research-article

Toward Stable Network Performance in Wireless Sensor Networks: A Multilevel Perspective

Authors:

Mo’taz Al-Hami,

Kamin Whitehouse,

John A. Stankovic,

Hengchang LiuAuthors Info & Claims

ACM Transactions on Sensor Networks (TOSN), Volume 11, Issue 3

Article No.: 42, Pages 1 - 26

https://doi.org/10.1145/2700272

Published: 17 February 2015 Publication History

Abstract

Many applications in wireless sensor networks require communication performance that is both consistent and of high quality. Unfortunately, performance of current network protocols can vary significantly because of various interferences and environmental changes. Current protocols estimate link quality based on the reception of probe packets over a short time period. This method is neither efficient nor accurate enough to capture the dramatic variations of link quality. Therefore, we propose a link metric called competence that characterizes links over a longer period of time. We combine competence with current short-term estimations in routing algorithm designs. To further improve network performance, we have designed a distributed route maintenance framework based on feedback control solutions. This framework allows every link along an end-to-end (E2E) path to adjust its link protocol parameters, such as transmission power and number of retransmissions, to ensure specified E2E reliability and latency under dynamic link qualities. Our solutions are evaluated in both extensive simulations and real system experiments. In real system evaluations with 48 T-Motes, our overall solution improves E2E packet delivery ratio over existing solutions by up to 40% while reducing transmission energy consumption by up to 22%. Importantly, our solution also achieves more stable and better transient performance than current approaches.

References

[1]

T. Abdelzaher, Y. Diao, J. L. Hellerstein, C. Lu, and X. Zhu. 2008. Introduction to control theory and its application to computing systems. In Performance Modeling and Engineering. Springer, 185--215.

[2]

A. Ahmad, L. Abdul Latiff, and N. Fisal. 2008. Real-time routing in wireless sensor networks. In Proceedings of ICDSW.

Digital Library

[3]

P. Asare, D. Cong, S. G. Vattam, B.-G. Kim, A. King, O. Sokolsky, I. Lee, S. Lin, and M. Mullen-Fortino. 2012. The medical device dongle: An open-source standards-based platform for interoperable medical device connectivity. In Proceedings of IHI’12.

Digital Library

[4]

J. Bicket, D. Aguayo, S. Biswas, and R. Morris. 2005. Architecture and evaluation of an unplanned 802.11b mesh network. In Proceedings of ACM MobiCom’05.

Digital Library

[5]

S. Boyd and L. Vandenberghe. 2004. Convex Optimization. Cambridge University Press.

Digital Library

[6]

G. Buttazzo. 2006. Research trends in real-time computing for embedded systems. ACM SIGBED Review 3, 3, 1--10.

Digital Library

[7]

Q. Cao, T. Abdelzaher, T. He, and R. Kravets. 2007. Cluster-based forwarding for reliable end-to-end delivery in wireless sensor networks. In Proceedings of IEEE INFOCOM’07.

[8]

A. Cerpa, J. L. Wong, M. Potkonjak, and D. Estrin. 2005. Temporal properties of low power wireless links: Modeling and implications on multi-hop routing. In Proceedings of ACM MobiHoc’05.

Digital Library

[9]

S. Chakrabarti and A. Mishra. 2001. QoS issues in ad hoc wireless networks. IEEE Communications Magazine 39, 2, 142--148.

Digital Library

[10]

L. Chen and W. Heinzelman. 2005. QoS-aware routing based on bandwidth estimation for mobile ad hoc networks. IEEE Journal on Selected Areas in Communications 23, 3, 561--572.

Digital Library

[11]

O. Chipara, Z. He, G. Xing, Q. Chen, X. Wang, C. Lu, J. Stankovic, and T. Abdelzaher. 2006. Real-time power aware routing in wireless sensor networks. In Proceedings of IWQOS’06.

[12]

D. E. Comer. 2000. Internetworking with TCP/IP: Principles, Protocols, and Architecture, Vol. 1. Addison-Wesley.

Digital Library

[13]

A. Dunkels, F. Österlind, and Z. He. 2007. An adaptive communication architecture for wireless sensor networks. In Proceedings of ACM SenSys’07.

Digital Library

[14]

E. Felemban, C. Lee, E. Ekici, R. Boder, and S. Vural. 2005. Probabilistic QoS guarantee in reliability and timeliness domains in wireless sensor networks. In Proceedings of IEEE INFOCOM’05.

[15]

R. Fonseca, O. Gnawali, K. Jamieson, and P. Levis. 2007. Four bit wireless link estimation. In Proceedings of HotNets VI’07.

[16]

L. Girod, M. Lukac, V. Trifa, and D. Estrin. 2006. A self-calibrating distributed acoustic sensing platform. In Proceedings of ACM SenSys’06.

Digital Library

[17]

O. Gnawali, R. Fonseca, K. Jamieson, D. Moss, and P. Levis. 2009. Collection Tree Protocol. In Proceedings of SenSys’09.

Digital Library

[18]

Y. Gu and T. He. 2007. Data forwarding in extremely low duty-cycle sensor networks with unreliable communication links. In Proceedings of ACM SenSys’07.

Digital Library

[19]

G. Hackmann, O. Chipara, and C. Lu. 2008. Robust topology control for indoor wireless sensor networks. In Proceedings of ACM SenSys’08.

Digital Library

[20]

T. He, S. Krishnamurthy, J. A. Stankovic, T. F. Abdelzaher, L. Luo, R. Stoleru, T. Yan, L. Gu, J. Hui, and B. Krogh. 2004. Energy-efficient surveillance system using wireless sensor networks. In Proceedings of ACM MobiSys’04.

Digital Library

[21]

T. He, P. Vicaire, T. Yan, L. Luo, L. Gu, G. Zhou, R. Stoleru, Q. Cao, J. A. Stankovic, and T. Abdelzaher. 2006. Achieving real-time target tracking using wireless sensor networks. In Proceedings of RTAS’06.

Digital Library

[22]

J. L. Hellerstein, Y. Diao, S. Parekh, and D. M. Tilbury. 2004. Feedback Control of Computing Systems. John Wiley and Sons.

Digital Library

[23]

IEEE 802.15.4. 1999. IEEE 802.15.4, Wireless Medium Access Control (MAC) and Physical Layer (PHY) Specifications for Low Rate Wireless Personal Area Networks (LR-WPANs).

[24]

C. Intanagonwiwat, R. Govindan, D. Estrin, J. Heidemann, and F. Silva. 2003. Directed diffusion for wireless sensor networking. IEEE/ACM Transactions on Networking 11, 1, 2--16.

Digital Library

[25]

S. Katti, H. Rahul, W. Hu, D. Katabi, M. Médard, and J. Crowcroft. 2006. XORs in the air: Practical wireless network coding. ACM SIGCOMM Computer Communication Review 36, 4, 243--254.

Digital Library

[26]

M. Kim and B. Noble. 2001. Mobile network estimation. In Proceedings of ACM MobiCom’01.

Digital Library

[27]

S. Kim, R. Fonseca, P. Dutta, A. Tavakoli, D. Culler, P. Levis, S. Shenker, and I. Stoica. 2007. Flush: A reliable bulk transport protocol for multihop wireless networks. In Proceedings of ACM SenSys’07.

Digital Library

[28]

S. Kim, S. H. Son, J. A. Stankovic, S. Li, and Y. Choi. 2003. Safe: A data dissemination protocol for periodic updates in sensor networks. In Proceedings of Distributed Computing Systems Workshops. IEEE, 228--234.

Digital Library

[29]

S. Lin, J. Zhang, G. Zhou, L. Gu, J. A. Stankovic, and T. He. 2006. ATPC: Adaptive transmission power control for wireless sensor networks. In Proceedings of ACM SenSys’06.

Digital Library

[30]

X. Liu, H. Zhang, Q. Xiang, X. Che, and X. Ju. 2012. Taming uncertainties in real-time routing for wireless networked sensing and control. In Proceedings of MobiHoc’12.

Digital Library

[31]

C. Lu, J. A. Stankovic, S. H. Son, and G. Tao. 2002. Feedback control real-time scheduling: Framework, modeling, and algorithms. In Proceedings of JRTS’02.

Digital Library

[32]

C. Lu, X. Wang, and X. Koutsoukos. 2005. Feedback utilization control in distributed real-time systems with end-to-end tasks. IEEE Transactions on Parallel and Distributed Systems 16, 6, 550--561.

Digital Library

[33]

E. Miluzzo, X. Zheng, K. Fodor, and A. T. Campbell. 2008. Radio characterization of 802.15.4 and its impact on the design of mobile sensor networks. In Proceedings of WSN’08.

Digital Library

[34]

D. C. Montgomery. 2005. Introduction to Statistical Quality Control. John Wiley and Sons.

[35]

MultihopLQI 2006. Tinyos MultiHopLQI Collection Protocol. Retrieved January 15, 2015, from http://www.tinyos.net/tinyos-1.x/tos/lib/MultiHopLQI.

[36]

J. Paek and R. Govindan. 2007. RCRT: Rate-controlled reliable transport for wireless sensor networks. In Proceedings of ACM SenSys’07.

Digital Library

[37]

J. Polastre, J. Hill, and D. Culler. 2004. Versatile low power media access for wireless sensor networks. In Proceedings of ACM SenSys’04.

Digital Library

[38]

J. Polastre, J. Hui, P. Levis, J. Zhao, D. Culler, S. Shenker, and I. Stoica. 2005. A unifying link abstraction for wireless sensor networks. In Proceedings of ACM Sensys’05.

Digital Library

[39]

D. Puccinelli, O. Gnawali, S. Yoon, S. Santini, U. Colesanti, S. Giordano, and L. Guibas. 2011. The impact of network topology on collection performance. In Proceedings of EWSN’11.

Digital Library

[40]

P. Santi. 2005. Topology control in wireless ad hoc and sensor networks. ACM Computing Surveys 37, 2, 164--194.

Digital Library

[41]

H. Schulzrinne and S. Casner. 1993. RTP: A Transport Protocol for Real-Time Applications. Internet draft.

[42]

L. Selavo, A. Wood, Q. Cao, T. Sookoor, H. Liu, A. Srinivasan, Y. Wu, W. Kang, J. Stankovic, D. Young, and J. Porter. 2007. LUSTER: Wireless sensor network for environmental research. In Proceedings of ACM SenSys’07.

Digital Library

[43]

N. Shankaran, N. Roy, D. C. Schmidt, X. D. Koutsoukos, Y. Chen, and C. Lu. 2008. Design and performance evaluation of an adaptive resource management framework for distributed real-time and embedded systems. EURASIP Journal on Embedded Systems 2008, Article No. 9.

Digital Library

[44]

M. R. Souryal, J. Geissbuehler, L. E. Miller, and N. Moayeri. 2007. Real-time deployment of multihop relays for range extension. In Proceedings of ACM MobiSys’07.

Digital Library

[45]

K. Srinivasan, M. Kazandjieva, S. Agarwal, and P. Levis. 2008. The beta-factor: Measuring wireless link burstiness. In Proceedings of ACM SenSys’08.

Digital Library

[46]

M. Wachs, J. I. Choi, J. W. Lee, K. Srinivasan, Z. Chen, M. Jain, and P. Levis. 2007. Visibility: A new metric for protocol design. In Proceedings of SenSys’07.

Digital Library

[47]

A. Woo, T. Tong, and D. Culler. 2003. Taming the underlying challenges of reliable multihop routing in sensor networks. In ACM SenSys’03.

Digital Library

[48]

Y. Xue, B. Ramamurthy, and M. Vuran. 2011. SDRCS: A service-differentiated real-time communication scheme for event sensing in wireless sensor networks. Computer Networks 55, 5, 3287--3302.

Digital Library

[49]

J. Zhao and R. Govindan. 2003. Understanding packet delivery performance in dense wireless sensor networks. In Proceedings of ACM SenSys’03.

Digital Library

[50]

G. Zhou, Q. Li, J. Li, Y. Wu, S. Lin, J. Lu, C.-Y. Wan, M. D. Yarvis, and J. A. Stankovic. 2011. Adaptive and radio-agnostic QoS for body sensor networks. ACM Transactions on Embedded Computing Systems 10, 4, Article No. 48.

Digital Library

Cited By

Xia MJin JLiu BHu YWang XChi K(2023)Physical-Assisted Routing for Proactive Avoidance of Nomadic Obstacles in IoTACM Transactions on Sensor Networks10.1145/356502119:2(1-29)Online publication date: 3-Feb-2023
https://dl.acm.org/doi/10.1145/3565021
Xia MLiu BHu YChi KWang XLiu J(2020)PACE: Physically-Assisted Channel EstimationIEEE Transactions on Wireless Communications10.1109/TWC.2020.297847819:6(3769-3781)Online publication date: Jun-2020
https://doi.org/10.1109/TWC.2020.2978478
Homaei MSoleimani FShamshirband SMosavi ANabipour NVarkonyi-Koczy A(2020)An Enhanced Distributed Congestion Control Method for Classical 6LowPAN Protocols Using Fuzzy Decision SystemIEEE Access10.1109/ACCESS.2020.29685248(20628-20645)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.2968524
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Index Terms

Toward Stable Network Performance in Wireless Sensor Networks: A Multilevel Perspective
1. Networks
  1. Network protocols

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Information & Contributors

Information

Published In

cover image ACM Transactions on Sensor Networks

ACM Transactions on Sensor Networks Volume 11, Issue 3

May 2015

400 pages

ISSN:1550-4859

EISSN:1550-4867

DOI:10.1145/2737802

Editor:
Chenyang Lu
Department of Computer Science and Engineering / School of Engineering and Applied Sciences / Washington University, MO

Issue’s Table of Contents

Copyright © 2015 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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ACM Journals for the Design of Smart and Connected Systems

Publication History

Published: 17 February 2015

Accepted: 01 October 2014

Revised: 01 July 2014

Received: 01 October 2013

Published in TOSN Volume 11, Issue 3

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NSF CAREER
NSF of Jiangsu Province
NSFC
EU FP7 CROWN
National Science Foundation (NSF) and SAIC

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Cited By

Xia MJin JLiu BHu YWang XChi K(2023)Physical-Assisted Routing for Proactive Avoidance of Nomadic Obstacles in IoTACM Transactions on Sensor Networks10.1145/356502119:2(1-29)Online publication date: 3-Feb-2023
https://dl.acm.org/doi/10.1145/3565021
Xia MLiu BHu YChi KWang XLiu J(2020)PACE: Physically-Assisted Channel EstimationIEEE Transactions on Wireless Communications10.1109/TWC.2020.297847819:6(3769-3781)Online publication date: Jun-2020
https://doi.org/10.1109/TWC.2020.2978478
Homaei MSoleimani FShamshirband SMosavi ANabipour NVarkonyi-Koczy A(2020)An Enhanced Distributed Congestion Control Method for Classical 6LowPAN Protocols Using Fuzzy Decision SystemIEEE Access10.1109/ACCESS.2020.29685248(20628-20645)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.2968524
Shen QYang CWen S(2019)A Dual-Camera Surveillance Video Summarization Generating Strategy for Multi-Target CapturingProceedings of the 3rd International Conference on Video and Image Processing10.1145/3376067.3376071(121-125)Online publication date: 20-Dec-2019
https://dl.acm.org/doi/10.1145/3376067.3376071
Oteafy SHassanein H(2019)Leveraging Tactile Internet Cognizance and Operation via IoT and Edge TechnologiesProceedings of the IEEE10.1109/JPROC.2018.2873577107:2(364-375)Online publication date: Feb-2019
https://doi.org/10.1109/JPROC.2018.2873577
Hadadian Nejad Yousefi MKavian YMahmoudi A(2019)RTMCHMultimedia Tools and Applications10.1007/s11042-018-6480-978:6(7803-7818)Online publication date: 1-Mar-2019
https://dl.acm.org/doi/10.1007/s11042-018-6480-9
(2018)A location and mobility independent scheme to quantify the neighbourhood stability of a node in mobile sensor networksInternational Journal of Mobile Network Design and Innovation10.5555/3272206.32722128:2(111-125)Online publication date: 1-Jan-2018
https://dl.acm.org/doi/10.5555/3272206.3272212
(2018)A location and mobility independent scheme to quantify the neighbourhood stability of a node in mobile sensor networksInternational Journal of Mobile Network Design and Innovation10.5555/3272193.32721998:2(111-125)Online publication date: 1-Jan-2018
https://dl.acm.org/doi/10.5555/3272193.3272199
(2018)A location and mobility independent scheme to quantify the neighbourhood stability of a node in mobile sensor networksInternational Journal of Mobile Network Design and Innovation10.5555/3272186.32721928:2(111-125)Online publication date: 1-Jan-2018
https://dl.acm.org/doi/10.5555/3272186.3272192
Fu SZhang YCeriotti MJiang YPackeiser MMarron P(2018)Modeling packet loss rate of IEEE 802.15.4 links in diverse environmental conditions2018 IEEE Wireless Communications and Networking Conference (WCNC)10.1109/WCNC.2018.8377111(1-6)Online publication date: Apr-2018
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