Cited By
View all- Sandell MRaza UUchida D(2023)SoLiCiT: Synchronous Listen, Code, and Transmit Protocol for Wireless Control ApplicationsIEEE Systems Journal10.1109/JSYST.2023.323677817:3(4212-4223)Online publication date: Sep-2023
Clustering-Based Data Collection Using Concurrent Transmission in Wireless Sensor Network
Pages 261 - 268
Abstract
This paper presents a cluster based data collection protocol for wireless sensor network. Constructive interference based flooding provides a novel way of global synchronization. Its communication mechanism turns a multi-hop wireless network into a shared network infrastructure. Yet, since transmission of each single message involves a flooding process over whole network, it suffers from scalability problems, and hence it is difficult to achieve comparable data transfer capacity, especially for densely deployed network. Furthermore, increasing numbers of transmitting nodes jeopardize the reliability of concurrent transmission. This paper proposes to tackle the problem from the viewpoint of clustering. The use of concurrent transmission in clustering-based data collection has not been explored in literature. Herein, a heuristic algorithm is designed from the viewpoints of balance and connectivity to carry out network clustering process. The prototype is implemented on Tmote Sky sensor node with Contiki operating system. The efficiency has been verified with almost 100% data collection on a deployed testbed consisting of 30 sensor nodes. Extensive simulations are also conducted to investigate the protocol performance in a fine-grained way.
References
[1]
O. Zahwe, O. Majed, H. Harb, M. Hamze, and A. Nasser. 2018. A Fast Clustering Algorithm for Analyzing Big Data Generated in Ubiquitous Sensor Networks. In 2018 International Arab Conference on Information Technology (ACIT). 1–6. https://doi.org/10.1109/ACIT.2018.8672680
[2]
Bradford W. Bazemore and Wenjia Li. 2014. Data Center Heat Monitoring Using Wireless Sensor Networks. In Proceedings of the 2014 ACM Southeast Regional Conference (Kennesaw, Georgia) (ACM SE ’14). Association for Computing Machinery, New York, NY, USA, Article 59, 4 pages. https://doi.org/10.1145/2638404.2675734
[3]
Y. M. Manaserh, M. I. Tradat, G. Mohsenian, B. G. Sammakia, and M. J. Seymour. 2020. General Guidelines for Commercialization a Small-Scale In-Row Cooled Data Center: A Case Study. In 2020 36th Semiconductor Thermal Measurement, Modeling Management Symposium (SEMI-THERM). 48–55. https://doi.org/10.23919/SEMI-THERM50369.2020.9142847
[4]
N. Hadj-Ahmed and C. Pattinson. 2015. Data centre energy efficiency. In 2015 World Congress on Sustainable Technologies (WCST). 108–109. https://doi.org/10.1109/WCST.2015.7415130
[5]
Marcelo da Silva Conterato, Tiago Coelho Ferreto, Fábio Rossi, Wagner dos Santos Marques, and Paulo Silas Severo de Souza. 2019. Reducing Energy Consumption in SDN-Based Data Center Networks through Flow Consolidation Strategies. InProceedings of the 34thACM/SIGAPP Symposium on Applied Computing(Limassol, Cyprus)(SAC ’19). Association for Computing Machinery, New York, NY, USA, 1384–1391. https://doi.org/10.1145/3297280.3297420
[6]
C. Li, J. Li, M. Jafarizadeh, G. Badawy, and R. Zheng. 2019. LEMoNet: low energy wireless sensor network design for data center monitoring. In 2019 IFIP Networking Conference (IFIP Networking). 1–9. https://doi.org/10.23919/IFIPNetworking46909.2019.8999456
[7]
Chieh-Jan Mike Liang, Jie Liu, Liqian Luo, Andreas Terzis, and Feng Zhao. 2009. RACNet: A High-Fidelity Data Center Sensing Network. In Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems (Berkeley, California) (SenSys ’09). Association for Computing Machinery, New York, NY, USA, 15–28. https://doi.org/10.1145/1644038.1644041
[8]
Abusayeed Saifullah, Sriram Sankar, Jie Liu, Chenyang Lu, Ranveer Chandra, and Bodhi Priyantha. 2018. CapNet: Exploiting Wireless Sensor Networks for Data Center Power Capping. ACM Trans. Sen. Netw. 15, 1, Article 6 (Dec. 2018), 34 pages. https://doi.org/10.1145/3278624
[9]
[n. d.]. Wireless Sensor Networks for Data Centers. Retrieved from https://energy.gov/eere/femp/wirelesssensor-networks-data-centers.
[10]
Sukun Kim, Rodrigo Fonseca, Prabal Dutta, Arsalan Tavakoli, David Culler, Philip Levis, Scott Shenker, and Ion Stoica. 2007. Flush: A Reliable Bulk Transport Protocol for Multihop Wireless Networks. In Proceedings of the 5th International Conference on Embedded Networked Sensor Systems (Sydney, Australia) (SenSys ’07). Association for Computing Machinery, New York, NY, USA, 351–365. https://doi.org/10.1145/1322263.1322296
[11]
Bhaskaran Raman, Kameswari Chebrolu, Sagar Bijwe, and Vijay Gabale. 2010. 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 (Zürich, Switzerland) (SenSys ’10). Association for Computing Machinery, New York, NY, USA, 15–28. https://doi.org/10.1145/1869983. 1869986
[12]
Sathiya Kumaran Mani, Ramakrishnan Durairajan, Paul Barford, and Joel Sommers. 2018. An Architecture for IoT Clock Synchronization. In Proceedings of the 8th International Conference on the Internet of Things (Santa Barbara, California, USA) (IOT ’18). Association for Computing Machinery, New York, NY, USA, Article 17, 8 pages. https://doi.org/10.1145/3277593.3277606
[13]
Farzad Asgarian and Khalil Najafi. 2019. Reducing Synchronization Error in Wireless Sensor Nodes by Using Previous Timing Information as Training Data: Poster Abstract. In Proceedings of the 17th Conference on Embedded Networked Sensor Systems (New York, New York) (SenSys ’19). Association for Computing Machinery, New York, NY, USA, 432–433. https://doi.org/10.1145/3356250.3361967
[14]
Linshan Jiang, Rui Tan, and Arvind Easwaran. 2020. Resilience Bounds of Network Clock Synchronization with Fault Correction. ACM Trans. Sen. Netw. 16, 4, Article 38 (Sept. 2020), 30 pages. https://doi.org/10.1145/3409804
[15]
F. Ferrari, M. Zimmerling, L. Thiele, and O. Saukh. 2011. Efficient network flooding and time synchronization with Glossy. In Proceedings of the 10th ACM/IEEE International Conference on Information Processing in Sensor Networks. 73–84
[16]
V. S. Rao, R. V. Prasad, T. V. Prabhakar, C. Sarkar, M. Koppal, and I. Niemegeers. 2019. Understanding and Improving the Performance of Constructive Interference Using Destructive Interference in WSNs.IEEE/ACM Transactions on Networking27, 2 (2019), 505-517.https://doi.org/10.1109/TNET.2019.2893597
[17]
X. Liu. 2015. Atypical Hierarchical Routing Protocols for Wireless Sensor Networks: A Review. IEEE Sensors Journal 15, 10 (2015), 5372–5383. https://doi.org/10.1109/JSEN.2015.2445796
[18]
S. Selvakennedy, S. Sinnappan, and Yi Shang, "T-ANT: A Nature-Inspired Data Gathering Protocol for Wireless Sensor Networks," Journal of Communications, vol. 1, no. 2, pp. 22-29, 2006.
[19]
Yoshiaki Taniguchi, Go Hasegawa and Hirotaka Nakano, "Self-organizing Transmission Scheduling Considering Collision Avoidance for Data Gathering in Wireless Sensor Networks," Journal of Communications, vol. 8, no. 6, pp. 389-397, 2013.
[20]
Raj Anwit and Prasanta K. Jana. 2020. An Efficient Clustering Based Data Collection Using Mobile Sink in Wireless Sensor Networks. In Proceedings of the 21st International Conference on Distributed Computing and Networking (Kolkata, India) (ICDCN 2020). Association for Computing Machinery, New York, NY, USA, Article 6, 5 pages. https://doi.org/10.1145/3369740.3369769
[21]
Yuvaraj Padmanaban and Manimozhi Muthukumarasamy. 2018. Energy-efficient clustering algorithm for structured wireless sensor networks. Iet Networks 7, 4 (2018), 265–272. https://doi.org/10.1049/iet-net.2017.0112
[22]
V. Rajaram, S. Srividhya, N. Kumaratharan, and V. Ganapathy. 2017. Fuzzy logic based unequal clustering in wireless sensor networks for effective energy utilization. In 2017 IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI). 2056–2061. https://doi.org/10.1109/ICPCSI.2017.8392077
[23]
S. H. Sackey, J. A. Ansere, J. H. Anajemba, M. Kamal, and C. Iwendi. 2019. Energy Efficient Clustering Based Routing Technique in WSN using Brain Storm Optimization. In 2019 15th International Conference on Emerging Technologies (ICET). 1–6. https://doi.org/10.1109/ ICET48972.2019.8994740
[24]
Omprakash Gnawali, Rodrigo Fonseca, Kyle Jamieson, David Moss, and Philip Levis. 2009. Collection Tree Protocol. In Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems (Berkeley, California) (SenSys ’09). Association for Computing Machinery, New York, NY, USA, 1–14. https://doi.org/10.1145/1644038.1644040
[25]
J. Polastre, R. Szewczyk, and D. Culler. 2005. Telos: enabling ultra-low power wireless research. In IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005. 364–369. https://doi.org/10.1109/IPSN.2005.1440950
[26]
A. Dunkels, B. Gronvall, and T. Voigt. 2004. Contiki - a lightweight and flexible operating system for tiny networked sensors. In 29th Annual IEEE International Conference on Local Computer Networks. 455–462. https://doi.org/10.1109/LCN.2004.38
[27]
Federico Ferrari, Marco Zimmerling, Luca Mottola, and Lothar Thiele. 2012. Low-Power Wireless Bus. In Proceedings of the 10th ACM Conference on Embedded Network Sensor Systems (Toronto, Ontario, Canada) (SenSys ’12). Association for Computing Machinery, New York, NY, USA, 1–14. https://doi.org/10.1145/2426656.2426658
[28]
M. Suzuki, Y. Yamashita, and H. Morikawa. 2013. Low-Power, End-to-End Reliable Collection Using Glossy for Wireless Sensor Networks.In2013 IEEE 77th Vehicular Technology Conference (VTC Spring). 1–5. https://doi.org/10.1109/VTCSpring.2013.6692624
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February 2021
342 pages
ISBN:9781450389174
DOI:10.1145/3456415
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Published: 06 June 2021
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ICCBN 2021
ICCBN 2021: 2021 9th International Conference on Communications and Broadband Networking
February 25 - 27, 2021
Shanghai, China
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View all- Sandell MRaza UUchida D(2023)SoLiCiT: Synchronous Listen, Code, and Transmit Protocol for Wireless Control ApplicationsIEEE Systems Journal10.1109/JSYST.2023.323677817:3(4212-4223)Online publication date: Sep-2023
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