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A Novel AEB-AODV Based AADITHYA Cross Layer Design Hibernation Algorithm for Energy Optimization in WSN

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Abstract

Wireless Sensor Networks (WSN) has gained significant importance in current scenario because of its ability to monitor as well as understand the physical environment in terms of different parameters like temperature, humidity, pressure etc. There is a plethora of applications in WSN is finding importance ranking from military tracking, surveillance to environmental exploration and wildlife monitoring. The main challenge in WSN is energy efficiency especially when the capacity of battery and availability of energy source is a constraint. To address some of key WSN challenges, a novel routing protocol, a hibernation algorithm (cross layer design) along with the low power hardware design for achieving energy efficiency are proposed here.Because of the fact that WSN has requirement to adapt itself according to the needs of the dynamically changing environment, the quantity of sensor nodes which are part of routing tree cannot be the same and need to adapt itself so that it can precisely observe and forecast the physical surroundings. Initially the routing protocols being used popularly for WSN network layer i.e. AODV, AOMDV, and DSR are compared. The next stage is a proposal for adaptive model for AODV routing protocol for sensor node selection based on residual energy (AEB-AODV) towards improving the efficiency of energy and Quality of Service depending on the mentioned targets of performance. Here, the scheme utilizes fewer sensor nodes at a time along the route to the destination from the source of the event, and place remaining sensor nodes’ transceivers in the sleep mode but microcontroller, sensors and low power transceivers of the nodes are ON. The last module is a combined model capable of achieving improvements in efficiency of energy–adaptive routing model (AEB-AODV) and Hibernation of the sensor nodesi.e. AADITHYA algorithm, which reduces energy consumption, duty cycle to great extent and improved the latency, implemented with low power ARM CORTEX microcontroller and two sets of transceivers, one active power (AP) for data transmission and another very low power (LP) for sending wake up signals and control signals to the hibernating neighbors. Simulation results of AEB-AODV routing protocol and actual test readings of the developed hardware have shown that this method is effective in optimizing the energy usage in the nodes and hence improves the life expectancy of the WSN used for any general application.

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References

  1. Waltenagus Dargie, Chirstian Poellabauer, Fundamentals of Wireless Sensor Networks, Theory and Practice, Wiley Series on Wireless Communications and Mobile Computing, Wiley Publications.

  2. Kazemsohraby, Daniel Minoli, Taiebznati, Wireless Sensor Networks: Technology, Protocols and Applications, Wiley Publications.

  3. Edgar H. Callaway, Wireless Sensor Networks: Architectures and Protocols. CRC Press, Taylor and Francis Group, Boca Raton.

  4. Yang, Shuang-Hua, Wireless Sensor Networks: Principles, Design and Applications, Signal and Communication Technology, Springer Publications, Heidelberg.

  5. More, A., & Raisinghani, V. (2017). A survey on energy efficient coverage protocols in wireless sensor networks. Journal of King Saud University - Computer and Information Sciences, 29(4), 428–448.

    Article  Google Scholar 

  6. Padmalaya Nayak, & Bhavani Vathasavai. (2017) Energy efficient clustering algorithm for multi-hop wireless sensor network using Type-2 fuzzy logic. IEEE Sensors Journal, 17(14).

  7. Guillaume Terrasson, Renaud Briand, Skandar Basrour, Valérie Dup & Olivier Arrijuria. (2009) Energy model for the design of ultra-low power nodes for wireless sensor networks. Procedia Chemistry, 1, 1195–1198.

  8. Jean Mickael Lebreton, Somasekhar Kandukuri, Nour Murad, Richard Lorion. (2016) An energy-efficient duty-cycled wake-up radio protocol for avoiding overhearing in wireless sensor networks. Wireless Sensor Network, 8, 176–190.

  9. Majid Gholipour, Abolfazl Toroghi Haghighat & Mohammad Reza Meybodi (2015) Hop-by-hop traffic-aware routing to congestion control in wireless sensor networks. EURASIP Journal on Wireless Communications and Networking.

  10. Experimental Assessment of the Battery Lifetime in WSN Based on the Duty-Cycle Current Average Method Wireless Sensor Network, 2014, 6, 212–220, Published Online October 2014.

  11. Adinya John Odey. (2012). Daoliang Li. Low Power Transceiver Design Parameters for Wireless Sensor Networks, Wireless Sensor Network, 4, 243–249.

  12. Ramya, R, Saravana kumar, G., & Ravi, S. (2015) E8MAC protocols for wireless sensor networks. Indian Journal of Science and Technology, 8(34). https://doi.org/10.17485/ijst/2015/v8i34/72318, December 2015.

  13. Vivek Agarwal, Raymond A. De Carlo, & Lefteri H. Tsoukalas (2017) Modeling energy consumption and lifetime of a wireless sensor node operating on a contention-based MAC protocol. IEEE Sensors Journal, 17(16).

  14. Syyed Javad Mohammadi Baygi, Mehran Mokhtar. (2014) Evaluation performance of protocols LEACH, 802.15.4 and CBRP, using analysis of QoS in WSNs. Wireless Sensor Network, 6, 221–236.

  15. Anuradha Pughat, Vidushi Sharma Pughat & Sharma. (2015). A review on stochastic approach for dynamic power management in wireless sensor networks. Human-centric Computing and Information Sciences, 5, (4). https://doi.org/10.1186/s13673-015-0021-6

  16. Sandra Sendra, Jaime Lloret, Miguel García & José F. Toledo. (2011) E12Power saving and energy optimization techniques for Wireless Sensor Networks. Journal Of Communications, 6 (6).

  17. Uma Maheswari, Gnanambigai J. (2011). Energy optimization in wireless sensor network using sleep mode transceiver. Iran University of Science & Technology Global Journal of Research in Engineering Volume 11 Issue 3 Version 1.0 April 2011.

  18. Tommaso Melodia, Dario Pompili, Vehbi C. Gungor, & Ian F. Akyildiz. (2007). Communication and coordination in wireless sensor and actor ntworks. IEEE Transactions On Mobile Computing, 6 (10).

  19. Sofiane Ouni & Zayneb Trabelsi Ayoub. (2013) Predicting communication delay and energy consumption for IEEE 802.15.4/Zigbee Wireless Sensor Networks, International Journal of Computer Networks & Communications (IJCNC), 5 (1). https://doi.org/10.5121/ijcnc.2013.5110 141.

  20. Dan Tudose, Laura Gheorghe, Nicolae Ţăpuş. (2013). Radio Transceiver Consumption Modeling For Multi-Hop Wireless Sensor Networks, U.P.B. Sci. Bull., Series C, Vol. 75, Iss. 1, 2013 ISSN 1454-234x.

  21. Joint Routing and Sleep Scheduling for Lifetime Maximization of Wireless Sensor Networks Article in IEEE Transactions on Wireless Communications, August 2010.

  22. 22.Changming Liu, Cai Fu, Deliang Xu, Lin Sun, & Lansheng Han. (2015) An Energy-Balanced WSN Algorithm Based on Active Hibernation and Data Recovery, Springer International Publishing Switzerland 2015, ICA3PP 2015. Part I, LNCS, 9528, 730–743. https://doi.org/10.1007/978-3-319-27119-4_51

  23. Lindsey, S., & Raghavendra, C. (2002). PEGASIS: Power-Efficient Gathering in Sensor Information Systems. In Proceedings of IEEE Aerospace Conference, USA, Montana, 3, 1125–1130.

  24. Manjeshwar, A., & Agrawal, D. (2002). APTEEN: A Hybrid Protocol for Efficient Routing and Comprehensive Information Retrieval in Wireless Sensor Networks (pp. 195–202). In Proc. International Parallel and Distributed Processing Symposium: Florida.

  25. Yao, Y., & Gehrke, J. (2002). The Cougar approach to in-network query processing in sensor networks. SIGMOD Record, 31(3), 9–18.

    Article  Google Scholar 

  26. Almazaydeh, L., Abdelfattah, E., Al-Bzoor, M., & Al-Rahayfeh, A. (2010). Performance evaluation of routing protocols in wireless sensor networks. Computer Science and Information Technology, 2(2), 64–73.

    Google Scholar 

  27. Ganesan, D., et al. (2001). Highly-resilient, energy-efficient multipath routing in wireless sensor networks. ACM SIGMOBILE Mobile Computing and Communications Review, 5(4), 11–25.

    Article  Google Scholar 

  28. Ma, J., et al. (2007). Energy-efficient opportunistic topology control in wireless sensor networks (pp. 33–38). New York: ACM.

  29. Lu, G. et al (2004) An adaptive Energy-Efficient and Low-Latency MAC for Data Gathering in wireless Sensor Networks. In Proceedings of the 18th International Parallel and Distributed Processing Symposium, IPDPS 04, Santa Fe, NM, USA, 26–30 April, 2004; pp. 224–231.

  30. Rajendran, V. et al (2003) Energy-efficient, collision-free medium access control for wireless sensor networks. In Proceedings of the 1st ACM Conference on Embedded Networked Sensor Systems, SENSYS‟ 03, Los Angeles, CA, USA, 5–7 November 2003; pp. 181–192.

  31. Rakesh Kumar Saini, Sandeep Vijay. (2016). A survey on cross layer design implementation in wireless sensor network. International Journal of Advanced Information Science and Technology, 51, 101–107.

  32. Ram Prasadh Narayanan. (2016). Thazath VeeduSarath, Vellora Veetil Vineeth, Survey on Motes Used in Wireless Sensor Networks: Performance & Parametric Analysis, Wireless Sensor. Network, 8, 51–60.

  33. Pouya Kamalinejad, Kamyar Keikhosravy, Michele Magno, Shahriar Mirabbasi, Victor C. M. Leung, & Luca Benini. (2014). A high-sensitivity fully passive wake-up radio front-end for wireless sensor nodes. IEEE International Conference on Consumer Electronics (ICCE).

  34. Luca Catarinucci, Sergio Guglielmi, Riccardo Colella, & Luciano Tarricone. (2014). Pattern-reconfigurable antennas and smart wake-up circuits to decrease power consumption in WSN Nodes. IEEE Sensors Journal, 14 (12).

  35. Nanda, K., Babu, H., Selvakumar, D., Dwarakanath, T., Nayak, K., & Venkatesh (2014). Smartmote-An innovative autonomous Wireless Sensor Node Architecture, 2014 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT), Bangalore (pp. 1–6). https://doi.org/10.1109/CONECCT.2014.6740350

  36. Mohen Nasri, Amina Msolli, Abdelhamid Helali, Hassen Maaref. (2012). A 2.4-GHz-low-power CMOS RF transmitter for IEEE 802.15.4 Standard Wireless Sensor Network, 4, 173–176.

  37. Takashi Takeuchi, Shintaro Izumi, Takashi Matsuda, Hyeokjong Lee, Toshihiro Konishi, KohTsuruda, Yasuhiro Sakai, Hiroshi Kawaguchi, ChikaraOhta, & Masahiko Yoshimoto. (2009). A Single-Chip Sensor Node LSI with Synchronous MAC Protocol and Divided Data-Buffer SRAM, 978-1-4244-5035-0/09 IEEE, ISOCC 2009, 202–207.

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Authors and Affiliations

  1. Electronics & Telecommunication Department, Dr. D.Y. Patil Institute of Technology, Pimpri, Pune, 411018, India

    Urmila Patil, Anju V. Kulkarni & Mithra Venkatesan

  2. Mathematics Department, Dr. D.Y. Patil Institute of Technology, Pimpri, Pune, 411018, India

    Radhika Menon

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  1. Urmila Patil
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  2. Anju V. Kulkarni
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  3. Radhika Menon
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  4. Mithra Venkatesan
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Patil, U., Kulkarni, A.V., Menon, R. et al. A Novel AEB-AODV Based AADITHYA Cross Layer Design Hibernation Algorithm for Energy Optimization in WSN. Wireless Pers Commun 117, 1419–1439 (2021). https://doi.org/10.1007/s11277-020-07929-4

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