The rapid expansion of the Internet of Things (IoT) has driven the need for advanced computational frameworks capable of handling the complex data processing and security challenges that modern IoT applications demand. However, traditional cloud computing frameworks face significant latency, scalability, and security issues. Quantum-Edge Cloud Computing (QECC) offers an innovative solution by integrating the computational power of quantum computing with the low-latency advantages of edge computing and the scalability of cloud computing resources. This study is grounded in an extensive literature review, performance improvements, and metrics data from Bangladesh, focusing on smart city infrastructure, healthcare monitoring, and the industrial IoT sector. The discussion covers vital elements, including integrating quantum cryptography to enhance data security, the critical role of edge computing in reducing response times, and cloud computing’s ability to support large-scale IoT networks with its extensive resources. Through case studies such as the application of quantum sensors in autonomous vehicles, the practical impact of QECC is demonstrated. Additionally, the paper outlines future research opportunities, including developing quantum-resistant encryption techniques and optimizing quantum algorithms for edge computing. The convergence of these technologies in QECC has the potential to overcome the current limitations of IoT frameworks, setting a new standard for future IoT applications.
References
[1]
Malhotra, P., Singh, Y., Anand, P., Bangotra, D.K., Singh, P.K. and Hong, W. (2021) Internet of Things: Evolution, Concerns and Security Challenges. Sensors, 21, Article 1809. https://doi.org/10.3390/s21051809
[2]
Shukla, S., Hassan, M.F., Tran, D.C., Akbar, R., Paputungan, I.V. and Khan, M.K. (2021) Improving Latency in Internet-Of-Things and Cloud Computing for Real-Time Data Transmission: A Systematic Literature Review (SLR). ClusterComputing, 26, 2657-2680. https://doi.org/10.1007/s10586-021-03279-3
[3]
How, M. and Cheah, S. (2023) Business Renaissance: Opportunities and Challenges at the Dawn of the Quantum Computing Era. Businesses, 3, 585-605. https://doi.org/10.3390/businesses3040036
[4]
Ren, J., Pan, Y., Goscinski, A. and Beyah, R.A. (2018) Edge Computing for the Internet of Things. IEEENetwork, 32, 6-7. https://doi.org/10.1109/mnet.2018.8270624
[5]
Jain, R. and Tata, S. (2017) Cloud to Edge: Distributed Deployment of Process-Aware IoT Applications. 2017 IEEE International Conference on Edge Computing (EDGE), Honolulu, 25-30 June 2017, 182-189. https://doi.org/10.1109/ieee.edge.2017.32
[6]
Badhon, M.B., Hasan, H.M., Islam, M.N.U., Jaly, N., Sumon, S.A. and Ullah, R. (2024) Enhancing Productivity through Business Analytics and Human Capital. InternationalJournalforMultidisciplinaryResearch, 6, 1-11. https://doi.org/10.36948/ijfmr.2024.v06i04.24688
[7]
Pal, A., Dey, T., Chopra, P., Akuli, A., Ray, M. and Bhattacharvva, N. (2012) A New Method for Grading of Silk Yarn Using Electronic Vision. 2012 Sixth International Conference on Sensing Technology (ICST), 18-21 December 2012, 387-392. https://doi.org/10.1109/icsenst.2012.6461706
[8]
Jain, S., Vaibhav, A. and Goyal, L. (2014) Raspberry Pi Based Interactive Home Automation System through E-Mail. 2014 International Conference on Reliability Optimization and Information Technology (ICROIT), Faridabad, 6-8 February 2014, 277-280. https://doi.org/10.1109/icroit.2014.6798330
[9]
Wu, Y. (2021) Cloud-Edge Orchestration for the Internet of Things: Architecture and AI-Powered Data Processing. IEEEInternetofThingsJournal, 8, 12792-12805. https://doi.org/10.1109/jiot.2020.3014845
[10]
Capra, M., Peloso, R., Masera, G., Ruo Roch, M. and Martina, M. (2019) Edge Computing: A Survey on the Hardware Requirements in the Internet of Things World. FutureInternet, 11, Article 100. https://doi.org/10.3390/fi11040100
[11]
C.P, V. and Chikkamannur, D.A.A. (2016) IOT Future in Edge Computing. InternationalJournalofAdvancedEngineeringResearchandScience, 3, 148-154. https://doi.org/10.22161/ijaers/3.12.29
[12]
Vo, T., Dave, P., Bajpai, G. and Kashef, R. (2022) Edge Fog and Cloud Computing: An Overview on Challenges and Applications. arXiv: 2211.01863. https://arxiv.org/abs/2211.01863
[13]
Pan, J. and McElhannon, J. (2018) Future Edge Cloud and Edge Computing for Internet of Things Applications. IEEEInternetofThingsJournal, 5, 439-449. https://doi.org/10.1109/jiot.2017.2767608
[14]
Ning, Z., Kong, X., Xia, F., Hou, W. and Wang, X. (2019) Green and Sustainable Cloud of Things: Enabling Collaborative Edge Computing. IEEECommunicationsMagazine, 57, 72-78. https://doi.org/10.1109/mcom.2018.1700895
[15]
Ketu, S. and Mishra, P.K. (2021) Cloud, Fog and Mist Computing in IoT: An Indication of Emerging Opportunities. IETETechnicalReview, 39, 713-724. https://doi.org/10.1080/02564602.2021.1898482
[16]
Zhang, J. (2024) Quantum Healthcare Analysis Based on Smart IoT and Mobile Edge Computing: Way into Network Study. OpticalandQuantumElectronics, 56, Article No. 566. https://doi.org/10.1007/s11082-024-06285-y
[17]
Javeed, D., Saeed, M.S., Ahmad, I., Adil, M., Kumar, P. and Islam, A.N. (2023) Quantum-Empowered Federated Learning and 6G Wireless Networks for IoT Security: Concept, Challenges and Future Directions. Future Generation Computer Systems, 160, 577-597.
[18]
Kulkarni, S., Tripathi, R.K. and Joshi, M. (2023) A Study on Data Security in Cloud Computing: Traditional Cryptography to the Quantum Age Cryptography. In: Deyasi, A., Sarkar, A. and Santra, S., Eds., SystemDesignUsingtheInternetofThingswithDeepLearningApplications, Apple Academic Press, 147-174. https://doi.org/10.1201/9781003376651-8
[19]
Yang, Z., Zolanvari, M. and Jain, R. (2023) A Survey of Important Issues in Quantum Computing and Communications. IEEECommunicationsSurveys&Tutorials, 25, 1059-1094. https://doi.org/10.1109/comst.2023.3254481
[20]
Hossain, M.I., Sumon, S.A., Hasan, H.M., Akter, F., Badhon, M.B. and Islam, M.N.U. (2024) Quantum-Edge Cloud Computing: A Future Paradigm for IoT Applications. arXiv: 2405.04824.
[21]
Serrano, M.A., Sánchez, L.E., Santos-Olmo, A., García-Rosado, D., Blanco, C., Barletta, V.S., et al. (2023) Minimizing Incident Response Time in Real-World Scenarios Using Quantum Computing. SoftwareQualityJournal, 32, 163-192. https://doi.org/10.1007/s11219-023-09632-6
[22]
Hamdan, S., Ayyash, M. and Almajali, S. (2020) Edge-Computing Architectures for Internet of Things Applications: A Survey. Sensors, 20, Article 6441. https://doi.org/10.3390/s20226441
[23]
Hua, H., Li, Y., Wang, T., Dong, N., Li, W. and Cao, J. (2023) Edge Computing with Artificial Intelligence: A Machine Learning Perspective. ACMComputingSurveys, 55, 1-35. https://doi.org/10.1145/3555802
[24]
Jeyaraj, R., Balasubramaniam, A., M.A., A.K., Guizani, N. and Paul, A. (2023) Resource Management in Cloud and Cloud-Influenced Technologies for Internet of Things Applications. ACMComputingSurveys, 55, 1-37. https://doi.org/10.1145/3571729
[25]
Maddikunta, P.K.R., Pham, Q., B, P., Deepa, N., Dev, K., Gadekallu, T.R., et al. (2022) Industry 5.0: A Survey on Enabling Technologies and Potential Applications. JournalofIndustrialInformationIntegration, 26, Article ID: 100257. https://doi.org/10.1016/j.jii.2021.100257
[26]
Badhon, M.B., Carr, N., Hossain, S., Khan, M.R.H., Sunna, A.A., Uddin, M.M., Chavarria, J.A. and Sultana, T. (2023) Digital Forensics Use-Case of Blockchain Technology: A Review. (2023). AMCIS 2023 Proceedings, Panama City, 10-12 August 2023, 29. https://aisel.aisnet.org/amcis2023/sig_sec/sig_sec/29
[27]
Tyagi, H. and Kumar, R. (2020) Cloud Computing for IoT. In: Alam, M., Shakil, K. and Khan, S., Eds., InternetofThings(IoT), Springer International Publishing, 25-41. https://doi.org/10.1007/978-3-030-37468-6_2
[28]
Nguyen, H.T., Krishnan, P., Krishnaswamy, D., Usman, M. and Buyya, R. (2024) Quantum Cloud Computing: A Review, Open Problems, and Future Directions. arXiv: 2404.11420.
[29]
Furutanpey, A., Barzen, J., Bechtold, M., Dustdar, S., Leymann, F., Raith, P., et al. (2023) Architectural Vision for Quantum Computing in the Edge-Cloud Continuum. 2023 IEEEInternationalConferenceonQuantumSoftware (QSW), Chicago, 2-8 July 2023, 88-103. https://doi.org/10.1109/qsw59989.2023.00021
