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A Survey on Clustering Algorithms and Proposed Architectural Framework for Border Surveillance System in Wireless Sensor Networks


Affiliations
1 School of Computer Science Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu,, India
 

.Border Surveillance system is a major security issue in all nations. In border surveillance systems, wireless sensor networks are one of the most important technologies which are going to play a vital role in future research. Researchers address the variety of challenges and spread the deployment in large areas in real time. In this paper, an overview of the border surveillance system their applied technologies, and the challenges faced during the deployment are discussed. An architectural framework for the border surveillance system is developed and presented. A comprehensive review is conducted with different routing protocols based on the node’s mobility, node’s localization, routing metrics, delay, throughput, energy efficiency, and their network lifetime. Simulation results of various protocols are conducted and presented. This work is intended to identify and focus on recent protocol developments and also opens research issues that need to be investigated in the future.

Keywords

Wireless Sensor Networks, Clustering, Routing, Raspberry Pi, IoT, Intruder Detection, Border Surveillance.
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  • Singh, Rajeev, and Sukhwinder Singh. "Smart border surveillance system using wireless sensor networks." International Journal of System Assurance Engineering and Management 13, no. 2 (2022): 880-894.
  • Bhadwal, Neha, Vishu Madaan, Prateek Agrawal, Awadesh Shukla, and Anuj Kakran. "Smart border surveillance system using wireless sensor network and computer vision." In 2019 international conference on Automation, Computational and Technology Management (ICACTM), pp. 183-190. IEEE, 2019.
  • Dande, Bhargavi, Chih-Yung Chang, Wen-Hwa Liao, and Diptendu Sinha Roy. "MSQAC: Maximizing the Surveillance Quality of Area Coverage in Wireless Sensor Networks." IEEE Sensors Journal 22, no. 6 (2022): 6150-6163.
  • T. Chindrella Priyadharshini, D. Mohana Geetha, E. A Mary Anita, “Energy Efficient Evolutionary Algorithm based Clustering with Route Selection Protocol for IoT Assisted Wireless Sensor Networks”, International Journal of Computer Networks and Applications (IJCNA), 9(3), PP: 328-339, 2022, https://doi.org/10.22247/ijcna/2022/212558
  • Shagari, Nura Modi, Mohd Yamani Idna Idris, Rosli Bin Salleh, Ismail Ahmedy, Ghulam Murtaza, and Aznul Qalid Bin Md Sabri. "A hybridization strategy using equal and unequal clustering schemes to mitigate idle listening for lifetime maximization of wireless sensor network." Wireless Networks 27, no. 4 (2021): 2641-2670.
  • Wang, Tong, Yunfeng Wang, and Chong Han. "An improved clustering routing mechanism for wireless Ad hoc network." Journal of Intelligent & Fuzzy Systems 32, no. 5 (2017): 3401-3412.
  • Haseeb, Khalid, Kamalrulnizam Abu Bakar, Abdul Hanan Abdullah, and Tasneem Darwish. "Adaptive energy aware cluster-based routing protocol for wireless sensor networks." Wireless Networks 23, no. 6 (2017): 1953-1966.
  • M. A. Mazaideh and J. Levendovszky, "A multi-hop routing algorithm for WSNs based on compressive sensing and multiple objective genetic algorithm," in Journal of Communications and Networks, vol. 23, no. 2, pp. 138-147, April 2021, doi: 10.23919/JCN.2021.000003.
  • Elsayed, Walaa M., Hazem M. El-Bakry, and Salah M. El-Sayed. "An Autonomous Fault-Awareness model adapted for upgrade performance in clusters of homogeneous wireless sensor networks." Wireless Networks 26, no. 7 (2020): 5085-5100.
  • Farahani, Marjan, and Akbar Ghaffarpour Rahbar. "Double leveled unequal clustering with considering energy efficiency and load balancing in dense iot networks." Wireless Personal Communications 106, no. 3 (2019): 1183-1207.
  • Dao, Thi-Kien, Jie Yu, Trong-The Nguyen, and Truong-Giang Ngo. "A hybrid improved MVO and FNN for identifying collected data failure in cluster heads in WSN." IEEE Access 8 (2020): 124311-124322.
  • Dao, Thi-Kien, Trong-The Nguyen, Jeng-Shyang Pan, Yu Qiao, and Quoc-Anh Lai. "Identification failure data for cluster heads aggregation in WSN based on improving classification of SVM." IEEE Access 8 (2020): 61070-61084.
  • Augustine, Susan, and John Patrick Ananth. "Taylor kernel fuzzy Cmeans clustering algorithm for trust and energy-aware cluster head selection in wireless sensor networks." Wireless Networks 26, no. 7 (2020): 5113-5132.
  • Liu, Xinyi, Ke Mei, and Shujuan Yu. "Clustering algorithm in wireless sensor networks based on differential evolution algorithm." In 2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC), vol. 1, pp. 478-482. IEEE, 2020.
  • Diwakaran, S., Perumal, B. & Vimala Devi, K. “A cluster prediction model-based data collection for energy efficient wireless sensor network”. Journal of supercomputing 75, 3302–3316 (2019). https://doi.org/10.1007/s11227-018-2437-z
  • J. Ding, H. Zhang, Z. Guo and Y. Wu, "The DPC-Based Scheme for Detecting Selective Forwarding in Clustered Wireless Sensor Networks," in IEEE Access, vol. 9, pp. 20954-20967, 2021, https://doi.org/10.1109/ACCESS.2021.3055026.
  • Nguyen, Tien-Dung, Vyacheslav Zalyubovskiy, Duc-Tai Le, and Hyunseung Choo. "Break-and-join tree construction for latency-aware data aggregation in wireless sensor networks." Wireless Networks 26, no. 7 (2020): 5255-5269.
  • Kim, Jung Woo, Sang Hun Sul, and Jae Boong Choi. “Development of real-time Internet of Things motion detection platform applying noncontact sensor based on open source hardware”. International Journal of Distributed Sensor Networks 16, no. 7 (2020): 1550147720944024.
  • Ullah, Ihsan, and Hee Yong Youn. "Efficient data aggregation with node clustering and extreme learning machine for WSN." The Journal of Supercomputing 76, no. 12 (2020): 10009-10035.
  • Tao, Ming, Xueqiang Li, Huaqiang Yuan, and Wenhong Wei. "UAVAided trustworthy data collection in federated-WSN-enabled IoT applications." Information Sciences 532 (2020): 155-169.
  • Kandah, Farah, Jesse Whitehead, and Peyton Ball. "Towards trusted and energy-efficient data collection in unattended wireless sensor networks." Wireless Networks 26, no. 7 (2020): 5455-5471.
  • Prabu, P., Ahmed Najat Ahmed, K. Venkatachalam, S. Nalini, and R. Manikandan. "Energy efficient data collection in sparse sensor networks using multiple Mobile Data Patrons." Computers & Electrical Engineering 87 (2020): 106778.
  • Navarro, Miguel, Yao Liang, and Xiaoyang Zhong. "Energy-efficient and balanced routing in low-power wireless sensor networks for data collection." Ad Hoc Networks 127 (2022): 102766.
  • Rudramurthy V C, R.Aparna, “Reliable and Efficient Routing Model for Unequal Clustering-Based Wireless Sensor Networks”, International Journal of Computer Networks and Applications (IJCNA), 9(1), PP: 1- 11, 2022, DOI: 10.22247/ ijcna/ 2022/211593.
  • Y. Tao, J. Zhang and L. Yang, "An Unequal Clustering Algorithm for Wireless Sensor Networks Based on Interval Type-2 TSK Fuzzy Logic Theory," in IEEE Access, vol. 8, pp. 197173-197183, doi: 10.1109/ACCESS.2020.3034607, 2020.
  • J. Uthayakumar, M. Elhoseny and K. Shankar, "Highly Reliable and Low-Complexity Image Compression Scheme Using Neighborhood Correlation Sequence Algorithm in WSN," in IEEE Transactions on Reliability, vol. 69, no. 4, pp. 1398-1423, Dec. 2020, https://doi.org/10.1109/TR.2020.2972567.
  • Shukla, Anurag, and Sarsij Tripathi. "An effective relay node selection technique for energy efficient WSN-assisted IoT." Wireless Personal Communications 112, no. 4 (2020): 2611-2641.
  • Arikumar, K. S., V. Natarajan, and Suresh Chandra Satapathy. "EELTM: An energy efficient LifeTime maximization approach for WSN by PSO and fuzzy-based unequal clustering." Arabian Journal for Science and Engineering 45, no. 12 (2020): 10245-10260.
  • Khalili, Mahdi, and Mohammad Khalily-Darmany. "A genetic algorithm for selecting cooperative or direct communications between nodes in wireless sensor networks." Iran Journal of Computer Science 3, no. 1 (2020): 25-33.
  • Mohanty, Sachi Nandan, E. Laxmi Lydia, Mohamed Elhoseny, Majid M. Gethami Al Otaibi, and K. Shankar. "Deep learning with LSTM based distributed data mining model for energy efficient wireless sensor networks." Physical Communication 40 (2020): 101097.
  • N. Gharaei, Y. D. Al-Otaibi, S. Rahim, H. J. Alyamani, N. A. K. K. Khani and S. J. Malebary, "Broker-Based Nodes Recharging Scheme for Surveillance Wireless Rechargeable Sensor Networks," in IEEE Sensors Journal, vol. 21, no. 7, pp. 9242-9249, 1 April1, 2021, https://doi.org/10.1109/JSEN.2021 .3053203.
  • N. Gharaei, Y. D. Al-Otaibi, S. A. Butt, S. J. Malebary, S. Rahim and G. Sahar, "Energy-Efficient Tour Optimization of Wireless Mobile Chargers for Rechargeable Sensor Networks," in IEEE Systems Journal, vol. 15, no. 1, pp. 27-36, March 2021, https://doi.org/10.1109/JSYST.2020.2968968.
  • A. Naeem, A. R. Javed, M. Rizwan, S. Abbas, J. C. -W. Lin and T. R. Gadekallu, "DARE-SEP: A Hybrid Approach of Distance Aware Residual Energy-Efficient SEP for WSN," in IEEE Transactions on Green Communications and Networking, vol. 5, no. 2, pp. 611-621, June 2021, https://doi.org/10.1109/TGCN .2021.3067885.
  • Das, Tisan, Rakesh Ranjan Swain, Pabitra Mohan Khilar, and Biswa Ranjan Senapati. "Deterministic linear-hexagonal path traversal scheme for localization in wireless sensor networks." Wireless Networks 26, no.
  • Heydari, Ali, MasoudReza Aghabozorgi, and Mehrzad Biguesh. "Optimal sensor placement for source localization based on RSSD." Wireless Networks 26, no. 7 (2020): 5151-5162.
  • Vikram, Raj, Ditipriya Sinha, Debashis De, and Ayan Kumar Das. "EEFFL: energy efficient data forwarding for forest fire detection using localization technique in wireless sensor network." Wireless Networks 26, no. 7 (2020): 5177-5205.
  • B. Ban, H. Wu and M. Jin, "Resilient Routing for Wireless Sensor Networks on High Genus Surfaces," in IEEE Transactions on Mobile Computing, vol. 20, no. 5, pp. 1993-2006, 1 May 2021, https://doi.org/10.1109/TMC.2020.2974195.
  • Dhumane, Amol V., and Rajesh S. Prasad. "Multi-objective fractional gravitational search algorithm for energy efficient routing in IoT." Wireless networks 25, no. 1 (2019): 399-413.
  • Alnawafa, Emad, and Ion Marghescu. "EDMHT-LEACH: Enhancing the performance of the DMHT-LEACH protocol for wireless sensor networks." 16th RoEduNet Conference: Networking in Education and Research (RoEduNet), pp. 1-6. IEEE, 2017.
  • Pathak, Aditya, Irfan Al-Anbagi, and Howard J. Hamilton. "An Adaptive QoS and Trust-based Lightweight Secure Routing Algorithm for WSNs." IEEE Internet of Things Journal (2022).
  • Renuga Devi, R., and T. Sethukarasi. "Develop Trust-Based Energy Routing Protocol for Energy Efficient with Secure Transmission." Wireless Personal Communications 123, no. 3 (2022): 2835-2862.
  • Aseeri, Mohammed, Muhammad Ahmed, Mohammed Shakib, Oussama Ghorbel, and Hussian Shaman. "Detection of attacker and location in wireless sensor network as an application for border surveillance." International Journal of Distributed Sensor Networks 13, no. 11 (2017): 1550147717740072.
  • Qu, Shaocheng, Liang Zhao, and Zhili Xiong. "Cross-layer congestion control of wireless sensor networks based on fuzzy sliding mode control." Neural Computing and Applications 32, no. 17 (2020): 13505- 13520.
  • Chilveri, P.G., Nagmode, M.S. “A novel node authentication protocol connected with ECC for heterogeneous network”. Wireless Networks 26, 4999–5012 (2020). https://doi.org /10.1007/s11276-020-02358-4
  • Ramonet, Alberto Gallegos, and Taku Noguchi. "Node replacement method for disaster resilient wireless sensor networks." In 2020 10th Annual Computing and Communication Workshop and Conference (CCWC), pp. 0789-0795. IEEE, 2020.
  • S. Verma, S. Kaur, D. B. Rawat, C. Xi, L. T. Alex and N. Zaman Jhanjhi, "Intelligent Framework Using IoT-Based WSNs for Wildfire Detection," in IEEE Access, vol. 9, pp. 48185-48196, 2021, https://doi.org/10.1109/ACCESS.2021.3060549
  • A. Verma, S. Kumar, P. R. Gautam, T. Rashid, and A. Kumar, ‘‘Fuzzy logic based effective clustering of homogeneous wireless sensor networks for mobile sink,’’ IEEE Sensors J., vol. 20, no. 10, pp. 5615– 5623, May 2020
  • R. Sharma, V. Vashisht, and U. Singh, ‘‘EETMFO/GA: A secure and energy efficient cluster head selection in wireless sensor networks,’’ Telecommunications. Syst., vol. 74, pp. 253–268, Feb. 2020.
  • S. R. Pokhrel, S. Verma, S. Garg, A. K. Sh arma, and J. Choi, ‘‘An efficient clustering framework for massive sensor networking in industrial IoT,’’ IEEE Trans. Ind. Information., early access, Jul. 1, 2020, doi: 10.1109/TII.2020.3006276.
  • Sirdeshpande, Nandakishor, and Vishwana th Udupi. "Fractional lion optimization for cluster head-based routing protocol in wireless sensor network." Journal of the Franklin Institute 354, no. 11 (2017): 4457- 4480.

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  • A Survey on Clustering Algorithms and Proposed Architectural Framework for Border Surveillance System in Wireless Sensor Networks

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Authors

Jayachandran J
School of Computer Science Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu,, India
Vimala Devi K
School of Computer Science Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu,, India

Abstract


.Border Surveillance system is a major security issue in all nations. In border surveillance systems, wireless sensor networks are one of the most important technologies which are going to play a vital role in future research. Researchers address the variety of challenges and spread the deployment in large areas in real time. In this paper, an overview of the border surveillance system their applied technologies, and the challenges faced during the deployment are discussed. An architectural framework for the border surveillance system is developed and presented. A comprehensive review is conducted with different routing protocols based on the node’s mobility, node’s localization, routing metrics, delay, throughput, energy efficiency, and their network lifetime. Simulation results of various protocols are conducted and presented. This work is intended to identify and focus on recent protocol developments and also opens research issues that need to be investigated in the future.

Keywords


Wireless Sensor Networks, Clustering, Routing, Raspberry Pi, IoT, Intruder Detection, Border Surveillance.

References





DOI: https://doi.org/10.22247/ijcna%2F2022%2F217710