QoS-Aware Service Provisioning in Multi Cloud Environments
DOI:
https://doi.org/10.15662/IJEETR.2023.0504001Keywords:
Multi-cloud environments, Quality of Service (QoS), Service provisioning, Resource allocation, Metaheuristic algorithms, Machine learning, Edge computing, Predictive analyticsAbstract
The proliferation of cloud computing has led to the emergence of multi-cloud environments, where applications leverage services from multiple cloud providers to meet diverse Quality of Service (QoS) requirements. Ensuring optimal service provisioning in such environments is crucial for maintaining performance, reliability, and cost effectiveness. This paper explores QoS-aware service provisioning strategies in multi-cloud settings, focusing on techniques that dynamically allocate resources based on real-time performance metrics. We present a framework that integrates QoS monitoring, service selection, and resource allocation to enhance application performance across heterogeneous cloud platforms. The proposed approach employs a hybrid optimization model combining metaheuristic algorithms and machine learning techniques to predict and adapt to varying QoS conditions. Experimental results demonstrate that our framework significantly improves service reliability and reduces latency compared to traditional provisioning methods. Additionally, we discuss the challenges and future directions in QoS-aware provisioning, including the integration of edge computing and the use of artificial intelligence for predictive analytics.
References
1. Alhamazani, K., Ranjan, R., Mitra, K., Rabhi, F., & Buyya, R. (2015). A Survey on Service Level Agreement (SLA) in Cloud Computing: Research Issues and Challenges. IEEE Cloud Computing, 2(2), 34-40.
2. Chen, Y., Bahsoon, R., & Yao, X. (2015). Online QoS Modeling in the Cloud: A Hybrid and Adaptive Multi-Learners Approach. IEEE Transactions on Services Computing, 8(5), 772-785.
3. Mohapatra, S., Mahapatra, R., & Samanta, D. (2022). QoS-Aware Cloud Service Recommendation Using Metaheuristic Optimization. Electronics, 11(21), 3469.
4. Zhang, Q., Cheng, L., & Boutaba, R. (2010). Cloud computing: state-of-the-art and research challenges. Journal of Internet Services and Applications, 1(1), 7-18.
5. Buyya, R., Yeo, C. S., Venugopal, S., Broberg, J., & Brandic, I. (2009). Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility. Future Generation Computer Systems, 25(6), 599-616.
