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Cross-Layer MAC Protocol for Semantic Wireless Sensor Network

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Abstract

Wireless sensor networks (WSN) are ad-hoc wireless networks used in many domains involving the analysis of various properties. Along with the growth in the number of deployments of WSNs, there has been an increase in the size of the networks as well. These systems tend to generate a tremendous amount of data that require further processing and analysis. Transmission of data requires a huge amount of energy considering that the components are powered by tiny batteries with a short life cycle. Consequently, energy efficiency is a dominant factor in the performance measure of WSNs. One major contributor to the overall energy consumption of a WSN is overhearing, a condition, in which the same data is picked up and transmitted by multiple nodes. Reducing overhearing results in a marked decrement in energy usage. This paper proposes to use semantic technology for the observation and collection of sensor data. With the use of an ontology, sensor nodes can be remarkably interoperable and configurable in the receipt and transmission of semantic data. Using this interoperability, we introduce asynchronous semantic preamble listening to avoid overhearing in a semantic sensor network. Performance comparisons to LPL by real experiments show stark improvements in energy consumption.

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References

  1. Ajigboye, O. S., & Danas, K. (2016). Towards semantics in wearable sensors: The role of transducers electronic data sheets (teds) ontology in sensor networks. In 2016 IEEE 18th international conference on e-Health networking, applications and services (Healthcom) (pp. 1–6).

  2. Bispo, K. A., Rosa, N. S., & Cunha, P. R. F. (2012). A semantic solution for saving energy in wireless sensor networks. In 2012 IEEE symposium on computers and communications (ISCC) (pp. 492–499).

  3. Chaochaisit, W., Bessho, M., Koshizuka, N., & Sakamura, K. (2016). Human localization sensor ontology: Enabling owl 2 dl-based search for user’s location-aware sensors in the iot. In 2016 IEEE tenth international conference on semantic computing (ICSC) (pp .107–111).

  4. Das, S., Bhowmik, S., & Giri, C. (2017). Design of asynchronous semantic preamble listening for semantic sensor network to avoid early overhearing. In 2017 International conference on wireless communications, signal processing and networking (WiSPNET) (pp. 420–424).

  5. Das, S., Bhowmik, S., & Giri, C. (2017). End device energy optimization in aspl for semantic sensor network. In 2017 IEEE international conference on advanced networks and telecommunications systems (ANTS) (pp. 1–6).

  6. Dey, S., Jaiswal, D., Dasgupta, R., & Mukherjee, A. (2015). Organization and management of semantic sensor information using SSN ontology: An energy meter use case. In 2015 9th International conference on sensing technology (ICST) (pp. 468–473).

  7. El-Hoiydi, A. (2002). Aloha with preamble sampling for sporadic traffic in ad hoc wireless sensor networks. In 2002 IEEE international conference on communications conference proceedings (ICC 2002) (Cat. No. 02CH37333) (Vol. 5, pp. 3418–3423).

  8. Ganeriwal, S., Ganesan, D., Shim, H., Tsiatsis, V., & Srivastava, B. M. (2005). Estimating clock uncertainty for efficient duty-cycling in sensor networks. ACM SenSys, 56, 130–141.

    Google Scholar 

  9. Hill, J. L., & Culler, D. E. (2002). Mica: A wireless platform for deeply embedded networks. IEEE Micro, 22(6), 12–24.

    Article  Google Scholar 

  10. Hu, S. C., Tsai, C. H., Lu, Y. C., Pan, M. S., & Tseng, Y. C. (2016). An energy-efficient multicast protocol for zigbee-based networks. In 2016 IEEE wireless communications and networking conference (pp. 1–6).

  11. Hu, S., & Motani, M. (2008). Early overhearing avoidance in wireless sensor networks (pp. 26–35). Springer.

  12. Kaed, El., Charbel, Khan, Imran, Van Den, Berg, Andre, Hossayni, Hicham, & Saint-Marcel, Christophe. (2018). Sre: Semantic rules engine for the industrial internet-of-things gateways. IEEE Transactions on Industrial Informatics, 14(2), 715–724.

    Article  Google Scholar 

  13. Polastre, J., Hill, J., & Culler, D. (2004). Versatile low power media access for wireless sensor networks. In The second international conference on embedded networked sensor systems (SenSys04) (pp. 95–107).

  14. Pu, F., Wang, Z., Du, C., Zhang, W., & Chen, N. (2016). Semantic integration of wireless sensor networks into open geospatial consortium sensor observation service to access and share environmental monitoring systems. IET Software, 10(2), 45–53.

    Article  Google Scholar 

  15. Rajendran, V., Obraczka, K., JGarcia-Luna-Aceves, J. (2003). Energy-efficient collision-free medium access control for wireless sensor networks. In ACM SenSys (pp. 181–192).

  16. Rezvan, M., Barekatain, M., Zaeri, A., & Taghandiki, K. (2015). Applying an innovative semantic sensor network model in internet of things. In 2015 International conference on information and communication technology convergence (ICTC) (pp. 324–328).

  17. Sensor Web Enablement Working Group. Sensor alert service. Retrieved March 16, 2018, from http://www.opengeospatial.org/projects/initiatives/sasie.

  18. Sensor Web Enablement Working Group. Sensor model language. March 16, 2018, http://www.opengeospatial.org/standards/sensorml.

  19. Sensor Web Enablement Working Group. Sensor web enablement. Retrieved March 16, 2018, http://www.opengeospatial.org/ogc/markets-technologies/swe.

  20. van Dam, T., & Langendoen, K. (2003). An adaptive energy-efficient mac protocol for wireless sensor networks. ACM SenSys, 56, 171–180.

    Google Scholar 

  21. Xiong, Q., & Li, X. (2014). Cross-layer design of mac and application semantics in wireless sensor networks. In 2014 Fourth international conference on communication systems and network technologies (pp. 147–150).

  22. Ye, W., Heidemann, J. S., & Estrin, D. (2002). An energy-efficient mac protocol for wireless sensor networks. INFOCOM, 56, 1567–1576.

    Google Scholar 

  23. Zhang, K., & Marchiori, A. (2015). Extending semantic sensor networks with queryml. In 2015 IEEE international conference on pervasive computing and communication workshops (PerCom Workshops) (pp. 264–267).

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Authors and Affiliations

  1. Department of IT, Indian Institute of Engineering Science and Technology, Shibpur, Howrah, 711103, India

    Sushovan Das & Chandan Giri

  2. Department of CSE, College of Engineering and Management, Kolaghat, KTPP Township, WB, India

    Suman Bhowmik

Authors
  1. Sushovan Das
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  2. Suman Bhowmik
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  3. Chandan Giri
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Contributions

All authors examined the energy efficiency of a cross-layer MAC protocol for Semantic Wireless Sensor Network based on Low Power Listening.

All authors examined the overall energy optimization for the whole network for a certain time duration. Here authors deployed 20 TelosB motes in the large campus of the institute where one mote is connected to the base station and two nodes are being used in the router node. All of the 17 remaining nodes were deployed in the range of either router 1 or router 2. The experimental results taken for 120, 180, 240, 300, 360, 420 secs time duration where each event occurs at 5 secs interval. The energy optimization examined for all 20 nodes for the certain time intervals.

All authors read and approve the final manuscript.

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Correspondence to Sushovan Das.

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I, Sushovan Das, give my consent for the publication of an original research article entitled “Cross layer MAC protocol for Semantic Wireless Sensor Network” by the Wireless Personal Communications Journal.

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Das, S., Bhowmik, S. & Giri, C. Cross-Layer MAC Protocol for Semantic Wireless Sensor Network. Wireless Pers Commun 120, 3135–3151 (2021). https://doi.org/10.1007/s11277-021-08603-z

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