References
- Bilal, J., H. Farman, H. Javed, B. Montrucchio, M. Khan, S. Ali. Energy Efficient Hierarchical Clustering Approaches in Wireless Sensor Networks: A Survey. – Wireless Communications and Mobile Computing, 2017, pp. 1-14. https://doi.org/10.1155/2017/6457942
- Gopika, D., R. Panjanathan. Energy Efficient Routing Protocols for WSN Based IoT Applications: A Review. – Materials Today Proceedings, November 2020. https://doi.org/10.1016/j.matpr.2020.10.137
- De-gan, Z., J. Qiu, T. Zhang, H. W u. New Energy-Efficient Hierarchical Clustering Approach Based on Neighbor Rotation for Edge Computing of IOT. – In: Proc. of 28th International Conference on Computer Communication and Networks (ICCCN’19), IEEE, 2019, pp. 1-2.
- Gazi, R. M. E., K. Wahid. LDCA: Lightweight Dynamic Clustering Algorithm for IoT-Connected Wide-Area WSN and Mobile Data Sink Using LoRa. – IEEE Internet of Things Journal, Vol. 9, 2021, No 2, pp. 1313-1325.
- Mohammad, M., Y. Jaradat, D. Zaidan, I. Jannoud. To Cluster or Not to Cluster: A Hybrid Clustering Protocol for WSN. – In: Proc. of IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology (JEEIT’19), IEEE, 2019, pp. 678-682.
- Shemim, F., U. Witkowski. Energy Efficient Clustering Protocols in WSNs: Performance Analysis and Comparison of EEAHP Protocol with LEACH and EAMMH Using MATLAB. – In: Proc. of Advances in Science and Engineering Technology International Conferences (ASET’20), IEEE, 2020, pp. 1-5.
- Dhiviya, S., A. Sariga, P. Sujatha. Survey on WSN Using Clustering. – In: Proc. of 2nd International Conference on Recent Trends and Challenges in Computational Models (ICRTCCM’17), IEEE, 2017, pp. 121-125.
- Santosh, A., K. C. Manoj. A Survey on Clustering Approaches to Strengthen the Performance of Wireless Sensor Network. – In: Proc. of 2nd International Conference on Inventive Research in Computing Applications (ICIRCA’20), IEEE, 2020, pp. 814-820.
- Fionn, M., P. Contreras. Algorithms for Hierarchical Clustering: An Overview. – Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, Vol. 2, 2012, No 1, pp. 86-97.
- Odilia, Y., K. T. Ramdeen. Hierarchical Cluster Analysis: Comparison of Three Linkage Measures and Application to Psychological Data. – The Quantitative Methods for Psychology, Vol. 11, 2015, No 1, pp. 8-21.
- Sambo, W., B. O. Yenke, A. Förster, P. Dayang. Optimized Clustering Algorithms for Large Wireless Sensor Networks: A Review. – Sensors, Vol. 19, 2019, No 2, 322.
- Amin, S., A. Taherkordi, Y. Haugen, F. Eliassen. Clustering Objectives in Wireless Sensor Networks: A Survey and Research Direction Analysis. – Computer Networks, Vol. 180, 2020, 107376.
- Himanshu, S., A. Haque, F. Blaabjerg. Machine Learning in Wireless Sensor Networks for Smart Cities: A Survey. – Electronics, Vol. 10, 2021, No 9, 1012.
- Wenliang, W., N. Xiong, C. Wu. Improved Clustering Algorithm Based on Energy Consumption in Wireless Sensor Networks. – Iet Networks, Vol. 6, 2017, No 3, pp. 47-53.
- SyedBilal, S., Z. Chen, F. Yin, I. UllahKhan, N. Ahmad. Energy and Interoperable Aware Routing for Throughput Optimization in Clustered IoT-Wireless Sensor Networks. – Future Generation Computer Systems, Vol. 81, 2018, pp. 372-381.
- Sobin, C. C. A Survey on Architecture, Protocols and Challenges in IoT. – Wireless Personal Communications, Vol. 112, 2020, No 3, pp. 1383-1429.
- TruptiMayee, B., U. ChandraSamal, S. K. Mohapatra. Energy‐Efficient Modified LEACH Protocol for IoT Application. – IET Wireless Sensor Systems, Vol. 8, 2018, No 5, pp. 223-228.
- Mehdi, H., A. Hemmati, A. M. Rahmani. Clustering for Smart Cities in the Internet of Things: A Review. – Cluster Computing, Vol. 25, 2022, No 6, pp. 4097-4127. https://doi.org/10.1007/s10586-022-03646-8
- AbbasShah, S., D. Sierra-Sosa, A. Kumar, A. Elmaghraby. IoT in Smart Cities: A Survey of Technologies, Practices and Challenges. – Smart Cities, Vol. 4, 2021, No 2, pp. 429-75. https://doi.org/10.3390/smartcities4020024
- Mehra, P. S. Lbecr: Load Balanced, Efficient Clustering and Routing Protocol for Sustainable Internet of Things in Smart Cities. – Journal of Ambient Intelligence and Humanized Computing, 2022, pp. 1-23.
- Hassan, E., A. Najid. ECH: An Enhanced Clustering Hierarchy Approach to Maximize Lifetime of Wireless Sensor Networks. – IEEE Access, Vol. 7, 2019, pp. 107142-107153.
- Premkumar, C., F. Al-Turjman, M. Kumar, T. Stephan. I-AREOR: An Energy-Balanced Clustering Protocol for Implementing Green IoT in Smart Cities. – Sustainable Cities and Society, Vol. 61, 2020, 102254.
- Vimal, V., K. U. Singh, A. Kumar, S. K. Gupta, M. Rashid, R. K. Saket, S. Padmanaban. Clustering Isolated Nodes to Enhance Network’s Life Time of WSNs for IoT Applications. – IEEE Systems Journal, Vol. 15, 2021, No 4, pp. 5654-5663.
- Akhilesh, P. A., R. K. Singh. EEHCHR: Energy Efficient Hybrid Clustering and Hierarchical Routing for Wireless Sensor Networks. – Ad Hoc Networks, Vol. 123, 2021, 102692.
- Amrit, M., A. P. Goswami, L. Yang, Z. Yan, M. Daneshmand. Dynamic Clustering Method Based on Power Demand and Information Volume for Intelligent and Green IoT. – Computer Communications, Vol. 152, 2020, pp. 119-125.
- Anurag, S., S. Tripathi. A Multi-Tier Based Clustering Framework for Scalable and Energy Efficient WSN-Assisted IoT Network. – Wireless Networks, Vol. 26, 2020, pp. 3471-3493.
- Ankur, C., S. Kumar, S. Gupta, M. Gong, A. Mahanti. FEHCA: A Fault-Tolerant Energy-Efficient Hierarchical Clustering Algorithm for Wireless Sensor Networks. – Energies, Vol. 14, 2021, No 13, 3935.
- Zhang, D., L. Chen, J. Zhang, J. Chen, T. Zhang, Y. Tang, J. Qiu. A Multi-Path Routing Protocol Based on Link Lifetime and Energy Consumption Prediction for Mobile Edge Computing. – IEEE Access, Vol. 8, 2020, pp.69058-69071.
- OMNET++ Simulation Environment. http://www.omnetpp.org
- Heinzelman, W. B., A. P. Chandrakasan, H. Balakrishnan. An Application-Specific Protocol Architecture for Wireless Microsensor Networks. – IEEE Transactions on Wireless Communications, Vol. 1, 2002, No 4, pp. 660-670. https://doi.org/10.1109/twc.2002.804190