EEBCDA Co-MIMO scheme for wireless sensor networks

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dc.contributor.author Dhrubo, Tanvir Islam
dc.contributor.author Ahmed, Sarwar
dc.contributor.author Rahman, Rafayat Razi
dc.contributor.author Tholaal, Ahmed
dc.contributor.author Haris, Muhammad
dc.date.accessioned 2017-11-03T06:16:05Z
dc.date.available 2017-11-03T06:16:05Z
dc.date.issued 2016-11-20
dc.identifier.citation [1] I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, ―A survey on sensor networks,‖ IEEE Commun [2] S. Cui, A. J. Goldsmith, and A. Bahai, ―Energy-efficiency of MIMO and cooperative MIMO in sensor networks,‖ IEEE JSAC, vol. 22, no. 6, pp. 1089– 1098, Aug. 2004. [3] J. N. Laneman, D. N. C. Tse, and G. W. Wornell, ―Cooperative diversity in wireless networks: Efficient protocols and outage behavior,‖ IEEE Trans. on Info. Theory, vol. 22, Dec. 2004. [4] W. Heinzelman, A. Chandrakasan, H. Balakrishnan, ―Energyefficient communication protocol for wireless sensor networks‖, in: Proceeding of the Hawaii International Conference System Sciences, Hawaii, January 2000. [5] H. Gou and Y. Yoo, ―An Energy Balancing LEACH Algorithm for Wireless Sensor Networks,‖ Proc. International Conference on Information Technology (ITNG 10), IEEE Press, Dec, 2010, pp. 822-827, doi: 10.1109/ITNG.2010.12 [6] X. Li, N. Li, L. Chen, Y. Shen, Z. Wang, and Z. Zhu, ―An Improved LEACH for Clustering Protocols in Wireless Sensor Networks,‖ Proc.International Conference. Measuring Technology and Mechatronics Automation (ICMTMA 10), IEEE Press, May, 2010, pp. 496-499,doi: 10.1109/ICMTMA.2010.710 51 [7] S. Lindsey, C.S. Raghavendra, ―PEGASIS: power efficient gathering in sensor information systems‖, in: Proceedings of the IEEE Aerospace Conference, Big Sky, Montana, March 2002. [8] D Kumar, TC Aseri, R Patel, EECDA: energy efficient clustering and data aggregation protocol for heterogeneous wireless sensor networks. Int. J. Comput. Commun. Control 6, 113–124 (2011) [9] D Wei, Y Jin, S Vural, K Moessner, R Tafazolli, An energy-efficient clustering solution for wireless sensor networks. Wirel. Commun. IEEE Transac. 10, 3973–3983 (2011) [10] X Min, S Wei-Ren, J Chang-Jiang, Z Ying, Energy efficient clustering algorithm for maximizing lifetime of wireless sensor networks. AEU-Int J. Electron. Commun. 64, 289–298 (2010) [11]R Fengyuan, Z Jiao, H Tao, L Chuang, SKD Ren, EBRP: energybalanced routing protocol for data gathering in wireless sensor networks. IEEE Transac. Parallel. Distrib. Syst. 22, 2108–2125 (2011) [12]D Karaboga, S Okdem, C Ozturk, Cluster based wireless sensor network routing using artificial bee colony algorithm. Wirel. Netw. 18, 847–860 (2012) [13]J Yuea, W Zhang, W Xiao, D Tang, J Tang, Energy efficient and balanced cluster-based data aggregation algorithm for wireless sensor networks. Procedia. Eng. 29, 2009–2015 (2012)CrossRefGoogle Scholar [14]RR Rout, SK Ghosh, Adaptive data aggregation and energy efficiency using network coding in a clustered wireless sensor network: an analytical approach. Comput. Commun. 40, 65–75 (2014). 3/1 52 [15]L Hui, H Uster, Exact and heuristic algorithms for data-gathering clusterbased wireless sensor network design problem. Netw. IEEE/ACM Transac 22, 903–916 (2014) [16]BS Mathapati, SR Patil, VD Mytri, Energy efficient reliable data aggregation technique for wireless sensor networks, in 2012 International Conference on Computing Sciences (ICCS), (Reykjavík, Iceland, 2012), pp. 153-158 [17]JP Sheu, PK Sahoo, CH Su, WK Hu, Efficient path planning and data gathering protocols for the wireless sensor network. Comput. Commun. 33, 398–408 (2010). 2/26 [18]D Ebrahimi, C Assi, Compressive data gathering using random projection for energy efficient wireless sensor networks. Ad Hoc Netw. 16, 105–119 (2014) [19]JK Min, CW Chung, EDGES: Efficient data gathering in sensor networks using temporal and spatial correlations. J. Syst. Softw. 83, 271–282 (2010). 2// [20]W Jin, T Shaojie, Y Baocai, L Xiang-Yang, Data gathering in wireless sensor networks through intelligent compressive sensing, in 2012 Proceedings IEEE INFOCOM, (Toronto, Canada), pp. 603-611, 2012 [21]Y Song, L Liu, H Ma, AV Vasilako, A biology-based algorithm to minimal exposure problem of wireless sensor networks. IEEE Trans. Netw. Serv. Manag. 11, 417–430 (2014) [22]L Liu, Y Song, H Zhang, H Ma, A Vasilakos, Physarum optimization: a biology-inspired algorithm for the Steiner tree problem in networks. IEEE Trans. Comput. 64(3), 819–832 (2013) 53 [23]P Li, S Guo, S Yu, AV Vasilakos, CodePipe: an opportunistic feeding and routing protocol for reliable multicast with pipelined network coding, in 2012 Proceedings IEEE INFOCOM, (2012), pp. 100-108. [24]Y Zeng, K Xiang, D Li, A Vasilakos, Directional routing and scheduling for green vehicular delay tolerant networks. Wire. Net. 19, 161–173 (2013). /02/01 2013 [25]Y Yao, Q Cao, AV Vasilakos, EDAL: an energy-efficient, delay-aware, and lifetime-balancing data collection protocol for wireless sensor networks, in 2013 IEEE 10th International Conference on Mobile Ad-Hoc and Sensor Systems (MASS), (China, 2013), pp. 182-190 [26]K Han, J Luo, Y Liu, AV Vasilakos, Algorithm design for data communications in duty-cycled wireless sensor networks: a survey. IEEE Commun. Mag. 51, 107–113 (2013) [27]L Xiang, J Luo, A Vasilakos, Compressed data aggregation for energy efficient wireless sensor networks, in 2011 8th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON), (Seattle, 2011), pp. 46-54 [28] Jun Yuea, Weiming Zhang, Weidong Xiao, Daquan Tang, Jiuyang Tang ‗‘Energy Efficient and Balanced Cluster-Based Data Aggregation Algorithm for Wireless Sensor Networks,‘‘ProcediaEngineeringVolume 29, 2012, Pages 2009-2015. 2012 International Workshop on Information and Electronics Engineering [29] X. Li, M. Chen and W. Liu, ―Application of STBC-Encoded Cooperative Transmissions in Wireless Sensor Networks,‖ IEEE Signal Processing Letters, vol. 12, Feb, 2005, pp. 134-137, doi: 10.1109/LSP.2004.840870(410) 12 en_US
dc.identifier.uri http://hdl.handle.net/123456789/130
dc.description Supervised by DR. Mohammad Rakibul Islam Department of Electrical and Electronic Engineering Islamic University of Technology, (IUT), Bangladesh Organization of Islamic Cooperation, (OIC) en_US
dc.description.abstract This thesis work is focused on the Cooperative multiple input multiple output (CO-MIMO). In radio, multiple-input and multiple-output, or MIMO , is a method for multiplying the capacity of a radio link using multiple transmit and receive antennas to exploit multipath propagation. At one time, in wireless the term "MIMO" referred to the use of multiple antennas at the transmitter and the receiver. In modern usage, "MIMO" specifically refers to a practical technique for sending and receiving more than one data signal simultaneously over the same radio channel by exploiting multipath propagation. MIMO is fundamentally different from smart antenna techniques developed to enhance the performance of a single data signal, such as beamforming and diversity. MIMO is often traced back to 1970s research papers concerning multi-channel digital transmission systems and interference (crosstalk) between wire pairs in a cable bundle: AR Kaye and DA George (1970), Branderburg and Wyner (1974), and W. van Etten (1975, 1976). Although these are not examples of exploiting multipath propagation to send multiple information streams, some of the mathematical techniques for dealing with mutual interference proved useful to MIMO development. EEBCDA is one of the efficient cluster based to wireless sensor networks (WSN) protocols. It solves unbalanced energy consumption of cluster based networks by clustering based on energy consumption of the clusters. This results in more balanced energy consumption among the clusters. In this thesis we combine EEBCDA with cooperative MIMO to make EEBCDA more energy efficient on longer distances. In EEBCDA MIMO scheme, the residual energy of each node is considered in choosing CHs for clustering and in case of cooperative nodes selection. Simulation results demonstrate that this results less energy consumption and in turn better overall life time of nodes EEBCDA SISO. en_US
dc.language.iso en en_US
dc.publisher IUT, EEE en_US
dc.title EEBCDA Co-MIMO scheme for wireless sensor networks en_US
dc.type Thesis en_US


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