research-article

FWB: : Funneling Wider Bandwidth algorithm for high performance data collection in Wireless Sensor Networks

Authors:

Rodrigo C. Tavares,

Marcos Carvalho,

Eduardo P.M. Câmara Júnior,

Erik de Britto e Silva,

Marcos A.M. Vieira,

Luiz F.M. Vieira,

Bhaskar KrishnamachariAuthors Info & Claims

Volume 148, Issue C

Pages 136 - 151

https://doi.org/10.1016/j.comcom.2019.09.015

Published: 15 December 2019 Publication History

Abstract

Many Wireless Sensor Networks (WSNs) applications demand to collect large volumes of data in a coordinated approach. To do this, a many-to-one pattern (convergecast) communication in tree-based WSN is used, but traffic near the sink node commonly becomes the network bottleneck. Thus, we propose an extension to a wireless network standard to provide wider bandwidth channels. We explore how fast the information can be collected in a WSN organized as a tree, with the radios operating with these wider bandwidth channels. As consequence, we proposed and implemented Funneling Wider Bandwidth (FWB), an algorithm that minimizes schedule length in networks with radios operating with the proposed extension. We proved that the algorithm is optimal in calculating a minimum number of time slots. In this way, we obtain a higher average throughput and a lesser number of time slots. Results from simulations and experiments on a real testbed confirm these gains. The proposed approach could be adapted and used with other related standards such as WirelessHART^TM, ISA 100.11a and IEEE 802.15.4e TSCH. Experiment results showed that with this wider bandwidth emulated in a given topology, the packets received per second by the sink node increased by 122.8% in comparison with just one bandwidth.

References

[1]

L.B. Ruiz, L.H.A. Correia, L.F.M. Vieira, D.F. Macedo, E.F. Nakamura, C.M. Figueiredo, M.A.M. Vieira, E.H.B. Maia, D. Câmara, A.A. Loureiro, et al. Architectures for Wireless Sensor Networks, Proceedings of the 22nd Brazilian Symposium on Computer Networks (SBRC 04), 2004, 167–218.

[2]

Lin R., Wang Z., Sun Y., Wireless sensor networks solutions for real time monitoring of nuclear power plant, in: Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on, Vol. 4, IEEE, 2004, pp. 3663–3667.

[3]

Kim S., Pakzad S., Culler D., Demmel J., Fenves G., Glaser S., Turon M., Health monitoring of civil infrastructures using wireless sensor networks, in: Information Processing in Sensor Networks, 2007. IPSN 2007. 6th International Symposium on, IEEE, 2007, pp. 254–263.

[4]

Werner-Allen G., Lorincz K., Johnson J., Lees J., Welsh M., Fidelity and yield in a volcano monitoring sensor network, in: Proceedings of the 7th Symposium on Operating Systems Design and Implementation, USENIX Association, 2006, pp. 381–396.

[5]

Werner-Allen G., Lorincz K., Ruiz M., Marcillo O., Johnson J., Lees J., Welsh M., Deploying a wireless sensor network on an active volcano, IEEE Internet Comput. 10 (2) (2006) 18–25,.

Digital Library

[6]

IEC TC/SC 65C, Industrial Communication Networks - Wireless Communication Network and Communication Profiles - WirelessHART™, Tech. Rep. IEC 62591, The International Electrotechnical Commission, 3, rue de Varembé, Case postale 131, CH-1211 Genève 20, Switzerland, 2010.

[7]

I. Standard, Wireless Systems for Industrial Automation: Process Control and Related Applications, ISA-100.11 a-2009.

[8]

IEEE STD 802.15.4E - 2016, IEEE Standard for Low-Rate Wireless Networks - IEEE Std 802.15.4-2015 (Revision of IEEE Std 802.15.4-2011), 2016, 1–225.

[9]

Polastre J., Szewczyk R., Culler D., Telos: Enabling ultra-low power wireless research, in: Proceedings of the 4th International Symposium on Information Processing in Sensor Networks, in: IPSN ’05, IEEE Press, Piscataway, NJ, USA, 2005.

[10]

M.A.M. Vieira, C.N. Coelho, D.C. da Silva, J.M. da Mata, Survey on Wireless Sensor Network Devices, in: EFTA 2003. 2003 IEEE Conference on Emerging Technologies and Factory Automation. Proceedings, Vol. 1, 2003, pp. 537–544 vol.1. https://doi.org/10.1109/ETFA.2003.1247753.

[11]

Incel O.D., Ghosh A., Krishnamachari B., Chintalapudi K., Fast data collection in tree-based wireless sensor networks, IEEE Trans. Mob. Comput. 11 (1) (2012) 86–99.

[12]

Júnior R., dos Santos N., Tavares R.C., Vieira M.A., Vieira L.F., Gnawali O., Codedrip, Ad Hoc Netw. 54 (C) (2017) 42–52,.

[13]

Gnawali O., Fonseca R., Jamieson K., Moss D., Levis P., Collection tree protocol, in: Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems, ACM, 2009, pp. 1–14.

[14]

Santos B.P., Vieira M.A., Vieira L.F., Extend collection tree protocol, in: 2015 IEEE Wireless Communications and Networking Conference (WCNC), IEEE, 2015, pp. 1512–1517.

[15]

Ahn G.-S., Hong S.G., Miluzzo E., Campbell A.T., Cuomo F., Funneling-MAC: A localized, sink-oriented MAC for boosting fidelity in sensor networks, in: Proceedings of the 4th International Conference on Embedded Networked Sensor Systems, in: SenSys ’06, ACM, New York, NY, USA, 2006, pp. 293–306.

[16]

Gandham S., Zhang Y., Huang Q., Distributed minimal time convergecast scheduling in wireless sensor networks, in: Distributed Computing Systems, 2006. ICDCS 2006. 26th IEEE International Conference on, IEEE, 2006, p. 50.

[17]

Zhou G., Huang C., Yan T., He T., Stankovic J.A., Abdelzaher T.F., MMSN: Multi-frequency media access control for wireless sensor networks, in: In IEEE INFOCOM, 2006, p. 7.

[18]

O.D. Incel, A. Ghosh, B. Krishnamachari, K.K. Chintalapudi, Multichannel Scheduling for Fast Convergecast in Wireless Sensor Networks.

[19]

Tavares R.C., Vieira M.A., Vieira L.F., FlushMF: A transport protocol using multiple frequencies for wireless sensor network, in: Mobile Ad Hoc and Sensor Systems (MASS), 2016 IEEE 13th International Conference on, IEEE, 2016, pp. 192–200.

[20]

Raman B., Chebrolu K., Bijwe S., Gabale V., PIP: A connection-oriented, multi-hop, multi-channel TDMA-based MAC for high throughput bulk transfer, in: Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems, ACM, 2010, pp. 15–28.

[21]

Doddavenkatappa M., Chan M.C., P3: A practical packet pipeline using synchronous transmissions for wireless sensor networks, in: Information Processing in Sensor Networks, IPSN-14 Proceedings of the 13th International Symposium on, IEEE, 2014, pp. 203–214.

[22]

Yuan D., Hollick M., Tree-based multi-channel convergecast in wireless sensor networks, in: World of Wireless, Mobile and Multimedia Networks (WoWMoM), 2012 IEEE International Symposium on a, IEEE, 2012, pp. 1–9.

[23]

Pan M.-S., Lee Y.-H., Fast convergecast for low-duty-cycled multi-channel wireless sensor networks, Ad Hoc Netw. 40 (2016) 1–14.

[24]

Chen Y.-D., Wu D.-R., Sung T.-C., Shih K.-P., Dbs: A dynamic bandwidth selection mac protocol for channel bonding in ieee 802.11 ac wlans, in: Wireless Communications and Networking Conference (WCNC), 2018 IEEE, IEEE, 2018, pp. 1–6.

[25]

Du P., Roussos G., Adaptive time slotted channel hopping for wireless sensor networks, in: Computer Science and Electronic Engineering Conference (CEEC), 2012 4th, IEEE, 2012, pp. 29–34.

[26]

Tavakoli R., Nabi M., Basten T., Goossens K., Enhanced time-slotted channel hopping in wsns using non-intrusive channel-quality estimation, in: Mobile Ad Hoc and Sensor Systems (MASS), 2015 IEEE 12th International Conference on, IEEE, 2015, pp. 217–225.

[27]

Li P., Vermeulen T., Liy H., Pollin S., An adaptive channel selection scheme for reliable tsch-based communication, in: Wireless Communication Systems (ISWCS), 2015 International Symposium on, IEEE, 2015, pp. 511–515.

[28]

Fafoutis X., Elsts A., Oikonomou G., Piechocki R., Craddock I., Adaptive static scheduling in ieee 802.15. 4 tsch networks, in: Internet of Things (WF-IoT), 2018 IEEE 4th World Forum on, IEEE, 2018, pp. 263–268.

[29]

Shannon C.E., A mathematical theory of communication, Bell Syst. Tech. J. 27 (3) (1948) 379–423,.

[30]

Goussevskaia O., Vieira L.F., Vieira M.A., Wireless scheduling with multiple data rates: From physical interference to disk graphs, Comput. Netw. 106 (Supplement C) (2016) 64–76,.

Digital Library

[31]

Wan C.-Y., Eisenman S.B., Campbell A.T., Crowcroft J., Siphon: Overload traffic management using multi-radio virtual sinks in sensor networks, in: Proceedings of the 3rd International Conference on Embedded Networked Sensor Systems, in: SenSys ’05, ACM, New York, NY, USA, 2005, pp. 116–129,.

Digital Library

[32]

Gupta P., Kumar P.R., The capacity of wireless networks, IEEE Trans. Inf. Theory 46 (2) (2000) 388–404.

[33]

Choi H., Wang J., Hughes E.A., Scheduling for information gathering on sensor network, Wirel. Netw. 15 (1) (2009) 127–140,.

Digital Library

[34]

Song W.-Z., Yuan F., LaHusen R., Shirazi B., Time-optimum packet scheduling for many-to-one routing in wireless sensor networks, Int. J. Parallel Emergent Distrib. Syst. 22 (5) (2007) 355–370.

[35]

Texas Instruments, 2.4 GHz IEEE 802.15.4 / ZigBee-ready RF Transceiver, CC2420 datasheet, rev. C, 2013.

[36]

Goussevskaia O., Moscibroda T., Wattenhofer R., Local broadcasting in the physical interference model, in: Proceedings of the Fifth International Workshop on Foundations of Mobile Computing, ACM, 2008, pp. 35–44.

[37]

P. Levis, D. Gay, TinyOS Programming, 2009.

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FWB: Funneling Wider Bandwidth algorithm for high performance data collection in Wireless Sensor Networks

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Information & Contributors

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Published In

cover image Computer Communications

Computer Communications Volume 148, Issue C

Dec 2019

243 pages

ISSN:0140-3664

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Elsevier B.V.

Publisher

Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 15 December 2019

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