi, L., Santini, S., and Vitaletti, A. 2008. Data collection in wireless sensor networks for noise pollution monitoring. In Proceedings of the International Conference on Distributed Computing in Sensor Systems (DCOSS'08).

Digital Library

[6]

Fonseca, R., Gnawali, O., Jamieson, K., and Levis, P. 2007. Four-Bit wireless link estimation. In Proceedings of the 6th Workshop on Hot Topics in Networks (HotNets-VI).

[7]

Ganesan, D., Govindan, R., Shenker, S., and Estrin, D. 2002. Highly resilient, energy efficient multipath routing in wireless sensor networks. ACM Mobile Comput. Comm. Rev. 1, 2, 10--24.

Digital Library

[8]

Gnawali, O. 2007. The link estimation exchange protocol (LEEP). http://www.tinyos.net/tinyos-2.x/doc/html/tep124.html.

[9]

Gnawali, O., Fonseca, R., Jamieson, K., Moss, D., and Levis, P. 2009. Collection tree protocol. In Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems (SenSys'09).

Digital Library

[10]

Gnawali, O., Yarvis, M., Heidemann, J., and Govindan, R. 2004. Interaction of retransmission, blacklisting, and routing metrics for reliability in sensor network routing. In Proceedings of the 1st IEEE Conference on Sensor and Ad Hoc Communication and Networks (SECON'04). 34--43.

[11]

Haenggi, M. and Puccinelli, D. 2005. Routing in ad hoc networks: A case for long hops. IEEE Comm. Mag. 43, 93--101.

Digital Library

[12]

Handziski, V., Koepke, A., Willig, A., and Wolisz, A. 2006. TWIST: A scalable and reconfigurable testbed for wireless indoor experiments with sensor networks. In Proceedings of the 2nd International Workshop on Multi-hop Ad Hoc Networks: from Theory to Reality (REALMAN'06).

Digital Library

[13]

Hauer, J., Handziski, V., Koepke, A., Willig, A., and Wolisz, A. 2008. A component framework for content-based publish/subscribe in sensor networks. In Proceedings of the IEEE European Workshop on Wireless Sensor Networks (EWSN'08).

Digital Library

[14]

Hill, J., Szewczyk, R., Woo, A., Hollar, S., Culler, D., and Pister, K. 2000. System architecture directions for network sensors. In Proceedings of the 9th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS'00).

Digital Library

[15]

Hull, B., Jamieson, K., and Balakrishnan, H. 2004. Mitigating congestion in wireless sensor networks. In Proceedings of the 2nd ACM Conference on Embedded Networked Sensor Systems (SenSys'04).

Digital Library

[16]

Jain, R. 1991. The Art of Computer Systems Performance Analysis. Wiley.

[17]

Karenos, K. and Kalogeraki, V. 2007. Facilitating congestion avoidance in sensor networks with a mobile sink. In Proceedings of the 28th International IEEE Real-Time Systems Symposium (RTSS'07).

Digital Library

[18]

Kothari, N., Millstein, T., and Govindan, R. 2008. Deriving state machines from TinyOS programs using symbolic execution. In Proceedings of the 7th International Conference on Information Processing in Sensor Networks (IPSN'08).

Digital Library

[19]

Langendoen, K., Baggio, A., and Visser, O. 2006. Murphy loves potatoes: Experiences from a pilot sensor network deployment in precision agriculture. In Proceedings of the 14th International Workshop on Parallel and Distributed Real-Time Systems (WPDRTS'06).

Digital Library

[20]

Musaloiu-E., R., Liang, C., and Terzis, A. 2008. Deriving state machines from TinyOS programs using symbolic execution. In Proceedings of the 7th International Conference on Information Processing in Sensor Networks (IPSN'08).

Digital Library

[21]

Paek, J. and Govindan, R. 2007. RCRT: Rate-Controlled reliable transport for wireless sensor networks. In Proceedings of the 5th ACM Conference on Embedded Networked Sensor Systems (SenSys'07).

Digital Library

[22]

Polastre, J., Hill, J., and Culler, D. 2004. Versatile low power media access for wireless sensor networks. In Proceedings of the 2nd ACM Conference on Embedded Networked Sensor Systems (SenSys'04).

Digital Library

[23]

Poor, R. 2000. Gradient routing in ad hoc networks. http://www.media.mit.edu/pia/Research/ESP/texts/poorieeepaper.pdf.

[24]

Puccinelli, D. and Haenggi, M. 2006a. Multipath fading in wireless sensor networks: Measurements and interpretation. In Proceedings of the International Wireless Communications and Mobile Computing Conference (IWCMC'06).

Digital Library

[25]

Puccinelli, D. and Haenggi, M. 2006b. Spatial diversity benefits by means of induced fading. In Proceedings of the 3rd IEEE International Conference on Sensor and Ad Hoc Communications and Networks (SECON'06).

[26]

Puccinelli, D. and Haenggi, M. 2008a. Arbutus: Network-Layer load balancing for wireless sensor networks. In Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC'08).

[27]

Puccinelli, D. and Haenggi, M. 2008b. DUCHY: Double cost field hybrid link estimation for low-power wireless sensor networks. In Proceedings of the 5th Workshop on Embedded Networked Sensors (HotEmNets'08).

[28]

Puccinelli, D. and Haenggi, M. 2009. Lifetime benefits through load balancing in homogeneous sensor networks. In Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC'09).

Digital Library

[29]

Ramakrishnan, K. and Jain, R. 1990. A binary feedback scheme for congestion avoidance in computer networks. ACM Trans. Comput. Syst. 8, 2 (May), 158--181.

Digital Library

[30]

Rangwala, S., Gummadi, R., Govindan, R., and Psounis, K. 2006. Interference-Aware fair rate control in wireless sensor networks. In Proceedings of the ACM SIGCOMM Symposium on Network Architectures and Protocols.

Digital Library

[31]

Srinivasan, K., Dutta, P., Tavakoli, A., and Levis, P. 2008a. An empirical study of low-power wireless. Tech. rep. SING-08-03, Stanford University.

[32]

Srinivasan, K., Kazandjieva, M., Agarwal, S., and Levis, P. 2008b. The beta-factor: Improving bimodal wireless networks. In Proceedings of the 6th ACM Conference on Embedded Networked Sensor Systems (SenSys'07).

[33]

Srinivasan, K. and Levis, P. 2006. RSSI is under appreciated. In Proceedings of the 3rd Workshop on Embedded Networked Sensors (EmNets'06).

[34]

Wachs, M., Choi, J., Lee, J., Srinivasan, K., Chen, Z., Jain, M., and Levis, P. 2007. Visibility: A new metric for protocol design. In Proceedings of the 5th ACM Conference on Embedded Networked Sensor Systems (SenSys'07).

Digital Library

[35]

Wan, C., Eisenman, S., and Campbell, A. 2003. CODA: Congestion detection and avoidance in sensor networks. In Proceedings of the 1st ACM Conference on Embedded Networked Sensor systems (SenSys'03).

Digital Library

[36]

Wan, C., Eisenman, S., Campbell, A., and Crowcroft, J. 2007. Overload traffic management in sensor networks. ACM Trans. Sensor Netw. 3, 4.

Digital Library

[37]

Wang, Q., Hempstead, M., and Yang, W. 2006. A realistic power consumption model for wireless sensor network devices. In Proceedings of the 3rd IEEE International Conference on Sensor and Ad Hoc Communications and Networks (SECON'06).

[38]

Werner-Allen, G., Swieskowski, P., and Welsh, M. 2005. MoteLab: A wireless sensor network testbed. In Proceedings of the 4th International Symposium on Information Processing in Sensor Networks (IPSN'05).

Digital Library

[39]

Woo, A. 2004. A holistic approach to multihop routing in sensor networks. Ph.D. thesis, University of California at Berkeley.

Digital Library

[40]

Woo, A. and Culler, D. 2001. A transmission control scheme for media access in sensor networks. In Proceedings of the 7th International Conference on Mobile Computing and Networking (MobiCom'01).

Digital Library

[41]

Woo, A., Tong, T., and Culler, D. 2003. Taming the underlying challenges of reliable multihop routing in sensor networks. In Proceedings of the 1st ACM Conference on Embedded Networked Sensor Systems (SenSys'03).

Digital Library

[42]

Zhang, H., Sang, L., and Arora, A. 2008. Data-Driven link estimation in sensor networks: An accuracy perspective. Tech. rep. DNC-TR-08-02, Wayne State University.

[43]

Zhao, J. and Govindan, R. 2003. Understanding packet delivery performance in dense wireless sensor networks. In Proceedings of the 1st ACM Conference on Embedded Networked Sensor Systems (SenSys'03).

Digital Library

[44]

Zuniga, M. and Krishnamachari, B. 2007. An analysis of unreliability and asymmetry in low-power wireless links. ACM Trans. Sensor Netw. 3, 2, 1--30.

Digital Library

Cited By

Navarro MLiang YZhong X(2022)Energy-efficient and balanced routing in low-power wireless sensor networks for data collectionAd Hoc Networks10.1016/j.adhoc.2021.102766127(102766)Online publication date: Mar-2022
https://doi.org/10.1016/j.adhoc.2021.102766
Hsu SYu YTang B(2020) DRE 2 : Achieving Data Resilience in Wireless Sensor Networks: A Quadratic Programming Approach 2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)10.1109/MASS50613.2020.00019(71-79)Online publication date: Dec-2020
https://doi.org/10.1109/MASS50613.2020.00019
Liu DCao ZZhang YHou M(2017)Achieving Accurate and Real-Time Link Estimation for Low Power Wireless Sensor NetworksIEEE/ACM Transactions on Networking10.1109/TNET.2017.268227625:4(2096-2109)Online publication date: 1-Aug-2017
https://dl.acm.org/doi/10.1109/TNET.2017.2682276
Show More Cited By

Index Terms

Reliable data delivery in large-scale low-power sensor networks
1. Networks
  1. Network protocols
    1. Network layer protocols
      1. Routing protocols
  2. Network types
    1. Mobile networks
    2. Wireless access networks

Recommendations

Event-to-sink reliable transport in wireless sensor networks

Wireless sensor networks (WSNs) are event-based systems that rely on the collective effort of several microsensor nodes. Reliable event detection at the sink is based on collective information provided by source nodes and not on any individual report. ...
Energy and congestion-aware load balanced multi-path routing for wireless sensor networks in ambient environments
Abstract
In wireless sensor networks (WSNs), a large number of sensor nodes (SNs) equipped with batteries are randomly distributed around an area in order to detect and capture sensor data. In WSNs, congestion is created in the node due to ...
Reliable data transport and congestion control in wireless sensor networks

Reliable data delivery and congestion control are two fundamental transport layer functions. Due to the specific characteristics of Wireless Sensor Networks (WSNs), traditional transport layer protocols (e.g. Transmission Control Protocol (TCP) and User ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Transactions on Sensor Networks

ACM Transactions on Sensor Networks Volume 6, Issue 4

July 2010

300 pages

ISSN:1550-4859

EISSN:1550-4867

DOI:10.1145/1777406

Issue’s Table of Contents

Copyright © 2010 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]

Publisher

Association for Computing Machinery

New York, NY, United States

Journal Family

ACM Journals for the Design of Smart and Connected Systems

Publication History

Published: 13 July 2010

Accepted: 01 September 2009

Revised: 01 July 2009

Received: 01 June 2008

Published in TOSN Volume 6, Issue 4

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed

Funding Sources

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

36
Total Citations
View Citations
947
Total Downloads

Downloads (Last 12 months)4
Downloads (Last 6 weeks)1

Reflects downloads up to 09 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

Navarro MLiang YZhong X(2022)Energy-efficient and balanced routing in low-power wireless sensor networks for data collectionAd Hoc Networks10.1016/j.adhoc.2021.102766127(102766)Online publication date: Mar-2022
https://doi.org/10.1016/j.adhoc.2021.102766
Hsu SYu YTang B(2020) DRE 2 : Achieving Data Resilience in Wireless Sensor Networks: A Quadratic Programming Approach 2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)10.1109/MASS50613.2020.00019(71-79)Online publication date: Dec-2020
https://doi.org/10.1109/MASS50613.2020.00019
Liu DCao ZZhang YHou M(2017)Achieving Accurate and Real-Time Link Estimation for Low Power Wireless Sensor NetworksIEEE/ACM Transactions on Networking10.1109/TNET.2017.268227625:4(2096-2109)Online publication date: 1-Aug-2017
https://dl.acm.org/doi/10.1109/TNET.2017.2682276
Kamal AHamid M(2017)Supervisory routing control for dynamic load balancing in low data rate wireless sensor networksWireless Networks10.1007/s11276-016-1209-z23:4(1085-1099)Online publication date: 1-May-2017
https://dl.acm.org/doi/10.1007/s11276-016-1209-z
Liu DCao ZHou MZhang YXing G(2016)Frame counterProceedings of the 15th International Conference on Information Processing in Sensor Networks10.5555/2959355.2959375(1-12)Online publication date: 11-Apr-2016
https://dl.acm.org/doi/10.5555/2959355.2959375
Navarro MLiang YRömer KLangendoen KVoigt T(2016)Efficient and Balanced Routing in Energy-Constrained Wireless Sensor Networks for Data CollectionProceedings of the 2016 International Conference on Embedded Wireless Systems and Networks10.5555/2893711.2893727(101-113)Online publication date: 15-Feb-2016
https://dl.acm.org/doi/10.5555/2893711.2893727
Vallati CAncillotti EBruno RMingozzi EAnastasi GLassous IBarba CRazafindralambo T(2016)Interplay of Link Quality Estimation and RPL PerformanceProceedings of the 13th ACM Symposium on Performance Evaluation of Wireless Ad Hoc, Sensor, & Ubiquitous Networks10.1145/2989293.2989299(83-90)Online publication date: 13-Nov-2016
https://dl.acm.org/doi/10.1145/2989293.2989299
Liu DCao ZHou MZhang Y(2016)Frame Counter: Achieving Accurate and Real-Time Link Estimation in Low Power Wireless Sensor Networks2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN)10.1109/IPSN.2016.7460673(1-12)Online publication date: Apr-2016
https://doi.org/10.1109/IPSN.2016.7460673
Li SGao HWu DLi L(2016)Development and implementation of EBGR routing protocol in cropland based on IRIS platform2016 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC)10.1109/ICSPCC.2016.7753627(1-6)Online publication date: Aug-2016
https://doi.org/10.1109/ICSPCC.2016.7753627
Li HPeng Su Zhizhen Chi Jingjing Wang (2016)Image retrieval and classification on deep convolutional SparkNet2016 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC)10.1109/ICSPCC.2016.7753615(1-6)Online publication date: Aug-2016
https://doi.org/10.1109/ICSPCC.2016.7753615
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Article

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Issue’s Table of Contents