RETRACTED ARTICLE: Soft computing approach based energy and correlation aware cooperative data collection for wireless sensor network
Energy plays the predominant constraint in wireless sensor network (WSN) hence, an energy and correlation aware cooperative data collection (ECCDC) method of soft computing approach has been discussed in this work. This work is an attempt to maximize the life span of the network by identifying and r...
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| Published in | Journal of ambient intelligence and humanized computing Vol. 12; no. 5; pp. 5297 - 5308 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.05.2021
Springer Nature B.V |
| Subjects | |
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| Abstract | Energy plays the predominant constraint in wireless sensor network (WSN) hence, an energy and correlation aware cooperative data collection (ECCDC) method of soft computing approach has been discussed in this work. This work is an attempt to maximize the life span of the network by identifying and rectifying the major energy exploiting activities of WSN and it also defines a hierarchical network structure with balanced clusters and energy harvesting sensor nodes. These sensor nodes select the Cluster Heads (CHs) among themselves using a low overhead passive clustering approach. The cluster balancing has been performed by acknowledging only the most deserved sensor nodes as their members. The members co-operatively collect the data from the region of interest. During every time slot, the cluster members are chosen for reporting, based on the mutual correlation, link quality of the member with the CH and the residual energy of the member nodes. The fraction of data collected at the CH is then sent through the optimized inter-cluster paths to the sink, wherein the received data are used for estimation, based on the node’s position and correlation pattern. This proposed system of optimize method reduces the energy consumed, due to the transmission of redundant data and the data loss by preferring optimized data paths. |
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| AbstractList | Energy plays the predominant constraint in wireless sensor network (WSN) hence, an energy and correlation aware cooperative data collection (ECCDC) method of soft computing approach has been discussed in this work. This work is an attempt to maximize the life span of the network by identifying and rectifying the major energy exploiting activities of WSN and it also defines a hierarchical network structure with balanced clusters and energy harvesting sensor nodes. These sensor nodes select the Cluster Heads (CHs) among themselves using a low overhead passive clustering approach. The cluster balancing has been performed by acknowledging only the most deserved sensor nodes as their members. The members co-operatively collect the data from the region of interest. During every time slot, the cluster members are chosen for reporting, based on the mutual correlation, link quality of the member with the CH and the residual energy of the member nodes. The fraction of data collected at the CH is then sent through the optimized inter-cluster paths to the sink, wherein the received data are used for estimation, based on the node’s position and correlation pattern. This proposed system of optimize method reduces the energy consumed, due to the transmission of redundant data and the data loss by preferring optimized data paths. |
| Author | Vinodha, R. Durairaj, S. |
| Author_xml | – sequence: 1 givenname: R. surname: Vinodha fullname: Vinodha, R. email: vinodhaphd.2019@gmail.com organization: Department of Electronics and Communication Engineering, ULTRA College of Engineering and Technology – sequence: 2 givenname: S. surname: Durairaj fullname: Durairaj, S. organization: Department of Electrical and Electronics Engineering, Dhanalakshmi Srinivasan Engineering College |
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| Cites_doi | 10.1145/1210669.1210672 10.1007/s12652-018-0901-5 10.3390/s150100248 10.1016/j.adhoc.2014.07.019 10.3390/s150819443 10.1109/TNET.2014.2306592 10.1007/s12652-017-0557-6 10.1016/j.ins.2015.10.004 10.1007/s11768-011-0240-y 10.1016/j.compeleceng.2018.01.013 10.3390/s150614458 10.1016/j.adhoc.2011.08.005 10.1109/COMST.2017.2650979 10.1109/JSEN.2015.2504106 10.1109/TPDS.2014.2312911 10.1109/TMC.2010.264 10.1049/iet-wss.2013.0050 10.1016/j.comcom.2011.09.009 10.1007/s12652-016-0345-8 10.1016/j.compeleceng.2014.07.010 10.1109/TNET.2008.2006818 10.1016/j.rser.2017.03.124 10.1016/j.pmcj.2017.02.005 10.1016/j.comcom.2012.04.007 10.3390/s140712523 10.1109/TPDS.2007.1046 10.1109/TWC.2016.2531041 10.1007/s12652-018-0751-1 10.1109/TVT.2009.2031454 10.1007/s10115-014-0772-9 10.25103/jestr.073.27 10.1007/s12652-018-0885-1 10.1186/1687-1499-2013-85 10.1007/978-3-319-91337-7_32 10.5120/15383-4047 10.1109/JIOT.2018.2878528 10.1002/9780470515181 10.1186/s13638-018-1173-7 10.1109/ICCCN.2012.6289260 |
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| Keywords | Link aware forwarding Energy balancing Energy conservation Soft computing approach Data compression Passive clustering |
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