Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
Wireless sensor networks (WSNs) are usually a resource constrained networks which have limited energy, bandwidth, processing power, memory etc. These networks are now part of Internet by the name Internet of Things (IoT). To get many services from WSNs, we may need to run many applications in the sensor nodes which consumes resources. Ideally, the resources availability of all sensor nodes should be known to the sink before it requests for any further service(s) from the sensor node(s). Hence, continuous monitoring of the resources of the sensor nodes by the sink is essential. The proposed work is a framework for monitoring certain important resources of sensor network using Adaptive-Neuro Fuzzy Inference System (ANFIS) and Constrained Application Protocol (CoAP). The ANFIS is trained with these resources consumption patterns. The input to ANFIS is the resources consumption levels and the output is the resources consumed levels that needs to be sent to the sink which may be individual or combinations of resources. The trained ANFIS generates the output periodically which determines resources consumption levels that needs to be sent to the sink. Also, ANFIS continuously learns using hybrid learning algorithm (which is basically a combination of back propagation and least squares method) and updates its parameters for better results. The CoAP protocol with its observe option is used to transport the resource monitoring data from the sensor nodes to the cluster head, then from the cluster head to the sink. The sensor nodes runs coap server, the cluster head runs both coap client and server and the sink runs coap client. The performance of the proposed work is compared with LoWPAN network management protocol (LNMP) and EmNets Network Management Protocol (EMP) in terms of bandwidth and energy overheads. It is observed that proposed work performs better when compared to the existing works.
Wydawca
Czasopismo
Rocznik
Tom
Strony
41--67
Opis fizyczny
Bibliogr. 22 poz., rys., tab.
Twórcy
autor
- Department of Electronics and Instrumentation Engineering JSS Academy of Technical Education, Bengaluru, India
autor
- School of Computing and Information Technology Reva University, Bengaluru, India
Bibliografia
- 1. Ian. F. Akyildiz, Weillan Su, Yogesh Sankarasubramaniam and Erdal Cayirci, 2002, A Survey on Sensor Networks, IEEE Communication Magazine Vol.40, No.8, pp.102-114.
- 2. Zack Shelby, 2010. Embedded Web Services, IEEE Wireless Communications, Vol.17, No.6, pp.52-57.
- 3. Jyh-shing Roger Jang, 1993, ANFIS: Adaptive network base Fuzzy Inference System, IEEE Transactions on Systems, Man and Cybernetics Vol.23, No.03, pp.665-685
- 4. Shelby Z., Hartke K. and Bormann C., 2014, The IETF's, The Constrained Application Protocol, https://datatracker.ietf.org/doc/rfc7252/
- 5. Hartke K., 2015, Observing Resources in the Constrained Application Protocol (CoAP), http://www.rfc-editor.org/info/rfc7641/
- 6. Yonggang Jerry Zhao, Ramesh Govindhan and Deborah Estrin, 2002, Residual Energy scan for Monitoring Sensor Networks, https://escholarship.org/uc/item/2st0t8cf
- 7. Raquel A. F. Mini, Max do Val Machado, Antonio A. F. Loureiro and Badri Nath, 2005, Prediction - based energy map for wireless sensor networks, Ad Hoc Networks, Vol 3, No. 2, pp. 235-253
- 8. Edward Chan and Song Han, 2009, Energy Efficient Residual Energy Monitoring in Wireless Sensor Networks, International Journal of Distributed Sensor Networks, Vol 5, pp. 748-770
- 9. Alec Woo, Terence Tong and David Culler, 2003, Taming the Underlying Challenges of Reliable Multihop Routing in Sensor Networks, SenSys' 03, November 5-7, 2003, Los Angeles, California, USA.
- 10. Chieh-Yih, Shane B. Eisenman and Andrew T. Campbell, 2003, CODA:Congestion Detection and Avoidance in Sensor Networks, SenSys' 03, November 5-7, 2003, Los Angeles, California, USA.
- 11. Li Qiang Tao and Feng Qi Yu, 2010, ECODA:enhanced congestion detection and avoidance for multiple class of traffic in sensor networks, IEEE Transaction on Consumer Electronics, Vol 56, No. 3, pp.1387-1394
- 12. Falko Dressler and Dominik Neuner, 2013, Energy-Efficient Monitoring of Distributed System Resources for Self-Organizing Sensor Networks, IEEE Topical conference on wireless sensors networks (WiSNET), Jan 20-23, 2013 Austin, TX, PP.145-147
- 13. Winnie Louis Lee, Amitava Datta and Rachel Cardell-Oliver, 2007, Network Management in Wireless Sensor Networks, https://cpn.unl.edu/
- 14. Hamid Mukhtar, Kim Kang-Myo, Shafique Ahmad Chaudhry, Ali Hammad Akbar, Kim Ki-Hyung, Seung-Wha Yoo, 2008, LNMP-Management architecture of IPv6 based low-power wireless Personal Area Networks (6LoWPAN), IEEE Network operations and Management Symposium, April 7-11 2008, Salvador Bahia, pp.417-424
- 15. Shafique Ahmad Chaudhry, Weiping Song, Muhammad Habeeb Vulla, Cormac Sreenan, 2011, EMP:A Protocol for IP Based Wireless Sensor Networks Management, Journal of Ubiquitous Systems and Pervasive Networks, Vol. 2, No. 1, pp. 15-22.
- 16. Zhengguo Sheng, Hao Wang, Changchuan Yin, Xiping Hu, Shusen Yang, Victor C. M. Leung, 2015, Lightweight Management of Resource Constrained Sensor Devices in Internet of Things, IEEE Internet of Things Journal, Vol. 2, No.5, pp. 402-411.
- 17. Nagesha and Sunilkumar S. Manvi, 2016, ANFIS based Resource Mapping for Query Processing in Wireless Multimedia Sensor Networks, Journal of Intelligent Systems, accepted, http://www.degruyter.com/printahead/j/jisys
- 18. Maria Rita Palattella, Nicola Accettura, Xavier Vilajosana, Thomas Watteyne, Luigi Alfredo Grieco, Gennaro Boggia, Mischa Dohler, 2013, Standardized protocol stack for the Internet of (Important) Things, IEEE Communication Surveys and Tutorials, Vol. 15, No. 3, pp.1389-1406.
- 19. Wireless personal area network (WPAN) working group, 2011, Low-Rate Wireless Personal Area Networks (LR-WPANs), http://standards.ieee.org.
- 20. Kushalnagar N., Montenegro G. and Schumacher C., 2007, IPv6 over LowPower Wireless Personal Area Networks (6LoWPANs): Overview, Assumptions, problem Statement, and Goals, https://datatracker.ietf.org/doc/rfc4919/
- 21.Winter,T., Thubert,P., Brandt,A., Hui,J., Kelsey,R., Levis,P., Pister,K., Struik,R., JP.Vasseur and Alexander,R., 2012, RPL:IPv6 Routing Protocol for LowPower and Lossy Networks, https://datatracker.ietf.org/doc/rfc6550/
- 22.Tomohiro Takagi and Michio Sugeno, 1985, Fuzzy Identification of Systems and its Application to Modelling and Control, IEEE Transactions on Systems, Man and Cybernetics, Vol. 15, pp.116-132
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-e78b5992-451d-4926-b66b-d4012b65aab4