Refine your search
Collections
Journals
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Sonavane, Santosh S.
- Energy-Efficient Routing in Wireless Sensor Networks with Improved Network Life
Abstract Views :134 |
PDF Views:3
Authors
Affiliations
1 Maharashtra Academy of Engineering, Alandi(D), Pune, IN
2 Electronics Engg. Dept. with Maharashtra Academy of Engineering, Alandi (D), Pune, IN
1 Maharashtra Academy of Engineering, Alandi(D), Pune, IN
2 Electronics Engg. Dept. with Maharashtra Academy of Engineering, Alandi (D), Pune, IN
Source
Wireless Communication, Vol 3, No 7 (2011), Pagination: 541-545Abstract
Nowadays maintaining neighbourhood information for packet forwarding can achieve a high efficiency in geographic routing, but may not be appropriate for wireless sensor networks in highly dynamic scenarios where network topology changes frequently due to nodes mobility and availability. Geographic routing is an attractive localized routing scheme for wireless sensor networks (WSNs) due to its desirable scalability and efficiency. We propose an online routing scheme, which can provide loop-free, fully stateless, energy-efficient and beaconless sensor-to-sink routing at a low communication overhead without the help of prior neighbourhood knowledge. In this algorithm, each node first calculates its ideal next-hop relay position on the straight line toward the sink based on the energy-optimal forwarding distance, and each forwarder selects the neighbour closest to its ideal next-hop relay position as the next-hop relay using the Request-To-Send/Clear-To-Send (RTS/CTS) handshaking mechanism. At the same time, we also estimate the energy level of that particular node which will be the best next hop relay, whether it has sufficient energy to transmit or not.Keywords
Wireless Sensor Networks, Beaconless Geographic Routing, Energy-Efficient, Power-Aware Routing.
- Survey on Data Reduction Techniques for Energy Conservation for Prolonging Life of Wireless Sensor Network
Abstract Views :242 |
PDF Views:2
Authors
Affiliations
1 Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu, IN
2 Department of Electrical and Communication Engineering, Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu
3 Department of Information Technology, Government College of Engineering, Vidya Nagar, Karad, Dist. Satara, Maharashtra, IN
4 Department of Electronics and Telecommunication Engineering, Dr. D. Y. Patil Knowledge City, Charholi (Bk), Via. Lohegaon, Pune- 412 105, Maharashtra, IN
1 Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu, IN
2 Department of Electrical and Communication Engineering, Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu
3 Department of Information Technology, Government College of Engineering, Vidya Nagar, Karad, Dist. Satara, Maharashtra, IN
4 Department of Electronics and Telecommunication Engineering, Dr. D. Y. Patil Knowledge City, Charholi (Bk), Via. Lohegaon, Pune- 412 105, Maharashtra, IN
Source
Wireless Communication, Vol 10, No 2 (2018), Pagination: 17-25Abstract
Now a days, in every research, focus has been given to energy conservation and that is very essential for Wireless Sensor Network too. In the WSN energy need to be utilized properly to prolong the life of the network. The major energy consumed in wireless sensor network will be for transmission of data from source to destination. We need to focus on reduction of such data which is going to transmit from source to destination, which will reduce the energy and that will prolong the life of WSN. In this paper, survey of such research papers has been done which will help to minimize energy consumption. Many research papers are referred and some of the important and related papers are used for the survey. The focus of all the papers is on energy minimization through data mining techniques like data reduction, data compression and data prediction etc.. This survey proves that data mining is one the important techniques which will reduce data transmission and minimizes the energy consumption.Keywords
Data Reduction, Data Prediction, Data Compression, Energy Conservation, Prolonging Life of the Network.References
- M. Arunraja, V. Malathi, E. Sakthivel, Energy Conservation in WSN through Multilevel Data Reduction Scheme, Microprocessors and Microsystems (2015), doi: http://dx.doi.org/10.1016/j.micpro. 2015.05.019.
- Tan, Liansheng, and Mou Wu. "Data reduction in wireless sensor networks: A hierarchical LMS prediction approach." IEEE Sensors Journal 16.6 (2016): 1708-1715.
- M. Arun raja, V. Malathi , "An LMS Based Data Reduction Technique for Energy Conservation in Wireless Sensor Network (WSN)", Int. J. Computer Technology & Applications ,Vol 3 (4), 1569-1576, IJCTA July-August 2012
- Eric J. Msechu, Member, IEEE, and Georgios B. Giannakis, 400 IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 60, NO. 1, JANUARY 2012 Sensor-Centric Data Reduction for Estimation with WSNs via Censoring and Quantization.
- Stojkoska, Biljana, Dimitar Solev, and Danco Davcev. "Data prediction in WSN using variable step size LMS algorithm." Proceedings of the 5th International Conference on Sensor Technologies and Applications. 2011.
- Jun Zhang, Chao Chen, Yang Xiang, Wanlei Zhou, Yong Xiang, “Internet Traffic classification by aggregating correlated Naïve Bayes Predictions”, IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, VOL.8,NO.1, JANUARY 2013
- Ardjan Zwartjes, Paul J.M. Havinga, Gerard J.M. Smit, Johann L. Hurink, “Distribution Bottlenecks in Classification Algorithms”, Second International Symposium on Frontiers in Ambient and Mobile Systems (FAMS-2012), 1877-0509 © 2012, Elsevier, doi: 10.1016/j.procs.2012.06.131.
- Femi A. Aderohunmu, Giacomo Paci, Davide Brunelli, Jeremiah D. Deng, Luca Benini, Martin Purvis, “An Application-specific Forecasting Algorithm for Extending WSN Lifetime”, IEEE International Conference on Distributed Computing in Sensor Systems, © 2013 IEEE, 978-0-7695-504,1-1/13, DOI 10.1109/DCOSS.2013.51.
- Jiangtao Ren_, Sau Dan Lee , Xianlu Chen, Ben Kao, Reynold Cheng and David Cheung, “Naive Bayes Classification of Uncertain Data”, ICDM’09 Proceedings of the 2009 IEEE International Conference on Data Mining, Pg. 944-949, ISBN: 978-0-7695-3895-2,DOI. 10.1109/ICDM.2009.90.
- Moraru, Alexandra, et al. "Using machine learning on sensor data." CIT. Journal of Computing and Information Technology 18.4 (2010): 341-347.
- Jonathan Gana Kolo, S. Anandan Shanmugan, David Wee Gin Lim, Li-Minn Ang, “Fast and Efficient Lossless Adaptive Compression Scheme for Wireless Sensor Networks”, Elsevier, Computer and Electrical Engineering, June 2014.
- Tommy Szalapski • Sanjay Madria,” On compressing data in wireless sensor networks for energy efficiency and real time delivery”, Springer, Distributed Parallel Databases 31,151–182, 2013.
- Mohamed Abdelaal and Oliver Theel,” An Efficient and Adaptive Data Compression Technique for Energy Conservation in Wireless Sensor Networks”, IEEE Conference on Wireless Sensors, December 2013.
- Massimo Vecchio, Raffaele Giaffreda, and Francesco Marcelloni, “Adaptive Lossless Entropy Compressors for Tiny IoT Devices”, IEEE Transcations on Wireless Communications, Vol. 13, No. 2, Februrary 2014.
- Mohammad Tahghighi, Mahsa Mousavi, and Pejman Khadivi, “Hardware Implementation of Novel Adaptive Version of Deflate Compression Algorithm”, Proceedings of ICEE 2010, May 11-13, 2010.
- Danny Harnik, Ety Khaitzin, Dmitry Sotnikov, and Shai Taharlev, “Fast Implementation of Deflate”, IEEE Data Compression Conference, IEEE Computer Society, 2014.
- Wu Weimin, Guo Huijiang , Hu Yi , Fan Jingbao, and Wang Huan, “Improvable Deflate Algorithm”, 978-1-4244-1718-6/08/$25.00 ©2008 IEEE.
- Chen, Fred, et al. "Energy-aware design of compressed sensing systems for wireless sensors under performance and reliability constraints." Circuits and Systems I: Regular Papers, IEEE Transactions on 60.3 (2013): 650-661.
- Nazim Agoulmine, Carlos Giovanni Nunes de Carvalho, Danielo." Multiple Linear Regression to Improve Prediction Accuracy in WSN Data Reduction “IEEE, 2011.
- C. Guestrin, P. Bodik, R. Thibaux R., M. Paskin and S. Madden: Distributed Regression: an Efficient Framework for Modeling Sensor Network Data". In Proceedings of the 3rd International Symposium on Information processing in Sensor Networks (IPSN ’04), Berkeley, USA, April 2004.
- Amirmohammad Rooshenas, Hamid R. Rabiee , Ali Movaghar , M. Yousof Naderi, "Reducing The Data Transmission in Wireless Sensor Networks Using The Principal Component Analysis", sixth international conference on intelligent sensor, sensor network , information processing.
- Benazir Fateh, Manimaran Govindarasu, “Energy minimization by exploiting data redundancy in real-time wireless sensor networks”, Ad Hoc Networks,©2013 Elsevier, vol. 11, 1715–1731.
- Syed Misbahuddin, Jahinger H. Sarkar and Muhammad T. Simsim, “On the Throughput Maximization of Sensor Networks using Data Aggregation and Reduction”, International Conference on Collaboration Technologies and Systems (CTS), 2013 IEEE, 978-1-4673-6404-1/13, DOI: 10.1109/CTS.2013.6567215.
- Chen, Zhiliang, Alexander Kuehne, and Anja Klein. "Reducing aggregation bias and time in gossiping-based wireless sensor networks." Signal Processing Advances in Wireless Communications (SPAWC), 2013 IEEE 14th Workshop on. IEEE, 2013.
- Cheng, Jie, et al. "STCDG: An efficient data gathering algorithm based on matrix completion for wireless sensor networks." Wireless Communications, IEEE Transactions on 12.2 (2013): 850-861.
- Vy, Vuong Dao, et al. "Data reduction algorithms for wireless sensor networks in environment monitoring and warning applications." Computational Intelligence, Modelling and Simulation (CIMSiM), 2012 Fourth International Conference on. IEEE, 2012.
- Zhang, Qingquan, et al. "Cooperative data reduction in wireless sensor network." Global Communications Conference (GLOBECOM), 2012 IEEE. IEEE, 2012.
- Abdel-Aal, Mohamed O., et al. "Energy saving and reliable data reduction techniques for single and multi-modal WSNs." Engineering and Technology (ICET), 2012 International Conference on. IEEE, 2012.
- Pramod D. Ganjewar, Sanjeev J. Wagh and Barani S., “Threshold Based Data Reduction Technique (TBDRT) For Minimization of Energy Consumption in WSN”, Pg. No. 619 – 623, IEEE International Conference on Energy Systems and Applications (ICESA-2015), Organized by Department of Electrical Engineering, Dr. D. Y. Patil Vidya Pratishthan Society’s Dr. D. Y. Patil Institute of Engineering and Technology, Pimpri, Pune – 411018, Maharashtra, India, in association with Institute of Electrical and Electronics Engineers (IEEE), Pune Section, held from 30th October 2015 to 1st November 2015. ISBN Proceeding : 978-1-4673-6817-9/15/$31.00 ©2015 IEEE.
- Pramod Ganjewar, Barani S., S. J. Wagh, “Threshold Based Data Reduction for Prolonging Life of Wireless Sensor Network”, International Journal on AdHoc Networking Systems (IJANS), Vol. 7, No. 1/2/3, Pg. No. 01 – 08, DOI - 10.5121/ijans.2017.7301, ISSN : 2249 – 0175 [Online], 2249 – 2682 [Print].
- Pramod D. Ganjewar, Barani S., Sanjeev J. Wagh, “Data Reduction using Incremental Naïve Bayes Prediction (INBP) in WSN”, IEEE International Conference on Information Processing (ICIP) 2015, Organized by Department of Electronics Engineering, Vishwakarma Institute of Technology, Bibwewadi, Pune, Pune – 411037, Maharashtra, India, in association with Institute of Electrical and Electronics Engineers (IEEE), Pune Section, held from 16th To 19th December 2015. ISBN Proceeding: 978-1-4673-7758-4/15$31.00 ©2015 IEEE.
- Pramod D. Ganjewar, Barani S., Sanjeev J. Wagh, “Energy Efficient Deflate (EEDeflate) Compression For Energy Conservation in Wireless Sensor Network”, Springer International Publishing Ag 2016, Intelligent Systems Technologies and Applications 2016 (ISTA 2016), Advances in Intelligent Systems and Computing 530, DOI – 10.1007/978-3-319-47952-1_22.
- Pramod Ganjewar, Barani S., S. J. Wagh, “HFBLMS : Hierarchical Fractional Bidirectional Least –Mean - Square Prediction Method for Data Reduction in Wireless Sensor Network”, International Journal of Modeling, Simulation and Scientific Computing, Nov. 2017, ISSN : 1793 - 9623, 1793 - 9615.
- Barani, S.,Gomathy, C. Impact of radio propagation model for Fuzzy Based Energy Aware Dynamic Path Route (FEADR) 2011 International Conference on Emerging Trends in Electrical and Computer Technology, ICETECT 2011 23-24 March 2011.
- DAS, S.,BARANI, S.,WAGH, S.,SONAVANE, S.S. Extending lifetime of wireless sensor networks using multi-sensor data fusion Sadhana - Academy Proceedings in Engineering Sciences Article in Press.
- Das, S.,Barani, S.,Wagh, S.,Sonavane, S.S. Energy efficient and trustable routing protocol for Wireless Sensor Networks based on Genetic Algorithm (E2TRP) International Conference on Automatic Control and Dynamic Optimization Techniques, ICACDOT 2016.
- Durbhaka, G.K.,Barani, S. Fault behaviour pattern analysis and recognition Proceedings - 2016 International Conference on Information Science, ICIS 2016.
- Paranjape, S.,Barani, S.,Sutaone, M.,Mukherji, P. Intra and inter cluster congestion control technique for mobile wireless sensor networks Conference on Advances in Signal Processing, CASP 2016 9-11 June 2016.
- Das, S.,Barani, S.,Wagh, S.,Sonavane, S.S. Energy aware routing based on multi-sensor data fusion for wireless sensor networks Communications in Computer and Information Science.
- Shanmugavel, B.,Roslin, E.,Chidambaram, G. Humidity measurement using an efficient topology control and energy aware routing for wireless sensor network Asian Journal of Scientific Research 2014 7 (4) 601-608.