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Preethi, G.
- Hybrid Optimization-Based Secure Routing Protocol for Cloud Computing
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Authors
B. Vatchala
1,
G. Preethi
1
Affiliations
1 Department of Computer Science, PRIST Deemed University, Thanjaur, Tamil Nadu, IN
1 Department of Computer Science, PRIST Deemed University, Thanjaur, Tamil Nadu, IN
Source
International Journal of Computer Networks and Applications, Vol 9, No 2 (2022), Pagination: 229-239Abstract
Cloud Computing (CC) combines the computer paradigm and a shared environment allowing multiple users to access services and resources. In addition to being accessible internationally via the Internet, this ecosystem may be shared at all levels. Resources, infrastructure, and platforms at all levels may be traded with a wide range of customers. Through the Internet, CC enables remote server access. To create cloud environments, CCuses a wide range of already existing technologies, including internet servers, web browsers, and virtualization. These system vulnerabilities can have a significant impact on the cloud as well. The majority of data breaches occur on the way to their final destination. Because of this, the route that data takes must be protected. In this paper, Hybrid Optimization-based Secure Routing Protocol (HOSRP) is proposed to find the best route to destination and provide security to data that passes on it. HOSRP initially clusters the network into different numbers via modified particle swarm optimization strategy and selects the cluster head. HOSRP detects the shorted routes among clusters via firefly optimization strategy to minimize the delay and maximize the delivery ratio of packets. HOSRP applies security to data transmission using the message digest and cryptographic strategy. The performance of HOSRP is analyzed using greencloud simulator with standard performance metrics. Results indicate that HOSRP has better performance in minimizing the delay to save energy consumption and protecting security to the data.Keywords
Hybrid, Optimization, Routing, Cloud, Security, Swarm.Full Text
References
- R. Yarinezhad et al., “An energy efficient cluster head selection approach for performance improvement in network-coding-based wireless sensor networks with multiple sinks,” Ad Hoc Networks, vol. 64, pp. 514–526, Apr. 2021, doi: https://doi.org/10.1016/j.future.2018.12.024.
- H. Han, S. Shakkottai, C. V Hollot, R. Srikant, and D. Towsley, “Multi-Path TCP: A Joint Congestion Control and Routing Scheme to Exploit Path Diversity in the Internet,” IEEE/ACM Trans. Netw., vol. 14, no. 6, pp. 1260–1271, 2006, doi: 10.1109/TNET.2006.886738.
- O. Samuel, N. Javaid, T. A. Alghamdi, and N. Kumar, “Towards sustainable smart cities: A secure and scalable trading system for residential homes using blockchain and artificial intelligence,” Sustain. Cities Soc., vol. 76, p. 103371, 2022, doi: https://doi.org/10.1016/j.scs.2021.103371.
- M. Ganesan and N. Sivakumar, “IoT based heart disease prediction and diagnosis model for healthcare using machine learning models,” in 2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN), 2019, pp. 1–5, doi: 10.1109/ICSCAN.2019.8878850.
- S. Luo, G. Zhang, C. Wu, S. U. Khan, and K. Li, “Boafft: Distributed Deduplication for Big Data Storage in the Cloud,” IEEE Trans. Cloud Comput., vol. 8, no. 4, pp. 1199–1211, 2020, doi: 10.1109/TCC.2015.2511752.
- I. Bolodurina and D. Parfenov, “Comprehensive approach for optimization traffic routing and using network resources in a virtual data center,” Procedia Comput. Sci., vol. 136, pp. 62–71, 2018, doi: https://doi.org/10.1016/j.procs.2018.08.238.
- B. Farahani, F. Firouzi, V. Chang, M. Badaroglu, N. Constant, and K. Mankodiya, “Towards fog-driven IoT eHealth: Promises and challenges of IoT in medicine and healthcare,” Futur. Gener. Comput. Syst., vol. 78, pp. 659–676, 2018, doi: https://doi.org/10.1016/j.future.2017.04.036.
- A. S. Alqahtani, “Security threats and countermeasures in software defined network using efficient and secure trusted routing mechanism,” Comput. Commun., vol. 153, pp. 336–341, 2020, doi: https://doi.org/10.1016/j.comcom.2020.02.020.
- J. Ben Othman and L. Mokdad, “Enhancing data security in ad hoc networks based on multipath routing,” J. Parallel Distrib. Comput., vol. 70, no. 3, pp. 309–316, 2010, doi: https://doi.org/10.1016/j.jpdc.2009.02.010.
- V. Mythili, A. Suresh, M. M. Devasagayam, and R. Dhanasekaran, “SEAT-DSR: Spatial and energy aware trusted dynamic distance source routing algorithm for secure data communications in wireless sensor networks,” Cogn. Syst. Res., vol. 58, pp. 143–155, 2019, doi: https://doi.org/10.1016/j.cogsys.2019.02.005.
- G. C. Hadjichristofi, L. A. DaSilva, S. F. Midkiff, U. Lee, and W. De Sousa, “Routing, security, resource management, and monitoring in ad hoc networks: Implementation and integration,” Comput. Networks, vol. 55, no. 1, pp. 282–299, 2011, doi: https://doi.org/10.1016/j.comnet.2010.09.001.
- R. Prasad P and Shivashankar, “ENHANCED ENERGY EFFICIENT SECURE ROUTING PROTOCOL FOR MOBILE AD-HOC NETWORK,” Glob. Transitions Proc., 2021, doi: https://doi.org/10.1016/j.gltp.2021.10.001.
- K. Haseeb, I. Ud Din, A. Almogren, I. Ahmed, and M. Guizani, “Intelligent and secure edge-enabled computing model for sustainable cities using green internet of things,” Sustain. Cities Soc., vol. 68, p. 102779, 2021, doi: https://doi.org/10.1016/j.scs.2021.102779.
- G. Thahniyath and M. Jayaprasad, “Secure and load balanced routing model for wireless sensor networks,” J. King Saud Univ. - Comput. Inf. Sci., 2020, doi: https://doi.org/10.1016/j.jksuci.2020.10.012.
- A. Seyfollahi, M. Moodi, and A. Ghaffari, “MFO-RPL: A secure RPL-based routing protocol utilizing moth-flame optimizer for the IoT applications,” Comput. Stand. Interfaces, vol. 82, p. 103622, 2022, doi: https://doi.org/10.1016/j.csi.2022.103622.
- C. C. Sobin, C. Labeeba, and K. Deepika Chandran, “An Efficient method for Secure Routing in Delay Tolerant Networks,” Procedia Comput. Sci., vol. 143, pp. 820–826, 2018, doi: https://doi.org/10.1016/j.procs.2018.10.384.
- A. Vinitha, M. S. S. Rukmini, and Dhirajsunehra, “Secure and energy aware multi-hop routing protocol in WSN using Taylor-based hybrid optimization algorithm,” J. King Saud Univ. - Comput. Inf. Sci., 2019, doi: https://doi.org/10.1016/j.jksuci.2019.11.009.
- A. Yazdinejad, R. M. Parizi, A. Dehghantanha, G. Srivastava, S. Mohan, and A. M. Rababah, “Cost optimization of secure routing with untrusted devices in software defined networking,” J. Parallel Distrib. Comput., vol. 143, pp. 36–46, 2020, doi: https://doi.org/10.1016/j.jpdc.2020.03.021.
- R. Prasad and S. shankar, “Secure Intrusion Detection System Routing Protocol for Mobile Ad-Hoc Network,” Glob. Transitions Proc., 2021, doi: https://doi.org/10.1016/j.gltp.2021.10.003.
- D. Kothandaraman, S. Naik Korra, A. Balasundaram, and S. Magesh Kumar, “Sequence number based secure routing algorithm for IoT networks,” Mater. Today Proc., 2021, doi: https://doi.org/10.1016/j.matpr.2020.11.703.
- H. Helly, E. Efrat, and J. Yosef, “Spatial routinization and a ‘secure base’ in displacement processes: Understanding place attachment through the security-exploratory cycle and urban ontological security frameworks,” J. Environ. Psychol., vol. 75, p. 101612, 2021, doi: https://doi.org/10.1016/j.jenvp.2021.101612.
- Z. Liu, L. Wang, X. Wang, X. Shen, and L. Li, “Secure Remote Sensing Image Registration Based on Compressed Sensing in Cloud Setting,” IEEE Access, vol. 7, pp. 36516–36526, 2019, doi: 10.1109/ACCESS.2019.2903826.
- R. Kumar and R. Goyal, “Modeling continuous security: A conceptual model for automated DevSecOps using open-source software over cloud (ADOC),” Comput. Secur., vol. 97, p. 101967, 2020, doi: https://doi.org/10.1016/j.cose.2020.101967.
- F. Thabit, P. S. Alhomdy, and P. S. Jagtap, “Security Analysis and Performance Evaluation of a New Lightweight Cryptographic Algorithm for Cloud Computing Environment,” Glob. Transitions Proc., 2021, doi: https://doi.org/10.1016/j.gltp.2021.01.014.
- J. Ramkumar and R. Vadivel, “Meticulous elephant herding optimization based protocol for detecting intrusions in cognitive radio ad hoc networks,” Int. J. Emerg. Trends Eng. Res., vol. 8, no. 8, pp. 4549–4554, 2020, doi: 10.30534/ijeter/2020/82882020. How to cite this article:
- J. Ramkumar and R. Vadivel, “Bee inspired secured protocol for routing in cognitive radio ad hoc networks,” INDIAN J. Sci. Technol., vol. 13, no. 30, pp. 3059–3069, 2020, doi: 10.17485/IJST/v13i30.1152.
- R. Vadivel and J. Ramkumar, “QoS-Enabled Improved Cuckoo Search-Inspired Protocol (ICSIP) for IoT-Based Healthcare Applications,” pp. 109–121, 2019, doi: 10.4018/978-1-7998-1090-2.ch006.
- J. Ramkumar and R. Vadivel, “Intelligent Fish Swarm Inspired Protocol (IFSIP) For Dynamic Ideal Routing in Cognitive Radio Ad-Hoc Networks,” Int. J. Comput. Digit. Syst., vol. 10, no. 1, pp. 1063–1074, 2020, doi: http://dx.doi.org/10.12785/ijcds/100196.
- J. Ramkumar, R. Vadivel, and B. Narasimhan, “Constrained Cuckoo Search Optimization Based Protocol for Routing in Cloud Network,” Int. J. Comput. Networks Appl., doi: 10.22247/ijcna/2021/210727.
- J. Ramkumar and R. Vadivel, “Performance Modeling of Bio-Inspired Routing Protocols in Cognitive Radio Ad Hoc Network to Reduce End-to-End Delay,” Int. J. Intell. Eng. Syst., vol. 12, no. 1, pp. 221–231, 2019, doi: 10.22266/ijies2019.0228.22.
- J. Ramkumar and R. Vadivel, “Whale Optimization Routing Protocol for Minimizing Energy Consumption in Cognitive Radio Wireless Sensor Network,” Int. J. Comput. Networks Appl., vol. 8, no. 4, doi: 10.22247/ijcna/2021/209711.
- J. Ramkumar and R. Vadivel, “Multi-Adaptive Routing Protocol for Internet of Things based Ad-hoc Networks,” Wirel. Pers. Commun., pp. 1–23, Apr. 2021, doi: 10.1007/s11277-021-08495-z.
- S. Namasudra, D. Devi, S. Kadry, R. Sundarasekar, and A. Shanthini, “Towards DNA based data security in the cloud computing environment,” Comput. Commun., vol. 151, pp. 539–547, 2020, doi: https://doi.org/10.1016/j.comcom.2019.12.041.
- S. R. Jena, R. Shanmugam, K. Saini, and S. Kumar, “Cloud Computing Tools: Inside Views and Analysis,” Procedia Comput. Sci., vol. 173, pp. 382–391, 2020, doi: https://doi.org/10.1016/j.procs.2020.06.045.
- Energizing Firefly Optimization-Inspired Routing Protocol (EFOIRP) for Performance Enhancement in IOT-Based Cloud Wireless Sensor Networks (IC-WSN)
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Authors
Affiliations
1 Department of Computer Technology, PSG College of Arts and Science, Coimbatore, Tamil Nadu, IN
2 Department of Computer Science, PRIST University, Thanjavur, Tamil Nadu, IN
1 Department of Computer Technology, PSG College of Arts and Science, Coimbatore, Tamil Nadu, IN
2 Department of Computer Science, PRIST University, Thanjavur, Tamil Nadu, IN
Source
International Journal of Computer Networks and Applications, Vol 11, No 2 (2024), Pagination: 127-139Abstract
Physical obstructions that disrupt signal propagation and routing paths hinder routing performance in IoT-based Cloud Wireless Sensor Networks (IC-WSN) for greenhouse farming. Existing routing algorithms fail to address the energy consumption challenge, resulting in suboptimal routing paths and potential data loss. This paper proposes an Energizing Firefly Optimization-Inspired Routing Protocol (EFOIRP) to enhance performance in IC-WSN. The protocol employs novel routing strategies to handle physical obstructions within greenhouses. It includes comprehensive site surveys to identify obstructions and their impact on signal propagation, enabling intelligent path selection that minimizes obstruction effects and ensures reliable data transmission. This research aims to achieve seamless data transmission and monitoring in greenhouse farming. EFOIRP minimizes signal interference by addressing physical obstructions, optimizing data transmission efficiency, and empowering farmers with reliable and accurate data for precise control over greenhouse conditions and resource management. The research objectives encompass characterizing obstructions, developing adaptive routing algorithms, evaluating performance through simulations or experiments, investigating scalability, and validating effectiveness in real-world greenhouse farming scenarios. The proposed EFOIRP aims to overcome the limitations of existing routing algorithms and improve the performance of IC-WSN in greenhouse farming environments.Keywords
Cloud, Greenhouse, Firefly Optimization, IoT, Routing Protocol, Wireless Sensor Networks.Full Text
References
- P. Handayani and N. Folz, “Adaptive Land Management for Climate-Smart Agriculture,” in InHeNce 2021 - 2021 IEEE International Conference on Health, Instrumentation and Measurement, and Natural Sciences, 2021. doi: 10.1109/InHeNce52833.2021.9537265.
- D. C. Magnaye, “Climate Smart Agriculture Edu-tourism: A Strategy to Sustain Grassroots Pro-biodiversity Entrepreneurship in the Philippines,” Advances in Science, Technology and Innovation. pp. 203–218, 2019. doi: 10.1007/978-3-030-10804-5_20.
- A. A. Abdalla et al., “Microstructure, chemical compositions, and soft computing models to evaluate the influence of silicon dioxide and calcium oxide on the compressive strength of cement mortar modified with cement kiln dust,” Constr. Build. Mater., vol. 341, p. 127668, 2022, doi: 10.1016/j.conbuildmat.2022.127668.
- C. Morales-Morales, P. R. Najera-Medina, M. Castro-Bello, J. Morales-Morales, and J. Hernandez-Romano, “Wireless Real-Time Monitoring System Applied in a Tomato Greenhouse,” in 2020 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2020, 2020, pp. 1–6. doi: 10.1109/ROPEC50909.2020.9258762.
- C. Guo, Y. Zi, and W. Ren, “A Blockchain Based Framework for Smart Greenhouse Data Management,” Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12817 LNAI. pp. 299–310, 2021. doi: 10.1007/978-3-030-82153-1_25.
- P. S. Georgantopoulos, D. Papadimitriou, C. Constantinopoulos, T. Manios, I. N. Daliakopoulos, and D. Kosmopoulos, “A Multispectral Dataset for the Detection of Tuta Absoluta and Leveillula Taurica in Tomato Plants,” Smart Agric. Technol., vol. 4, p. 100146, 2023, doi: 10.1016/j.atech.2022.100146.
- A. Banerjee and D. M. Akbar Hussain, “SD-EAR: Energy aware routing in software defined wireless sensor networks,” Appl. Sci., vol. 8, no. 7, 2018, doi: 10.3390/app8071013.
- D. Ardiansyah, A. S. Miftahul Huda, Darusman, R. G. Pratama, and A. P. Putra, “Wireless Sensor Network Server for Smart Agriculture Optimatization,” in IOP Conference Series: Materials Science and Engineering, 2019. doi: 10.1088/1757-899X/621/1/012001.
- S. Hemavathi and B. Latha, FRHO: Fuzzy rule-based hybrid optimization for optimal cluster head selection and enhancing quality of service in wireless sensor network, vol. 79, no. 11. Springer, 2023, pp. 12238–12265. doi: 10.1007/s11227-023-05106-5.
- S. B. Viswanath, T. M. Nagendrappa, and K. R. Venkatesh, “Jsmcrp: Cross-layer architecture based joint-synchronous mac and routing protocol for wireless sensor network,” ECTI Trans. Electr. Eng. Electron. Commun., vol. 19, no. 1, pp. 94–113, 2021, doi: 10.37936/ECTI-EEC.2021191.240719.
- K. Haseeb, I. Ud Din, A. Almogren, I. Ahmed, and M. Guizani, “Intelligent and secure edge-enabled computing model for sustainable cities using green internet of things,” Sustain. Cities Soc., vol. 68, p. 102779, 2021, doi: 10.1016/j.scs.2021.102779.
- L. Hong-tan, K. Cui-hua, B. A. Muthu, and C. B. Sivaparthipan, “Big data and ambient intelligence in IoT-based wireless student health monitoring system,” Aggression and Violent Behavior. Elsevier Ltd, 2021. doi: 10.1016/j.avb.2021.101601.
- K. Murali Krishna, Y. D. Borole, S. Rout, P. Negi, M. Deivakani, and R. Dilip, “Inclusion of Cloud, Blockchain and IoT Based Technologies in Agriculture Sector,” in 2021 9th International Conference on Cyber and IT Service Management, CITSM 2021, 2021. doi: 10.1109/CITSM52892.2021.9588894.
- S. Namani and B. Gonen, “Smart agriculture based on IoT and cloud computing,” in Proceedings - 3rd International Conference on Information and Computer Technologies, ICICT 2020, IEEE, Mar. 2020, pp. 553–556. doi: 10.1109/ICICT50521.2020.00094.
- L. L. Hung, F. Y. Leu, K. L. Tsai, and C. Y. Ko, “Energy-efficient cooperative routing scheme for heterogeneous wireless sensor networks,” IEEE Access, vol. 8, pp. 56321–56332, 2020, doi: 10.1109/ACCESS.2020.2980877.
- X. Fu, Y. Yang, and O. Postolache, “Sustainable multipath routing protocol for multi-sink wireless sensor networks in harsh environments,” IEEE Trans. Sustain. Comput., vol. 6, no. 1, pp. 168–181, 2021, doi: 10.1109/TSUSC.2020.2976096.
- I. A. A. E. M. And and S. M. Darwish, “Towards Designing a Trusted Routing Scheme in Wireless Sensor Networks: A New Deep Blockchain Approach,” IEEE Access, vol. 9, pp. 103822–103834, 2021, doi: 10.1109/ACCESS.2021.3098933.
- O. R. Ahutu and H. El-Ocla, “Centralized Routing Protocol for Detecting Wormhole Attacks in Wireless Sensor Networks,” IEEE Access, vol. 8, pp. 63270–63282, 2020, doi: 10.1109/ACCESS.2020.2983438.
- M. Alotaibi, “Improved Blowfish Algorithm-Based Secure Routing Technique in IoT-Based WSN,” IEEE Access, vol. 9, pp. 159187–159197, 2021, doi: 10.1109/ACCESS.2021.3130005.
- T. Zhao, L. Wang, K.-W. Chin, and C. Yang, “Routing in Energy Harvesting Wireless Sensor Networks With Dual Alternative Batteries,” IEEE Syst. J., vol. 15, no. 3, pp. 3970–3979, 2020, doi: 10.1109/jsyst.2020.3007166.
- K. Ramasamy, M. H. Anisi, and A. Jindal, “E2DA: Energy Efficient Data Aggregation and End-to-End Security in 3D Reconfigurable WSN,” IEEE Trans. Green Commun. Netw., vol. 6, no. 2, pp. 787–798, 2022, doi: 10.1109/TGCN.2021.3126786.
- T. M. Behera, S. K. Mohapatra, U. C. Samal, M. S. Khan, M. Daneshmand, and A. H. Gandomi, “I-SEP: An Improved Routing Protocol for Heterogeneous WSN for IoT-Based Environmental Monitoring,” IEEE Internet Things J., vol. 7, no. 1, pp. 710–717, 2020, doi: 10.1109/JIOT.2019.2940988.
- C. Chen, L. C. Wang, and C. M. Yu, “D2CRP: A Novel Distributed 2-Hop Cluster Routing Protocol for Wireless Sensor Networks,” IEEE Internet Things J., vol. 9, no. 20, pp. 19575–19588, 2022, doi: 10.1109/JIOT.2022.3148106.
- F. H. El-Fouly, R. A. Ramadan, and R. A. Ramadan, “E3AF: Energy Efficient Environment-Aware Fusion Based Reliable Routing in Wireless Sensor Networks,” IEEE Access, vol. 8, pp. 112145–112159, 2020, doi: 10.1109/ACCESS.2020.3003155.
- J. Ramkumar, A. Senthilkumar, M. Lingaraj, R. Karthikeyan, and L. Santhi, “Optimal Approach for Minimizing Delays in Iot-Based Quantum Wireless Sensor Networks Using Nm-Leach Routing Protocol,” J. Theor. Appl. Inf. Technol., vol. 102, no. 3, pp. 1099–1111, 2024.
- R. Jaganathan, V. Ramasamy, L. Mani, and N. Balakrishnan, “Diligence Eagle Optimization Protocol for Secure Routing (DEOPSR) in Cloud-Based Wireless Sensor Network,” Res. Sq., 2022, doi: 10.21203/rs.3.rs-1759040/v1.
- J. Ramkumar and R. Vadivel, “Improved frog leap inspired protocol (IFLIP) – for routing in cognitive radio ad hoc networks (CRAHN),” World J. Eng., vol. 15, no. 2, pp. 306–311, 2018, doi: 10.1108/WJE-08-2017-0260.
- L. Mani, S. Arumugam, and R. Jaganathan, “Performance Enhancement of Wireless Sensor Network Using Feisty Particle Swarm Optimization Protocol,” ACM Int. Conf. Proceeding Ser., pp. 1–5, Dec. 2022, doi: 10.1145/3590837.3590907.
- R. Jaganathan and R. Vadivel, “Intelligent Fish Swarm Inspired Protocol (IFSIP) for Dynamic Ideal Routing in Cognitive Radio Ad-Hoc Networks,” Int. J. Comput. Digit. Syst., vol. 10, no. 1, pp. 1063–1074, 2021, doi: 10.12785/ijcds/100196.
- K. Wang, C. M. Yu, and L. C. Wang, “DORA: A Destination-Oriented Routing Algorithm for Energy-Balanced Wireless Sensor Networks,” IEEE Internet Things J., vol. 8, no. 3, pp. 2080–2081, 2021, doi: 10.1109/JIOT.2020.3025039.
- G. Tong, S. Zhang, W. Wang, and G. Yang, “A particle swarm optimization routing scheme for wireless sensor networks,” CCF Trans. Pervasive Comput. Interact., vol. 5, no. 2, pp. 125–138, 2023, doi: 10.1007/s42486-022-00118-1.