Author Details

Scroll

Refine your search

Collections

Engineering Collection

Co-Authors

Journals

International Journal of Computer Networks and Applications

Year

2020
2021

Authors

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

Gupta, Rajeev

Cluster Head Election in Wireless Sensor Network: A Comprehensive Study and Future Directions

Abstract Views :236 | PDF Views:0

Authors

Rekha ¹, Rajeev Gupta ²

Affiliations
1 Department of Computer Science and Applications, Maharishi Markandeshwar (Deemed to be University), Mullana (Ambala), IN
2 Department of Computer Science and Engineering, Maharishi Markandeshwar (Deemed to be University), Mullana (Ambala), IN

Source

International Journal of Computer Networks and Applications, Vol 7, No 6 (2020), Pagination: 178-192

Abstract

Due to the advancement of wireless communication interchanges, electronic technology, and micro-electromechanical devices, Wireless Sensor Network (WSN) has got advanced as a promising zone of research. WSN consists of a collection of sensor nodes having a little calculative capability, limited memory, and constrained energy assets. Clusters are formed from the collection of sensor nodes whose leader node (Cluster head) can send the sensed information from hubs to the BS. To condense the power consumption and boost group longevity, the cluster head executes data accumulation. This paper discusses many algorithms based on deterministic, probabilistic, adaptive, fuzzy logic, and Multi-attribute decisionmaking techniques for clustering and cluster head election. Existing algorithms enhance the network lifetime and energy efficiency but fail to provide a better quality of service and security. So many issues and challenges have been laid down and it is concluded that when computational intelligence is combined with network intelligence then QoS and security both can be provided along with the network longevity and energy efficiency in homogeneous as well as a heterogeneous environment.

Keywords

Wireless Sensor Network (WSN), Deterministic Schemes, Adaptive, Schemes, Probabilistic Schemes, Multi- Attribute Decision Making Schemes (MADM), Fuzzy Based Cluster Head Election Schemes.

Full Text

References

Y. Al-obaisat and R. Braun, “On Wireless Sensor Networks : Architectures, Protocols, Applications , and Management Routing Protocols for WSNs,” in Proceedings of the 2nd international conference on wireless broadband and ultra wideband communication (AusWireless), 2007, pp. 1–11.

T. M. Behera, S. K. Mohapatra, U. C. Samal, M. S. Khan, M. Daneshmand, and A. H. Gandomi, “Residual Energy Based Cluster-head Selection in WSNs for IoT Application,” IEEE Internet Things J., vol. 6, no. 3, pp. 5132–5139, 2019.

B. K. Debroy, M. S. Sadi, and M. Al Imran, “An efficient approach to select cluster head in Wireless Sensor Networks,” J. Commun., vol. 6, no. 7, pp. 529–539, 2011, doi: 10.4304/jcm.6.7.529-539.

P. K. Batra and K. Kant, “LEACH-MAC: a new cluster head selection algorithm for Wireless Sensor Networks,” J. Wirel. Networks, vol. 22, no. 1, pp. 49–60, 2016, doi: 10.1007/s11276-015-0951-y.

A. Abed, A. Alkhatib, and G. S. Baicher, “Wireless Sensor Network Architecture,” in International Conference on Computer Networks and Communication Systems, 2012, vol. 35, no. Cncs2012, pp. 11–15.

A. Zeb et al., “Clustering Analysis in Wireless Sensor Networks: The Ambit of Performance Metrics and Schemes Taxonomy,” Int. J. Distrib. Sens. Networks, vol. 12, no. 7, pp. 1–24, 2016, doi: 10.1177/155014774979142.

S. R. Jino Ramson and D. Jackuline Moni, “Applications of Wireless Sensor Networks - A survey,” Proc. IEEE Int. Conf. Innov. Electr. Electron. Instrum. Media Technol. ICIEEIMT 2017, vol. 2017-Janua, no. July, pp. 325–329, 2017, doi: 10.1109/.2005.1467103.

A. A. Abbasi and M. Younis, “A survey on clustering algorithms for wireless sensor networks,” Comput. Commun., vol. 30, no. 14–15, pp. 2826–2841, 2007, doi: 10.1016/j.comcom.2007.05.024.

S. Verma, N. Sood, and A. K. Sharma, “Genetic Algorithm-based Optimized Cluster Head selection for single and multiple data sinks in Heterogeneous Wireless Sensor Network,” Appl. Soft Comput. J., vol. 85, p. 105788, 2019, doi: 10.1016/j.asoc.2019.105788.

L. Xu, R. Collier, and G. M. P. O’Hare, “A Survey of Clustering Techniques in WSNs and Consideration of the Challenges of Applying Such to 5G IoT Scenarios,” IEEE Internet Things J., vol. 4, no. 5, pp. 1229–1249, 2017, doi: 10.1109/JIOT.2017.2726014.

S. Aslam, N. U. Hasan, J. W. Jang, and K. G. Lee, “Optimized energy harvesting, cluster-head selection and channel allocation for IoTs in smart cities,” Sensors (Switzerland), vol. 16, no. 12, 2016, doi: 10.3390/s16122046.

P. Porambage, C. Schmitt, P. Kumar, A. Gurtov, and M. Ylianttila, “PAuthKey: A Pervasive Authentication Protocol and Key Establishment Scheme for Wireless Sensor Networks in Distributed IoT Applications,” Int. J. Distrib. Sens. Networks, vol. 2014, 2014, doi: 10.1155/2014/357430.

W. R. Heinzelman, A. Chandrakasan, and H. Balakrishnan, “Energy-efficient communication protocol for wireless microsensor networks,” Proc. 33rd Annu. Hawaii Int. Conf. Syst. Sci., vol. 1, pp. 1–10, 2000, doi: 10.1109/HICSS.2000.926982.

S. V. Manikanthan and T. Padmapriya, “An efficient cluster head selection and routing in mobile WSN,” Int. J. Interact. Mob. Technol., vol. 13, no. 10, pp. 56–70, 2019, doi: 10.3991/ijim.v13i10.11303.

A. A. Baradaran and K. Navi, “HQCA-WSN: High-quality clustering algorithm and optimal cluster head selection using fuzzy logic in wireless sensor networks,” Fuzzy Sets Syst., vol. 389, pp. 114–144, 2020, doi: 10.1016/j.fss.2019.11.015.

X. Yuan, M. Elhoseny, H. K. El-Minir, and A. M. Riad, “A Genetic Algorithm-Based, Dynamic Clustering Method Towards Improved WSN Longevity,” J. Netw. Syst. Manag., vol. 25, no. 1, pp. 21–46, 2017, doi: 10.1007/s10922-016-9379-7.

M. Elhoseny, X. Yuan, Z. Yu, C. Mao, H. K. El-Minir, and A. M. Riad, “Balancing energy consumption in heterogeneous wireless sensor networks using genetic algorithm,” IEEE Commun. Lett., vol. 19, no. 12, pp. 2194–2197, 2015, doi: 10.1109/LCOMM.2014.2381226.

M. Wu, H. Liu, and Q. Min, “Lifetime enhancement by cluster head evolutionary energy efficient routing model for WSN,” in 6th International Conference on Instrumentation and Measurement, Computer, Communication and Control, IMCCC 2016, 2016, pp. 545–548, doi: 10.1109/IMCCC.2016.86.

K. N. Dattatraya and K. R. Rao, “Hybrid based cluster head selection for maximizing network lifetime and energy efficiency in WSN,” J. King Saud Univ. - Comput. Inf. Sci., no. xxxx, 2019, doi: 10.1016/j.jksuci.2019.04.003.

P. L. Rajarajeswari and N. K. Karthikeyan, “Hyper-geometric energy factor based semi-Markov prediction mechanism for effective cluster head election in WSNs,” J. Intell. Fuzzy Syst., vol. 32, no. 4, pp. 3111–3120, 2017, doi: 10.3233/JIFS-169254.

A. E. Fawzy, A. Amer, M. Shokair, and W. Saad, “Proposed intermittent Cluster Head selection scheme for efficient energy consumption in WSNs,” in 34th National Radio Science Conference (NRSC), 2017, no. NRSC, pp. 275–283, doi: 10.1109/NRSC.2017.7893486.

S. P. Dongare and R. S. Mangrulkar, “Optimal Cluster Head Selection Based Energy Efficient Technique for Defending against Gray Hole and Black Hole Attacks in Wireless Sensor Networks,” Phys. Procedia, vol. 78, no. December 2015, pp. 423–430, 2016, doi: 10.1016/j.procs.2016.02.084.

G. Indranil, D. Riordan, and S. Srinivas, “Cluster-head election using fuzzy logic for wireless sensor networks,” in Proceedings of Annual Communication Networks and Services Research Conference, 2005, pp. 255–260, doi: 10.1109/CNSR.2005.27.

N. A. Torghabeh, M. R. A. Totonchi, and M. H. Y. Moghaddam, “Cluster head selection using a two-level fuzzy logic in wireless sensor networks,” in CCET 2010 - 2010 International Conference on Computer Engineering and Technology, Proceedings I, 2010, vol. 2, pp. 357–361, doi: 10.1109/ICCET.2010.5485483.

H. Kavandi, M. Meghdadi, and M. Bayat, “A Method for Optimizing of the Energy Consumption in Wireless Sensor Networks By Dynamic Selection of Cluster Head Using Fuzzy Logic,” Indian J. Sci. Res., vol. 7, no. 1, pp. 1018–1025, 2014.

M. Taheri and Y. S. Kavian, “Energy Efficient Algorithm for Wireless Sensor Networks using Fuzzy Logic,” Int. J. Comput. Appl., vol. 89, no. 14, pp. 1–5, 2014, doi: 10.5120/15696-4055.

S. Gupta and N. Marriwala, “Improved distance energy based LEACH protocol for cluster head election in wireless sensor networks,” in 4th IEEE International Conference on Signal Processing, Computing and Control, ISPCC 2017, 2017, pp. 91–96, doi: 10.1109/ISPCC.2017.8269656.

D. Izadi, J. Abawajy, and S. Ghanavati, “A new energy efficient cluster-head and backup selection scheme in WSN,” in Proceedings of the 2013 IEEE 14th International Conference on Information Reuse and Integration, 2013, pp. 408–415, doi: 10.1109/IRI.2013.6642500.

E. Thenmozhi and S. Audithan, “Energy Efficinet Cluster Head Selection and Data Convening in Wireless Sensor Networks,” Indian J. Sci. Technol., vol. 9, no. 15, pp. 1–6, 2016, doi: 10.17485/ijst/2016/v9i15/77749.

D. Jia, H. Zhu, S. Zou, and P. Hu, “Dynamic Cluster Head Selection Method for Wireless Sensor Network,” IEEE Sens. J., vol. 16, no. 8, pp. 2746–2754, 2016, doi: 10.1109/JSEN.2015.2512322.

D. Agrawal and S. Pandey, “FUCA: Fuzzy-based unequal clustering algorithm to prolong the lifetime of wireless sensor networks,” Int. J. Commun. Syst., vol. 31, no. 2, pp. 1–18, 2018, doi: 10.1002/dac.3448.

P. Neamatollahi and M. Naghibzadeh, “Distributed unequal clustering algorithm in large-scale wireless sensor networks using fuzzy logic,” J. Supercomput., vol. 74, no. 6, pp. 1–24, 2018, doi: 10.1007/s11227-018-2261-5.

P. S. Mehra, M. N. Doja, and B. Alam, “Fuzzy based enhanced cluster head selection (FBECS) for WSN,” J. King Saud Univ. - Sci., vol. 32, no. 1, pp. 390–401, 2018, doi: 10.1016/j.jksus.2018.04.031.

H. Natarajan and S. Selvaraj, “A Fuzzy Based Predictive Cluster Head Selection Scheme for Wireless Sensor Networks,” Proc. 8th Int. Conf. Sens. Technol. Liverpool, UK A, pp. 560–566, 2014.

J. Kim, S. Park, Y.-J. Han, and T. Chung, “CHEF: cluster head election mechanism using fuzzy logic in wireless sensor networks,” in 10th international conference on Advance Communication Technology, 2008, vol. 1, pp. 654–659, doi: 10.1109/ICACT.2008.4493846.

A. Krishnakumar and V. Anuratha, “An Energy-Efficient Cluster Head Selection of LEACH Protocol for Wireless Sensor Networks,” in InNextgen Electronic Technologies: Silicon to Software (ICNETS2), 2017 International Conference on, IEEE., 2017, pp. 57–61.

S. A. Sahaaya Arul Mary and J. B. Gnanadurai, “Enhanced Zone Stable Election Protocol based on Fuzzy Logic for Cluster Head Election in Wireless Sensor Networks,” Int. J. Fuzzy Syst., vol. 19, no. 3, pp. 799–812, 2017, doi: 10.1007/s40815-016-0181-1.

S. B. S and S. V. U, “Super Cluster Head Selection and Energy Efficient Round Robin Load Balancing Technique in Wireless Sensor Networks,” Int. J. Eng. Sci. Comput., vol. 7, no. 4, pp. 10065–10072, 2017.

A. Al-Baz and A. El-Sayed, “A new algorithm for cluster head selection in LEACH protocol for wireless sensor networks,” Int. J. Commun. Syst., vol. 31, no. 1, pp. 57–61, 2017, doi: 10.1002/dac.3407.

K. Ramesh, “Improved Fair-Zone Technique Using Mobility Prediction In WSN,” Int. J. Adv. Smart Sens. Netw. Syst., vol. 2, no. 2, pp. 23–32, 2012, doi: 10.5121/ijassn.2012.2203.

K. Somasundaram, S. Saritha, and K. Ramesh, “Enhancement of network lifetime by improving the leach protocol for large scale WSN,” Indian J. Sci. Technol., vol. 9, no. 16, 2016, doi: 10.17485/ijst/2016/v9i16/92242.

K.Ramesh and K.Somasundaram, “a Comparative Study of Clusterhead Selection Algorithms in Wireless Sensor Networks,” Int. J. Comput. Sci. Eng. Surv., vol. 2, no. 4, pp. 153–164, 2011, doi: 10.1002/fut.

A. Al-Baz and A. El-Sayed, “A new algorithm for cluster head selection in LEACH protocol for wireless sensor networks,” Int. J. Commun. Syst., vol. 31, no. 1, pp. 1–13, 2018, doi: 10.1002/dac.3407.

A. M. E. Tamizharasi, J. J. S. M. E, A. K. Priya, and R. Maarlin, “Energy Aware Heuristic Approach for Cluster Head Selection in Wireless Sensor Networks,” Bull. Electr. Eng. Informatics, vol. 6, no. 1, pp. 70–75, 2017, doi: 10.11591/eei.v6i1.598.

Z. Siqing, T. Yang, and Y. Feiyue, “ScienceDirect ScienceDirect Fuzzy Logic-Based Clustering Algorithm for Multi-hop Wireless Fuzzy Logic-Based Clustering Algorithm for Multi-hop Wireless Sensor Networks Sensor Networks,” Procedia Comput. Sci., vol. 131, pp. 1095–1103, 2018, doi: 10.1016/j.procs.2018.04.270.

W. I. S. W. Din, S. Yahya, R. Jailani, M. N. Taib, A. I. M. Yassin, and R. Razali, “Fuzzy logic for cluster head selection in wireless sensor network,” in AIP Conference Proceedings, 2016, vol. 1774, p. 050006, doi: 10.1063/1.4965093.

A. Yan and B. Wang, “An adaptive WSN clustering scheme based on neighborhood energy level,” in 2017 IEEE 3rd Information Technology and Mechatronics Engineering Conference (ITOEC), 2017, pp. 1170–1173.

K. A. Prasath and T. Shankar, “RMCHS: Ridge method based cluster head selection for energy efficient clustering hierarchy protocol in WSN,” 2015 Int. Conf. Smart Technol. Manag. Comput. Commun. Control. Energy Mater. ICSTM 2015 - Proc., no. May, pp. 64–70, 2015, doi: 10.1109/ICSTM.2015.7225391.

The, P. T., Manh, V. N., & Hung, T. C. (2018, February). Improving network lifetime in wireless sensor network using fuzzy logic based clustering combined with mobile sink. In 2018 20th International Conference on Advanced Communication Technology (ICACT) (pp. 113-119). IEEE.

P. Nayak and A. Devulapalli, “A Fuzzy Logic-Based Clustering Algorithm for WSN to Extend the Network Lifetime,” IEEE Sens. J., vol. 16, no. 1, pp. 137–144, 2016, doi: 10.1109/JSEN.2015.2472970.

S. Murugaanandam and V. Ganapathy, “Reliability-based cluster head selection methodology using fuzzy logic for performance improvement in wsns,” IEEE Access, vol. 7, pp. 87357–87368, 2019, doi: 10.1109/ACCESS.2019.2923924.

R. Ranganathan, B. Somanathan, and K. Kannan, “Fuzzy-Based Cluster Head Amendment (FCHA) Approach to Prolong the Lifetime of Sensor Networks,” Wirel. Pers. Commun., vol. 110, no. 3, pp. 1533–1549, 2020, doi: 10.1007/s11277-019-06800-5.

S. Biswas, J. Saha, T. Nag, C. Chowdhury, and S. Neogy, “A Novel Cluster Head Selection Algorithm for Energy-Efficient Routing in Wireless Sensor Network,” 2016 IEEE 6th Int. Conf. Adv. Comput., pp. 588–593, 2016, doi: 10.1109/IACC.2016.114.

M. Patil and C. Sharma, “Energy efficient cluster head selection to enhance network connectivity for wireless sensor network,” in Recent Trends in Electronics, Information & Communication Technology (RTEICT), IEEE International Conference on, 2016, pp. 175–179.

D. Sharma, S. Verma, and K. Sharma, “Network Topologies in Wireless Sensor Networks : A Review,” Int. J. Electron. Commun. Technol., vol. 4, pp. 93–97, 2013, doi: 2230-7109.

Y. Hu, H. Liu, and J. Liang, “Cluster-Head Election Using Fuzzy Logic Systems in Radar Sensor Networks,” in Proceedings of the 2015 International Conference on Communications, Signal Processing, and Systems, 2016, pp. 171–179.

P. Azad and V. Sharma, “Clusterhead selection using multiple attribute decision making (MADM) approach in wireless sensor networks,” Lect. Notes Inst. Comput. Sci. Soc. Telecommun. Eng. LNICST, vol. 115, pp. 141–142, 2013.

F. Hamzeloei and M. K. Dermany, “A TOPSIS Based Cluster Head Selection for Wireless Sensor Network,” Procedia Comput. Sci., vol. 58, pp. 8–15, 2016, doi: 10.1016/j.procs.2016.09.005.

H. Farman et al., “Analytical network process based optimum cluster head selection in wireless sensor network,” PLoS One, vol. 12, no. 7, pp. 1–28, 2017.

B. Muhammad, R. Bilal, and R. Young, “Fuzzy-TOPSIS based Cluster Head selection in mobile wireless sensor networks,” J. Electr. Syst. Inf. Technol., pp. 1–16, 2017, doi: 10.1016/j.jesit.2016.12.004.

P. Rajpoot and P. Dwivedi, “Multiple Parameter Based Energy Balanced and Optimized Clustering for WSN to Enhance the Lifetime Using MADM,” Wirel. Pers. Commun., vol. 106, no. 2, pp. 829–877, 2019, doi: 10.1007/s11277-019-06192-6.

P. T. Karthick and C. Palanisamy, “Optimized cluster head selection using krill herd algorithm for wireless sensor network,” Automatika, vol. 60, no. 3, pp. 340–348, 2019, doi: 10.1080/00051144.2019.1637174.

V. Pal, G. Singh, and R. P. Yadav, “SCHS: Smart Cluster Head Selection Scheme for Clustering Algorithms in Wireless Sensor Networks,” Wirel. Sens. Netw., vol. 04, no. 11, pp. 273–280, 2012, doi: 10.4236/wsn.2012.411039.

X. Kuang, L. Liu, Q. Liu, and L. Xiang, “A clustering approach based on convergence degree chain for wireless sensor networks,” Secur. Commun. Networks, vol. 5, no. June 2011, pp. 422–437, 2015, doi: 10.1002/sec.

A. Lipare, D. R. Edla, and R. Dharavath, “Energy Efficient Routing Structure to Avoid Energy Hole Problem in Multi-Layer Network Model,” Wirel. Pers. Commun., vol. 112, no. 4, pp. 2575–2596, 2020, doi: 10.1007/s11277-020-07165-w.

Performance Evaluation of a MANET based Secure and Energy Optimized Communication Protocol (E2S-AODV) for Underwater Disaster Response Network

Abstract Views :233 | PDF Views:0

Authors

Karan Singh ¹, Rajeev Gupta ²

Affiliations
1 Department of Computer Science and Applications, M.M. Institute of Computer Technology and Business Management, MMDU, Mullana, IN
2 Department of Computer Science and Engineering, M.M. Engineering College, MMDU, Mullana, IN

Source

International Journal of Computer Networks and Applications, Vol 8, No 1 (2021), Pagination: 11-27

Abstract

In recent years, the role of telecommunications in Under Water Mobile Ad-hoc Network (UWMANET) has emerged as a significant field during disaster prevention and rescue operations. Various disaster prevention and rescue supported applications are introduced in these years for flood, tsunamis, and underwater earthquakes. While communication in UWMANET, the existing communication system has some limitations like high energy utilization, tremendous packet loss rate, and delay. Sensor nodes can be deployed for data collection from the dense underwater environment. In UWMANET, security is another critical aspect of secure data transmission. In this paper, a new UWMANET based routing protocol, i.e., E2S-AODV (Energy Efficient Secure Ad-hoc On-demand Distance Vector) is designed and tested for Under Water Disaster Response Network (UWDRN) in a controlled environment. The optimum route for data transmission is selected by Pigeons Swarm Optimization (PiSO). PiSO reduces the hop count in the chosen shortest path. Hello, messages are broadcasted to inform their neighbors that the connection to the host is active. LDW technique is used to authenticate these hello messages. For security purposes, original event message encrypted with CST (Ciphertext Stealing Technique) and qu-Vanstone ECC based public-key cryptography. To utilize energy efficiently, E2S-AODV introduced two energy concepts drains rate finder and residual energy finder. Results that are compared with existing disaster-based protocols; are pro-motive and assure an improved quality of service (QoS) achievement in terms of many multipronged metrics like energy efficiency, reliability, security, scalability, delay, and Throughput, etc. E2S-AODV achieved a 2% improvement in PDR, 5% enhancement in Throughput, 8% reduction in end-to-end delay, and 11% reduction in energy utilization compared to its near existing competent.

Keywords

Energy Efficiency, End-to-End Delay, E²S-AODV, MANET, PDR, QoS, Security, Throughput, UWDRN, UWMANET.

Full Text

References

K. Singh, and A. K. Yadav. A Qualitative and Quantitative Analysis of Routing Protocols in MANET, International Journal of Advanced Research in Computer and Communication Engineering, 5(7), 2016.

K. Singh, and R. Gupta. Comparative Assessment and Performance Analysis of Numerous Mobile Ad-Hoc Network Routing Protocols, Journal of Computational and Theoretical Nanoscience, Vol. 16, pp. 3906–3911, 2019.

K. Singh, and R. Gupta. SO-AODV: A Secure and Optimized Ad-Hoc On-Demand Distance Vector Routing Protocol over AODV with Quality Metrics for Disaster Response Applications, To be Published in Journal of Information and Technology Reserch (JITR), 14(3), by IGI global publications , US, 2020.

K. Singh, and R. Gupta. E2S-AODV: An Energy Efficient Multipronged Reliable Strategy ensuring Secure and Scalable QoS over Disaster Response Applications, International Journal of Advanced Trends in Computer Science and Engineering, Volume 9, No.4, July – August 2020.

A. K. Yadav, and A. Kush. E2-SCRP: An Energy Efficient Secure Cluster based Routing Protocol for 3D Underwater Acoustic MANET (UWMANET), International Journal of Innovative Technology and Exploring Engineering, ISSN: 2278-3075, 8(11), 2019.

Shanen Yu, Shuai Liu, Peng Jiang, "A High-Efficiency Uneven Cluster Deployment based on Network Layered for Event Coverage in UWSNs", Sensors Basel, MDPI, Vol. 16, Issue.2, PP. 2016.

Seyed Mohammed Ghoreyshi, AlirezaShahrabi, TuleenBoutaleb, Mohsen Khalily, "Mobile Data Gathering with Hop-Constrained Clustering in Underwater Sensor Networks", IEEE Access, vol.7, pp. 21118-21132.

S. Cai, Y. Zhu, T. Wang, G. Xu, A. Liu and X. Liu, "Data Collection in Underwater Sensor Networks based on Mobile Edge Computing," in IEEE Access, vol. 7, pp. 65357-65367, 2019, doi: 10.1109/ACCESS.2019.2918213.

Fang Zhu, Junfang Wei, "An Energy Efficient Routing Protocol Based on Layers and Unequal Clusters in Underwater Wireless Sensor Networks". Journal of Sensors. 2018. 1-10.

Guilista Khan, Rakesh Kumar Dwivedi, "Autonomous Deployment and Adjustment of Nodes in UWSN to Achieve Blanket Coverage (ADAN-BC)", International Journal of Information Technology, PP. 1-10, 2018.

Zhongsi Wang, Bang Wang, "A Novel Node Sinking Algorithm for 3D Coverage and Connectivity in Underwater Sensor Networks", Ad Hoc Networks, Vol. 56, PP. 43-35, 2017.

Mohammed Reza Khosravi, HmaidHabibRostami, "Efficient Routing for Dense UWSNs with High-Speed Mobile Nodes using Spherical Divisions", The Journal of Supercomputing, Vol. 74, Issue 2, PP. 696-716, 2018.

Gomathi R.M, J Martin Leo Manickam, "Energy Efficient Shortest Path Routing Protocol for Underwater Acoustic Wireless Sensor Network", Wireless Personal Communications, Vol.98, Issue.4, PP. 1-14, 2017

R.M. Gomathi, J. Martin Leo Manickam, "Energy Efficient Static Node Selection in Underwater Acoustic Wireless Sensor Network", Wireless Personal Communications, pp. 1-19.

ChhaganLal, Roberto Petroccia, KonstantinosPelekanakis, Mauro Conti, Joao Alves, "Toward the Development of Secure Underwater Acoustic networks", IEEE Journal of Oceanic Engineering, IEEE Journal of Oceanic Engineering, Vol.12, issue.4, PP. 1075-1087, 2017.

Yue Zhao, Bo Tian, Zhouguo Chen, Yiming Liu, Jianwei Ding, "An Energy-Efficient Key Agreement Mechanism for Underwater Sensor Networks", Lecture Notes in Electrical Engineering, Vol. 450, PP.1-13, 2017.

Jing Yan, Xian Yang, XiaoyuanLuo, Calian Chen, "Energy Efficient Data Collection over AUV-assisted Underwater Acoustic Sensor Network", IEEE Systems Journal, PP. 1-12, 2018.

Bisen, Dhananjay & Sharma, Sanjeev. (2017). An enhanced performance through agent-based secure approach for mobile ad hoc networks. International Journal of Electronics. 105. 1-21. 10.1080/00207217.2017.1355019.

T. S. Vamsi, P. Kumar, and T. Sruthi. Performance Analysis of AODV Routing Protocol in MANET under Blackhole Attack, Journal of Engineering Research and Application, ISSN: 2248-9622, 9(5), pp. 58-63, 2019.

Sathiamoorthy, J., Ramakrishnan, B. A Reliable Data Transmission in EAACK MANETs Using Hybrid Three-Tier Competent Fuzzy Cluster Algorithm. Wireless Pers Commun 97, 5897–5916 (2017). https://doi.org/10.1007/s11277-017-4817-8

Mohanakrishnan, U., Bhagavathiperumal, R. & Jayaraman, S. A Trusted Waterfall Framework Based Peer to Peer Protocol for Reliable and Energy Efficient Data Transmission in MANETs. Wireless Pers Commun 102, 95–124 (2018). https://doi.org/10.1007/s11277-018-5829-8.

C. Perkins, E. B. Royer, and S. Das. Ad hoc On-Demand Distance Vector (AODV) Routing, Retrieved March 1, 2001.

Andel, Todd & Yasinsac, Alec. (2006). On the credibility of MANET simulations. Computer. 39. 48 - 54. 10.1109/MC.2006.242.

Arora, D., Millman, E. & Neville, S.W. Enabling richer statistical MANET simulations through cluster computing. Cluster Comput 16, 989–1003 (2013).

Ochola, Elisha & Eloff, Mm & Van der Poll, John. (2012). Mobile ad-hoc network security challenges under AODV routing protocol. 113-122.

Pandya, Morli. (2013). Review on security issues of AODV routing protocol for MANETs. IOSR Journal of Computer Engineering. 14. 127-134. 10.9790/0661-145127134.

Alghfari, Fawaz & Saeed, Khalid. (2016). Energy Consumption Analysis of AODV and ABHMAODV Routing Protocols in MANET.

Anjum, S.S., Noor, R.M. & Anisi, M.H. Review on MANET Based Communication for Search and Rescue Operations. Wireless Pers Commun 94, 31–52 (2017).

Sara, Getsy & Subu, Neelavathy & Sridharan, D.. (2010). Evaluation and Comparison of Emerging Energy Efficient Routing Protocols in MANET. ICTACT JOURNAL ON COMMUNICATION TECHNOLOGY. 1. 37-46. 10.21917/ijct.2010.0006.

M. Barati, K. Atefi, F. Khosravi and Yashar Azab Daftari, "Performance evaluation of energy consumption for AODV and DSR routing protocols in MANET," 2012 International Conference on Computer & Information Science (ICCIS), Kuala Lumpeu, 2012, pp. 636-642, doi: 10.1109/ICCISci.2012.6297107.

Mostafa Abd-El-Barr, Bambang Sarif, "Swarm intelligence versus direct cover algorithms in synthesis of Multi-Valued Logic functions", Applied Computing and Informatics Available online 10 March 2020.

N. Khanna and K. K. Naik, "Design and implementation of an energy efficient routing approach based on existing AODV protocol in Mobile Adhoc Networks for military," 2016 International Conference on Emerging Trends in Electrical Electronics & Sustainable Energy Systems (ICETEESES), Sultanpur, 2016, pp. 216-222, doi: 10.1109/ICETEESES.2016.7581388.

P. Paranavithana and A. Jayakody, "Compromising AODV for better performance: Improve energy efficiency in AODV," 2017 6th National Conference on Technology and Management (NCTM), Malabe, 2017, pp. 201-204, doi: 10.1109/NCTM.2017.7872854.

Patel, Maitri & Patel, Manish. (2018). Energy Efficient Routing Using Residual Energy and Stability in Mobile Ad-Hoc Network. 857-861. 10.1109/ICIRCA.2018.8597298.

Shivashankar, & Suresh, H.N. & Varaprasad, Golla & Jayanthi, Guruswamy. (2014). Designing Energy Routing Protocol With Power Consumption Optimization in MANET. Emerging Topics in Computing, IEEE Transactions on. 2. 192-197. 10.1109/TETC.2013.2287177.

Sharma, Manmohan & Rashid, Mamoon. (2020). Security Attacks In MANET -A Comprehensive Study.

Vu Khanh, Quy & Hung, Le. (2020). A Trade-off between Energy Efficiency and High-Performance in Routing for Mobile Ad hoc Networks. Journal of Communications. 10.12720/jcm.15.3.263-269.

Anjum, Shaik & Md. Noor, Rafidah & Anisi, Hossein. (2015). Review on MANET Based Communication for Search and Rescue Operations. Wireless Personal Communications. 10.1007/s11277-015-3155-y.

M. Zaki, Salim & Ngadi, Md & Razak, Shukor. (2009). A review of delay aware routing protocols in MANET. ISSR Journals, CS Letters. Vol. 1 (1). 1-12.

Z. Chen, W. Zhou, S. Wu and L. Cheng, "An Adaptive on-Demand Multipath Routing Protocol With QoS Support for High-Speed MANET," in IEEE Access, vol. 8, pp. 44760-44773, 2020, doi: 10.1109/ACCESS.2020.2978582.

Gutiérrez, Daniel & Askalani, M. & Toral, S.L. & Barrero, Federico & Asimakopoulou, Eleana & Bessis, Nik. (2015). A Survey on Multihop Ad Hoc Networks for Disaster Response Scenarios. International Journal of Distributed Sensor Networks. 2015. 10.1155/2015/647037.

Elliptic Curve Cryptography based Secure Image Transmission in Clustered Wireless Sensor Networks

Abstract Views :187 | PDF Views:0

Authors

Rekha ¹, Rajeev Gupta ²

Source

International Journal of Computer Networks and Applications, Vol 8, No 1 (2021), Pagination: 67-78

Abstract

Wireless Sensor Networks (WSN) is arising as a potential computing platform in diverse zones such as weather forecasting, modern robotization, medical health care, and military systems, etc. Since the sensors are constantly gathering information from the actual world and communicate with one another through remote connections, keeping up the security and protection of WSN communication is a prerequisite. In this paper, safe confirmation and key organization scheme dependent on Elliptic Curve Cryptography (ECC) has been suggested to make sure about information/picture transmission in WSNs. The scheme proposed in this paper is protected, competent, and appropriate for providing sensor technology based IoT services and applications. The protocol provides all the security features such as mutual authentication, confidentiality, data integrity, perfect forward secrecy, fair key agreement, etc. and is secure against hello flood attack, DoS attack, man-in-middle attack, etc. Simulation software AVISPA has confirmed the safety of the protocol for the known assaults. The performance analysis ensures the superiority of the projected proposal over the existing schemes.

Keywords

WSN, Security, Elliptical Curve Cryptography (ECC), Automated Validation of Internet Security Protocols and Applications (AVISPA).

Full Text

References

J. Ramasamy and J. S. Kumaresan, “Image Encryption and Cluster Based Framework for Secured Image Transmission in Wireless Sensor Networks,” Wirel. Pers. Commun., vol. 112, no. 3, pp. 1355–1368, 2020, doi: 10.1007/s11277-020-07106-7.

A. Durresi, V. Paruchuri, R. Kannan, and S. S. Iyengar, “Data Integrity Protocol for Sensor Networks,” Int. J. Distrib. Sens. Networks, vol. 1, no. 2, pp. 205–214, 2005, doi: 10.1080/15501320590966459.

W. Wang, D. Peng, H. Wang, H. Sharif, and H. H. Chen, “Energy-constrained quality optimization for secure image transmission in wireless sensor networks,” Adv. Multimed., vol. 2007, pp. 1–9, 2007, doi: 10.1155/2007/25187.

Sachin Gajjar, Mohanchur Sarkar and Kankar Dasgupta. Article: Cluster Head Selection Protocol using Fuzzy Logic for Wireless Sensor Networks. International Journal of Computer Applications 97(7):38-43, July 2014.

D. Sharma, A. P. Bhondekar, A. Ojha, A. K. Shukla, and C. Ghanshyam, “A traffic aware cluster head selection mechanism for hierarchical wireless sensor networks routing,” 2016 4th Int. Conf. Parallel, Distrib. Grid Comput. PDGC 2016, pp. 673–678, 2016, doi: 10.1109/PDGC.2016.7913207.

A. B. Kaimal, S. Manimurugan, and C. S. C. Devadass, “Image Compression Techniques : A Survey,” Int. J. Eng. Invent., vol. 2, no. 4, pp. 26–28, 2013.

L. Sha, W. E. I. Wu, and B. Li, “Novel Image Set Compression Algorithm Using Rate-Distortion Optimized Multiple Reference Image Selection,” IEEE Access, vol. 6, pp. 66903–66913, 2018, doi: 10.1109/ACCESS.2018.2879378.

R. Naveen, “An Improved Image Compression Algorithm Using Wavelet and Fractional Cosine Transforms,” Int. J. Image, Graph. Signal Process., vol. 10, no. 11, pp. 19–27, 2018, doi: 10.5815/ijigsp.2018.11.03.

G. S. Rao, G. V. Kumari, and B. P. Rao, “Image Compression Using Neural Network for Biomedical Applications,” Soft Comput. Probl. Solving. Springer, Singapore, pp. 107–119, 2019, doi: 10.1007/978-981-13-1595-4.

K. Chatterjee, A. De, and D. Gupta, “A Secure and Efficient Authentication Protocol in Wireless Sensor Network,” Wirel. Pers. Commun., vol. 81, no. 1, pp. 17–37, 2015, doi: 10.1007/s11277-014-2115-2.

D. De Oliveira Gonçalves and D. G. Costa, “A survey of image security in wireless sensor networks,” J. Imaging, vol. 1, no. 1, pp. 4–30, 2015, doi: 10.3390/jimaging1010004.

M. Elhoseny, H. Elminir, A. Riad, and X. Yuan, “A secure data routing schema for WSN using Elliptic Curve Cryptography and homomorphic encryption,” J. King Saud Univ. - Comput. Inf. Sci., vol. 28, no. 3, pp. 262–275, 2016, doi: 10.1016/j.jksuci.2015.11.001.

A. Mehmood, M. M. Umar, and H. Song, “ICMDS: Secure inter-cluster multiple-key distribution scheme for wireless sensor networks,” Ad Hoc Networks, vol. 55, pp. 97–106, 2017, doi: 10.1016/j.adhoc.2016.10.007.

Y. H. B, Z. Aliouat, S. Harous, and A. Bentaleb, on Elliptic Curve Cryptography, vol. 1. Springer International Publishing.

K. Gupta, S. Silakari, R. Gupta, and S. A. Khan, “An ethical way for image encryption using ECC,” 2009 1st Int. Conf. Comput. Intell. Commun. Syst. Networks, CICSYN 2009, pp. 342–345, 2009, doi: 10.1109/CICSYN.2009.33.

H. Chan, A. Perrig, and D. Song, “Random key predistribution schemes for sensor networks,” Proc. - IEEE Symp. Secur. Priv., vol. 2003-Janua, pp. 197–213, 2003, doi: 10.1109/SECPRI.2003.1199337.

Zhang, Z., Wang, H., Vasilakos, A. V., & Fang, H. (2012). ECG-cryptography and authentication in body area networks. IEEE Transactions on Information Technology in Biomedicine, 16(6), 1070-1078.

Isawa, R., & Morii, M. (2011). One-time password authentication scheme to solve stolen verifier problem. In Proceedings of the Forum on Information Technology (pp. 225-228).

T. PonSelvalingam, S. Mahalakshmi, and S. Kurshid Jinna, “Re-authentication in Wireless Sensor Network,” Int. J. Comput. Appl., vol. 55, no. 8, pp. 32–41, 2012, doi: 10.5120/8777-2720.

Watro, Ronald, Derrick Kong, Sue-fen Cuti, Charles Gardiner, Charles Lynn, and Peter Kruus. "TinyPK: securing sensor networks with public key technology." In Proceedings of the 2nd ACM workshop on Security of ad hoc and sensor networks, pp. 59-64. 2004. doi: 10.1145/1029102.1029113.

E. Mykletun, J. Girao, and D. Westhoff, “Public key based cryptoschemes for data concealment in wireless sensor networks,” IEEE Int. Conf. Commun., vol. 5, no. c, pp. 2288–2295, 2006, doi: 10.1109/ICC.2006.255111.

L. B. Oliveira et al., “SecLEACH-On the security of clustered sensor networks,” Signal Processing, vol. 87, no. 12, pp. 2882–2895, 2007, doi: 10.1016/j.sigpro.2007.05.016.

D. Wu, G. Hu, G. Ni, W. Li, and Z. Zhang, “Research on secure routing protocols in wireless sensor networks,” Chinese J. Sensors Actuators, vol. 21, no. 7, pp. 1195–1201, 2008.

Raj, E. D. (2012). An Efficient Cluster Head Selection Algorithm for Wireless Sensor Networks–Edrleach. IOSR Journal of Computer Engineering (IOSRJCE), 2(2), 39-44.

S. Sahraoui, Somia; Bouam, “Secure Routing Optimization in Hierarchical Cluster-Based Wireless Sensor Networks,” Int. J. Commun. Networks Inf. Secur., vol. 5, no. 3, pp. 178–185, 2013.

Biswas, K., Muthukkumarasamy, V., & Singh, K. (2014). An encryption scheme using chaotic map and genetic operations for wireless sensor networks. IEEE Sensors Journal, 15(5), 2801-2809.

Q. Jiang, J. Ma, F. Wei, Y. Tian, J. Shen, and Y. Yang, “An untraceable temporal-credential-based two-factor authentication scheme using ECC for wireless sensor networks,” J. Netw. Comput. Appl., vol. 76, pp. 37–48, 2016, doi: 10.1016/j.jnca.2016.10.001.

D. He, N. Kumar, and N. Chilamkurti, “A secure temporal-credential-based mutual authentication and key agreement scheme with pseudo identity for wireless,” Inf. Sci. (Ny)., vol. 321, pp. 263–277, 2015, doi: 10.1016/j.ins.2015.02.010.

Elhoseny, M., Farouk, A., Batle, J., Shehab, A., & Hassanien, A. E. (2017). Secure image processing and transmission schema in cluster-based wireless sensor network. In Handbook of research on machine learning innovations and trends (pp. 1022-1040). IGI Global.

Shankar, K., & Elhoseny, M. (2019). Secure Image Transmission in Wireless Sensor Network (WSN) Applications. Springer International Publishing.

Sumalatha, M.S., Nandalal, V. An intelligent cross layer security based fuzzy trust calculation mechanism (CLS-FTCM) for securing wireless sensor network (WSN). J Ambient Intell Human Comput (2020). https://doi.org/10.1007/s12652-020-01834-1

C. T. Chen, C. C. Lee, and I. C. Lin, “Efficient and secure three-party mutual authentication key agreement protocol for WSNs in IoT environments,” PLoS One, vol. 15, no. 4, pp. 1–28, 2020, doi: 10.1371/journal.pone.0232277.

Benenson, Z., Gedicke, N., & Raivio, O. (2005). Realizing robust user authentication in sensor networks. Real-World Wireless Sensor Networks (REALWSN), 14, 52.

H. L. Yeh, T. H. Chen, P. C. Liu, T. H. Kim, and H. W. Wei, “A secured authentication protocol for wireless sensor networks using Elliptic Curves Cryptography,” Sensors, vol. 11, no. 5, pp. 4767–4779, 2011, doi: 10.3390/s110504767.

Kumar, P., Sain, M., & Lee, H. J. (2011, February). An efficient two-factor user authentication framework for wireless sensor networks. In 13th International Conference on Advanced Communication Technology (ICACT2011) (pp. 574-578). IEEE.

B. Vaidya, D. Makrakis, and H. T. Mouftah, “Improved two-factor user authentication in wireless sensor networks,” 2010 IEEE 6th Int. Conf. Wirel. Mob. Comput. Netw. Commun. WiMob’2010, vol. 8, no. 3, pp. 600–606, 2010, doi: 10.1109/WIMOB.2010.5645004.

D. Mishra, A. Kumar, and S. Mukhopadhyay, “Expert Systems with Applications A secure user anonymity-preserving biometric-based multi-server authenticated key agreement scheme using smart cards,” Expert Syst. Appl., vol. 41, no. 18, pp. 8129–8143, 2014, doi: 10.1016/j.eswa.2014.07.004.

Khan, M. K., & Zhang, J. (2007). Improving the security of ‘a flexible biometrics remote user authentication scheme’. Computer Standards & Interfaces, 29(1), 82-85.

R. Dalia and R. Gupta, “Cluster Head Selection Technique for Improving The Network Lifetime in WSN using ANP,” SSRN Electron. J., pp. 1–6, 2020, doi: 10.2139/ssrn.3564867.

A. Armando, D. Basin, J. Cuellar, M. Rusinowitch, and L. Viganò, “AVISPA: Automated Validation of Internet Security Protocols and Applications,” ERCIM News, vol. 64, 2006.

Username
Password
Remember me