A Cluster—based Approach for Minimizing Energy Consumption by Reducing Travel Time of Mobile Element in WSN


  • Jangiti Siva Prashanth Academy of Scientific & Innovative Res.,CSIR-IICT campus
  • Satyanarayana V. Nandury Academy of Scientific and Innovative Res., CSIR-IICT Campus, CSIR-Indian Institute of Chemical Technology, Hyderabad, India.


Envoy Nodes, Halting Locations, travel time, latency


Envoy Node Identification (ENI) and Halting Location Identifier (HLI) algorithms have been developed to reduce the travel time of Mobile Element (ME) by determining Optimal Path(OP) in Wireless Sensor Networks. Data generated by cluster members will be aggregated at the Cluster Head (CH) identified by ENI for onward transmission to the ME and it likewise decides an ideal path for ME by interfacing all CH/Envoy Nodes (EN). In order to reduce the tour length (TL) further HLI determines finest number of Halting Locations that cover all ENs by taking transmission range of CH/ENs into consideration. Impact of ENI and HLI on energy consumption and travel time of ME have been examined through simulations.

Author Biography

Jangiti Siva Prashanth, Academy of Scientific & Innovative Res.,CSIR-IICT campus



Agarwal, A.; Gupta, K.; Yadav, K.P. (2016). A novel energy efficiency protocol for WSN based on optimal chain routing, 2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom), IEEE, 368-373, 2016.

Al-Tabbakh, S.M. (2017). Novel technique for data aggregation in wireless sensor networks, 2017 International Conference on Internet of Things, Embedded Systems and Communications (IINTEC), IEEE, 1-8, 2017. https://doi.org/10.1109/IINTEC.2017.8325904

Amarlingam, M.; Mishra, P. K.; Rajalakshmi, P.; Giluka, M.K.; Tamma, B.R. (2018). Energy efficient wireless sensor networks utilizing adaptive dictionary in compressed sensing, 2018 IEEE 4th World Forum on Internet of Things (WF-IoT), 383-388, 2018. https://doi.org/10.1109/WF-IoT.2018.8355140

Begum, B.A.; Satyanarayana, N.V. (2015). Composite interference mapping model for interference fault-free transmission in WSN, 2015 International Conference on Advances in Computing, Communications and Informatics (ICACCI), IEEE, 2118-2125,2015. https://doi.org/10.1109/ICACCI.2015.7275930

Chaudhari, M.;Koleva, P.; Poulkov, V.; Deshpande, V. (2017). Energy efficient reliable data transmission in resource constrained ad-hoc communication networks, 2017 Global Wireless Summit (GWS), IEEE, 17-21, 2017. https://doi.org/10.1109/GWS.2017.8300500

Chen, T.C.; Chen, T.S.; Wu, P.W. (2008). Data collection in wireless sensor networks assisted by mobile collector, 2008 1st IFIP Wireless Days, IEEE, 1-5, 2008.

Chiu, K.-M.; Liu, J.-S. (2011). Robot routing using clustering-based parallel genetic algorithm with migration, 2011 IEEE Workshop on Merging Fields of Computational Intelligence and Sensor Technology, IEEE, 42-49, 2011. https://doi.org/10.1109/MFCIST.2011.5949511

Cirstea, C.; Davidescu, R.; Jianu, A. (2013. Optimum communication paths for mobile WSNs using genetic algorithms, 2013 36th International Conference on Telecommunications and Signal Processing (TSP), IEEE, 299-303, 2013. https://doi.org/10.1109/TSP.2013.6613940

Devendra Rao, B.V.; Vasumathi, D.; Nandury, S. V. (2015). Exploiting Common Nodes in Overlapped Clusters for Path Optimization in Wireless Sensor Networks, Proceedings of the Second International Conference on Computer and Communication Technologies: IC3T 2015, Springer, 3, 209, 2015. https://doi.org/10.1007/978-81-322-2526-3_23

Diaz, S.; Mendez, D. (2019). Dynamic minimum spanning tree construction and maintenance for Wireless Sensor Networks, Revista Facultad de Ingeniería, 93, 57-69, 2019. https://doi.org/10.17533/10.17533/udea.redin.20190508

He, L.; Pan, J.; Xu, J. (2012). A progressive approach to reducing data collection latency in wireless sensor networks with mobile elements, IEEE Transactions on Mobile Computing, IEEE, 12(7), 1308-1320, 2012. https://doi.org/10.1109/TMC.2012.105

He, L.; Xu, J.; Yu, Y.; Li, M.; Zhao, W. (2009). Genetic algorithm based length reduction of a mobile BS path in WSNs, 2009 Eighth IEEE/ACIS International Conference on Computer and Information Science, IEEE, 797-802, 2009. https://doi.org/10.1109/ICIS.2009.92

Heinzelman, W.R.; Chandrakasan, A.; Balakrishnan, H. (2000). Energy-efficient communication protocol for wireless microsensor networks, Proceedings of the 33rd annual Hawaii international conference on system sciences, IEEE, 2, 1-10, 2000.

Helsgaun, K. (2000). An effective implementation of the Lin-Kernighan traveling salesman heuristic, European Journal of Operational Research, 126(1), 106-130, 2000. https://doi.org/10.1016/S0377-2217(99)00284-2

Jothikumar, C.; Venkataraman, R. (2019). EODC: An Energy Optimized Dynamic Clustering Protocol for Wireless Sensor Networks using PSO Approach, International Journal of Computers Communications & Control, 14(2), 183-198, 2019. https://doi.org/10.15837/ijccc.2019.2.3379

Kakde, K.R.; Kadam, M. (2017) Performance analysis of tree cluster based data gathering for WSNs, 2017 International Conference on Intelligent Computing and Control (I2C2), 1-5, 2017. https://doi.org/10.1109/I2C2.2017.8321864

Konstantopoulos, C.; Pantziou, G.; Gavalas, D.; Mpitziopoulos, A.; Mamalis, B. (2011). A rendezvous-based approach enabling energy-efficient sensory data collection with mobile sinks, IEEE Transactions on Parallel and Distributed Systems, 23, 809-817, 2011. https://doi.org/10.1109/TPDS.2011.237

Liao, W.-H.; Kuai, S.-C. (2017). An Energy-Efficient SDN-Based Data Collection Strategy for Wireless Sensor Networks, 2017 IEEE 7th International Symposium on Cloud and Service Computing (SC2), 91-97, 2017. https://doi.org/10.1109/SC2.2017.21

Liao, Y.; Qi, H.; Li, W. (2012). Load-balanced clustering algorithm with distributed selforganization for wireless sensor networks, IEEE Sensors Journal, 13, 1498-1506, 2012. https://doi.org/10.1109/JSEN.2012.2227704

Liu, J.-S.; Wu, S.-Y.; Chiu, K.-M. (2013). Path planning of a data mule in wireless sensor network using an improved implementation of clustering-based genetic algorithm, 2013 IEEE Symposium on Computational Intelligence in Control and Automation (CICA), 30-37, 2013. https://doi.org/10.1109/CICA.2013.6611660

Misbahuddin, M.; Putri Ratna, A.A.; Sari, R.F. (2018). Dynamic Multi-hop Routing Protocol Based on Fuzzy-Firefly Algorithm for Data Similarity Aware Node Clustering in WSNs, International Journal of Computers Communications & Control, 13(1), 99-116, 2018. https://doi.org/10.15837/ijccc.2018.1.3088

Prashanth, J.S.; Nandury, S.V.(2015). Cluster-based rendezvous points selection for reducing tour length of mobile element in WSN, 2015 IEEE International Advance Computing Conference (IACC), 1230-1235, 2015. https://doi.org/10.1109/IADCC.2015.7154898

Restuccia, F.; Anastasi, G.; Conti, M.; Das, S.K. (2013). Analysis and optimization of a protocol for mobile element discovery in sensor networks, IEEE Transactions on Mobile Computing, 13(9),1942-1954, 2013. https://doi.org/10.1109/TMC.2013.88

Rubel, M.D.S.I.; Kandil, N.; Hakem, N.; Zuyal, M.D.S.I. (2017). Clustering approach delay sensitive application in wireless sensor network (WSN), 2017 IEEE International Conference on Telecommunications and Photonics (ICTP), 82-86, 2017. https://doi.org/10.1109/ICTP.2017.8285914

Sen, S.; Chowdhury, C.; Neogy, S. (2016). Design of cluster-chain based WSN for energy efficiency, 2016 2nd International Conference on Applied and Theoretical Computing and Communication Technology (iCATccT), 150-154, 2016. https://doi.org/10.1109/ICATCCT.2016.7911982

Singh, V.K.; Kumar, R.; Sahana, S. (2017). To enhance the reliability and energy efficiency of WSN using new clustering approach, 2017 International Conference on Computing, Communication and Automation (ICCCA), 488-493, 2017. https://doi.org/10.1109/CCAA.2017.8229849

Venkataraman, G.; Emmanuel, S.; Thambipillai, S. (2005). DASCA: a degree and size based clustering approach for wireless sensor networks, 2005 2nd International Symposium on Wireless Communication Systems, 508-512, 2005.

Venkataraman, G.; Emmanuel, S.; Thambipillai, S. (2008). Energy-efficient cluster-based scheme for failure management in sensor networks, IET communications, 2(4), 528-537, 2008. https://doi.org/10.1049/iet-com:20070360

Vikram, G.R.; Krishna, A.V.N.; Chatrapati, K.S. (2017). Variable initial energy and unequal clustering (VEUC) based multicasting in WSN, 2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), 82-86, 2017. https://doi.org/10.1109/WiSPNET.2017.8299724

Vinutha, C.B.; Nalini, N.; Veeresh, B.S. (2017). Energy efficient wireless sensor network using neural network based smart sampling and reliable routing protocol, 2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), 2081-2085, 2017. https://doi.org/10.1109/WiSPNET.2017.8300128

Welzl, E. (1991). Smallest enclosing disks (balls and ellipsoids), New results and new trends in computer science, 359-370, 1991. https://doi.org/10.1007/BFb0038202

Xing, G.; Li, Mi.; Wang, T.; Jia, W.; Huang, J. (2011). Efficient rendezvous algorithms for mobility-enabled wireless sensor networks, IEEE Transactions on Mobile Computing, 11(1), 47-60, 2011. https://doi.org/10.1109/TMC.2011.66

Xing, G.; Wang, T.; Jia, W.; Li, Mi. (2008). Rendezvous design algorithms for wireless sensor networks with a mobile base station, Proceedings of the 9th ACM international symposium on Mobile ad hoc networking and computing, 231-240, 2008. https://doi.org/10.1145/1374618.1374650

Xing, G.; Wang, T.; Xie, Z.; Jia, W. (2008). Rendezvous planning in wireless sensor networks with mobile elements, IEEE Transactions on Mobile Computing, 7,1430-1443, 2008. https://doi.org/10.1109/TMC.2008.58

Xu, Ji.; He, L.; Chen, Z.; Huang, G.; Yuan, T. (2008). Reducing the path length of a mobile BS in WSNs, 2008 International Seminar on Future BioMedical Information Engineering, 271-274, 2008. https://doi.org/10.1109/FBIE.2008.56

Xu, R.; Dai, H.; Wang, F.; Jia, Z. (2013). A convex hull based optimization to reduce the data delivery latency of the mobile elements in wireless sensor networks, 2013 IEEE 10th International Conference on High Performance Computing and Communications & 2013 IEEE International Conference on Embedded and Ubiquitous Computing, IEEE, 2245-2252, 2013. https://doi.org/10.1109/HPCC.and.EUC.2013.322



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