A Conceptual Framework for Designing Resilient Multi-Cloud Networks Ensuring Security, Scalability, and Reliability Across Infrastructures.

References

[1] Agarwal, S., Yadav, S. and Yadav, A.K., 2015. An architecture for elastic resource allocation in fog computing. Int. J. Comput. Sci. Commun, 6(2), pp.201-207.

[2] Alhamazani, K., Ranjan, R., Jayaraman, P.P., Mitra, K., Liu, C., Rabhi, F., Georgakopoulos, D. and Wang, L., 2015. Cross-layer multi-cloud real-time application QoS monitoring and benchmarking as-a-service framework. IEEE Transactions on Cloud Computing, 7(1), pp.48-61.

[3] Alonso, J., Escalante, M. and Orue-Echevarria, L., 2016. Transformational cloud government (TCG): transforming public administrations with a cloud of public services. Procedia Computer Science, 97, pp.43-52.

[4] Bakar, Z.A., Yaacob, N.A. and Udin, Z.M., 2015. The effect of business continuity management factors on organizational performance: A conceptual framework. International Journal of Economics and Financial Issues, 5(1), pp.128-134.

[5] Battleson, D.A., West, B.C., Kim, J., Ramesh, B. and Robinson, P.S., 2016. Achieving dynamic capabilities with cloud computing: An empirical investigation. European Journal of Information Systems, 25(3), pp.209-230.

[6] Bhattacharjee, A., Barve, Y., Gokhale, A. and Kuroda, T., 2017. Cloudcamp: A model-driven generative approach for automating cloud application deployment and management. Vanderbilt University, Nashville, TN, USA, Tech. Rep. ISIS-17-105.

[7] Brogi, A., Fazzolari, M., Ibrahim, A., Soldani, J., Carrasco, J., Cubo, J., Durán, F., Pimentel, E., Di Nitto, E. and D Andria, F., 2015. Adaptive management of applications across multiple clouds: The SeaClouds Approach. CLEI electronic journal, 18(1), pp.2-2.

[8] Celestin, M. and Vanitha, N., 2015. Predictive analytics unleashed: Anticipating risks before they become crises. International Journal of Multidisciplinary Research and Modern Education (IJMRME), 1(2), pp.465-472.

[9] Chang, V., Ramachandran, M., Yao, Y., Kuo, Y.H. and Li, C.S., 2016. A resiliency framework for an enterprise cloud. International Journal of Information Management, 36(1), pp.155-166.

[10] Cohen, J., Krishnamoorthy, G. and Wright, A., 2017. Enterprise risk management and the financial reporting process: The experiences of audit committee members, CFO s, and external auditors. Contemporary Accounting Research, 34(2), pp.1178-1209.

[11] Cook, D.A., Brydges, R., Ginsburg, S. and Hatala, R., 2015. A contemporary approach to validity arguments: a practical guide to K ane's framework. Medical education, 49(6), pp.560-575.

[12] Dastjerdi, A.V., Garg, S.K., Rana, O.F. and Buyya, R., 2015. CloudPick: a framework for QoS‐aware and ontology‐based service deployment across clouds. Software: Practice and Experience, 45(2), pp.197-231.

[13] Demchenko, Y., Turkmen, F., Slawik, M. and De Laat, C., 2017, May. Defining intercloud security framework and architecture components for multi-cloud data intensive applications. In 2017 17th IEEE/ACM international symposium on cluster, cloud and grid computing (CCGRID) (pp. 945-952). IEEE.

[14] Ferrer, A.J., Pérez, D.G. and González, R.S., 2016. Multi-cloud platform-as-a-service model, functionalities and approaches. Procedia Computer Science, 97, pp.63-72.

[15] Ferry, N., Solberg, A., Jamshidi, P., Osman, R., Wang, W., Seycek, S., Gligor, V., Sucasa, R. and Abhervé, A., 2015. Modaclouds evaluation report–final version. MODAClouds EU Project Deliverable.

[16] Ghahramani, M.H., Zhou, M. and Hon, C.T., 2017. Toward cloud computing QoS architecture: Analysis of cloud systems and cloud services. IEEE/CAA Journal of Automatica Sinica, 4(1), pp.6-18.

[17] Ghahramani, M.H., Zhou, M. and Hon, C.T., 2017. Toward cloud computing QoS architecture: Analysis of cloud systems and cloud services. IEEE/CAA Journal of Automatica Sinica, 4(1), pp.6-18.

[18] Greenhalgh, T., Wherton, J., Papoutsi, C., Lynch, J., Hughes, G., Hinder, S., Fahy, N., Procter, R. and Shaw, S., 2017. Beyond adoption: a new framework for theorizing and evaluating nonadoption, abandonment, and challenges to the scale-up, spread, and sustainability of health and care technologies. Journal of medical Internet research, 19(11), p.e8775.

[19] Greenhalgh, T., Wherton, J., Papoutsi, C., Lynch, J., Hughes, G., Hinder, S., Fahy, N., Procter, R. and Shaw, S., 2017. Beyond adoption: a new framework for theorizing and evaluating nonadoption, abandonment, and challenges to the scale-up, spread, and sustainability of health and care technologies. Journal of medical Internet research, 19(11), p.e8775.

[20] Gudimetla, S. and Kotha, N., 2017. Azure Migrations Unveiled-Strategies for Seamless Cloud Integration. NeuroQuantology, 15(1), pp.117-123.

[21] Gupta, A., Christie, R. and Manjula, R., 2017. Scalability in internet of things: features, techniques and research challenges. Int. J. Comput. Intell. Res, 13(7), pp.1617-1627.

[22] Horowitz, B., Beling, P., Humphrey, M. and Gay, C., 2015. System Aware Cybersecurity: A Multi-Sentinel Scheme to Protect a Weapons Research Lab (No. SERC2015TR110).

[23] Jabłoński, A., 2016. Scalability of sustainable business models in hybrid organizations. Sustainability, 8(3), p.194.

[24] Jamshidi, P., Pahl, C. and Mendonça, N.C., 2017. Pattern‐based multi‐cloud architecture migration. Software: Practice and Experience, 47(9), pp.1159-1184.

[25] Jhawar, R. and Piuri, V., 2017. Fault tolerance and resilience in cloud computing environments. In Computer and information security handbook (pp. 155-173). Morgan Kaufmann.

[26] Kahnamouei, A.S., Bolandi, T.G. and Haghifam, M.R., 2017, September. The conceptual framework of resilience and its measurement approaches in electrical power systems. In IET International Conference on Resilience of Transmission and Distribution Networks (RTDN 2017) (pp. 1-11). IET.

[27] Kamel, F. and Ashraf, M., 2015. Vendor Lock-in in the transistion to a Cloud Computing platform.

[28] Karim, B., Tan, Q., El Emary, I., Alyoubi, B.A. and Costa, R.S., 2016. A proposed novel enterprise cloud development application model. Memetic Computing, 8(4), pp.287-306.

[29] Khan, S.U. and Ullah, N., 2016. Challenges in the adoption of hybrid cloud: an exploratory study using systematic literature review. The Journal of Engineering, 2016(5), pp.107-118.

[30] Kumar, S.M. and Belwal, M., 2017, August. Performance dashboard: Cutting-edge business intelligence and data visualization. In 2017 International Conference On Smart Technologies For Smart Nation (SmartTechCon) (pp. 1201-1207). IEEE.

[31] Li, S., Tryfonas, T. and Li, H., 2016. The Internet of Things: a security point of view. Internet Research, 26(2), pp.337-359.

[32] Liu, Y., Fieldsend, J.E. and Min, G., 2017. A framework of fog computing: Architecture, challenges, and optimization. IEEE Access, 5, pp.25445-25454.

[33] Malik, A. and Om, H., 2017. Cloud computing and internet of things integration: Architecture, applications, issues, and challenges. In Sustainable cloud and energy services: Principles and practice (pp. 1-24). Cham: Springer International Publishing.

[34] Maqsood, T., Khalid, O., Irfan, R., Madani, S.A. and Khan, S.U., 2016. Scalability issues in online social networks. ACM Computing Surveys (CSUR), 49(2), pp.1-42.

[35] Meyler, K., Buchanan, S., Scholman, M., Svendsen, J.G. and Rangama, J., 2017. Microsoft Hybrid Cloud Unleashed with Azure Stack and Azure. Sams Publishing.

[36] Mojtahedi, M. and Oo, B.L., 2017. Critical attributes for proactive engagement of stakeholders in disaster risk management. International journal of disaster risk reduction, 21, pp.35-43.

[37] Mushtaq, M.F., Akram, U., Khan, I., Khan, S.N., Shahzad, A. and Ullah, A., 2017. Cloud computing environment and security challenges: A review. International Journal of Advanced Computer Science and Applications, 8(10).

[38] Omopariola, M. and Lead, C.D., 2016. Zero-Trust Architecture Deployment in Emerging Economies: A Case Study from Nigeria [online]

[39] Panetto, H., Zdravkovic, M., Jardim-Goncalves, R., Romero, D., Cecil, J. and Mezgár, I., 2016. New perspectives for the future interoperable enterprise systems. Computers in industry, 79, pp.47-63.

[40] Pellegrini, R., Rottmann, P. and Strieder, G., 2017, December. Preventing vendor lock-ins via an interoperable multi-cloud deployment approach. In 2017 12th international conference for internet technology and secured transactions (icitst) (pp. 382-387). IEEE.

[41] Pham, L.M., Tchana, A., Donsez, D., Zurczak, V., Gibello, P.Y. and De Palma, N., 2015, January. An adaptable framework to deploy complex applications onto multi-cloud platforms. In The 2015 IEEE RIVF International Conference on Computing & Communication Technologies-Research, Innovation, and Vision for Future (RIVF) (pp. 169-174). IEEE.

[42] Phegade, V., Schrater, J., Kumar, A. and Kashyap, A., 2017. Self-defending key management service with intel® software guard extensions [online]

[43] Qu, L., Assi, C., Shaban, K. and Khabbaz, M.J., 2017. A reliability-aware network service chain provisioning with delay guarantees in NFV-enabled enterprise datacenter networks. IEEE Transactions on Network and Service Management, 14(3), pp.554-568.

[44] Ribeiro, L. and Björkman, M., 2017. Transitioning from standard automation solutions to cyber-physical production systems: An assessment of critical conceptual and technical challenges. IEEE systems journal, 12(4), pp.3816-3827.

[45] Rotsos, C., King, D., Farshad, A., Bird, J., Fawcett, L., Georgalas, N., Gunkel, M., Shiomoto, K., Wang, A., Mauthe, A. and Race, N., 2017. Network service orchestration standardization: A technology survey. Computer Standards & Interfaces, 54, pp.203-215.

[46] Sajid, A., Abbas, H. and Saleem, K., 2016. Cloud-assisted IoT-based SCADA systems security: A review of the state of the art and future challenges. Ieee Access, 4, pp.1375-1384.

[47] Schneeweiss, S., Eichler, H.G., Garcia‐Altes, A., Chinn, C., Eggimann, A.V., Garner, S., Goettsch, W., Lim, R., Löbker, W., Martin, D. and Müller, T., 2016. Real world data in adaptive biomedical innovation: a framework for generating evidence fit for decision‐making. Clinical Pharmacology & Therapeutics, 100(6), pp.633-646.

[48] Sekharan, S.S. and Kandasamy, K., 2017, March. Profiling SIEM tools and correlation engines for security analytics. In 2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET) (pp. 717-721). IEEE.

[49] Sikeridis, D., Papapanagiotou, I., Rimal, B.P. and Devetsikiotis, M., 2017. A Comparative taxonomy and survey of public cloud infrastructure vendors. arXiv preprint arXiv:1710.01476.

[50] Sikula, N.R., Mancillas, J.W., Linkov, I. and McDonagh, J.A., 2015. Risk management is not enough: a conceptual model for resilience and adaptation-based vulnerability assessments. Environment Systems and Decisions, 35(2), pp.219-228.

[51] Srai, J.S., Kumar, M., Graham, G., Phillips, W., Tooze, J., Ford, S., Beecher, P., Raj, B., Gregory, M., Tiwari, M.K. and Ravi, B., 2016. Distributed manufacturing: scope, challenges and opportunities. International Journal of Production Research, 54(23), pp.6917-6935.

[52] Taleb, T., Samdanis, K., Mada, B., Flinck, H., Dutta, S. and Sabella, D., 2017. On multi-access edge computing: A survey of the emerging 5G network edge cloud architecture and orchestration. IEEE Communications Surveys & Tutorials, 19(3), pp.1657-1681.

[53] Thekdi, S. and Aven, T., 2016. An enhanced data-analytic framework for integrating risk management and performance management. Reliability Engineering & System Safety, 156, pp.277-287.

[54] Troncoso, C., Isaakidis, M., Danezis, G. and Halpin, H., 2017. Systematizing decentralization and privacy: Lessons from 15 years of research and deployments. arXiv preprint arXiv:1704.08065.

[55] Um, J., 2017. Improving supply chain flexibility and agility through variety management. The international journal of logistics management, 28(2), pp.464-487.

[56] Vidhyalakshmi, R. and Kumar, V., 2017. CORE framework for evaluating the reliability of SaaS products. Future Generation Computer Systems, 72, pp.23-36.

[57] Wang, C., Zhang, T., Luo, F., Li, F. and Liu, Y., 2017. Impacts of cyber system on microgrid operational reliability. IEEE Transactions on Smart Grid, 10(1), pp.105-115.

[58] Yang, C., Shen, W., Lin, T. and Wang, X., 2016. A hybrid framework for integrating multiple manufacturing clouds. The International Journal of Advanced Manufacturing Technology, 86(1), pp.895-911.

[59] Zarrin, J., Aguiar, R.L. and Barraca, J.P., 2016. ElCore: Dynamic elastic resource management and discovery for future large-scale manycore enabled distributed systems. Microprocessors and Microsystems, 46, pp.221-239.

[60] Zhang, Q., Li, S., Li, Z., Xing, Y., Yang, Z. and Dai, Y., 2015. CHARM: A cost-efficient multi-cloud data hosting scheme with high availability. IEEE Transactions on Cloud computing, 3(3), pp.372-386.

[61] Zimmermann, A., Schmidt, R., Jugel, D. and Möhring, M., 2015. Evolving enterprise architectures for digital transformations (pp. 183-194). Gesellschaft für Informatik eV.

@article{1710600,
      author = {Tahir Tayor Bukhari, Oyetunji Oladimeji, Edima David Etim, Joshua Oluwagbenga Ajayi},
      title = {A Conceptual Framework for Designing Resilient Multi-Cloud Networks Ensuring Security, Scalability, and Reliability Across Infrastructures.},
      journal = {Iconic Research And Engineering Journals},
      year = {2018},
      volume = {1},
      number = {8},
      pages = {164-182},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1710600.pdf},
      abstract = {The rapid adoption of multi-cloud strategies in modern enterprises has introduced new challenges in ensuring secure, scalable, and reliable network infrastructures. Organizations increasingly deploy workloads across multiple cloud providers to achieve flexibility, optimize costs, and enhance service availability. However, distributing resources across heterogeneous cloud environments exposes networks to risks such as data breaches, inconsistent performance, and service disruptions. To address these challenges, this proposes a conceptual framework for designing resilient multi-cloud networks that simultaneously prioritizes security, scalability, and reliability. The framework emphasizes a modular and layered approach, integrating advanced security mechanisms, adaptive load balancing, and fault-tolerant network design. Security is enforced through end-to-end encryption, identity and access management, and continuous threat monitoring across all cloud nodes, mitigating risks associated with multi-tenant and cross-provider environments. Scalability is achieved by leveraging dynamic resource allocation, automated orchestration, and elastic network architectures that respond to fluctuating workloads without compromising performance. Reliability is ensured through redundancy, automated failover mechanisms, and real-time health monitoring of network links and services, reducing the likelihood of downtime and service degradation. Key components of the framework include cloud-agnostic network design principles, policy-driven traffic management, and integration with orchestration platforms for centralized visibility and control. By combining these elements, the framework enables organizations to optimize network performance, maintain compliance with security standards, and ensure continuous service availability in the presence of infrastructure failures or cyber threats. This conceptual model provides a foundation for future research and practical implementation of multi-cloud network architectures. By addressing the critical requirements of security, scalability, and reliability in an integrated manner, the framework supports resilient multi-cloud deployments capable of sustaining complex enterprise operations and meeting the demands of modern digital ecosystems.},
      keywords = {Conceptual framework, Designing resilient, Multi-cloud networks, Security, Scalability, Reliability, Infrastructures},
      month = {February},
  }