Cost-effective and secure multi-cloud optimization strategy for block storage

Abstract

Intheeraofbigdata,thevolumeofinformationbeinggeneratedandstoredhasgrown rapidly from terabytes to petabytes. Cloud storage provides a practical solution by offering nearly unlimited storage capacity with flexibility and scalability. However, relying on a single cloud provider poses significant risks, such as vendor lock-in, data breaches, andserviceoutages. Evenhaving replicationstrategiesputs usersintoseries of complex technical and financial situations. Multi-cloud storage, which distributes data across different cloud providers is an emerging research area which helps reduce these risks by improving fault tolerance and ensuring higher data while maintaining security for different user requirements. A major challenge in multi-cloud storage is determining how to store user’s block data in cost-effective, high availability, high performance within the budget. This projectaddressesthesechallengesbydevelopingCOSMOS-B,anoptimizedapproach to select the best combination of cloud providers for storing block data objects while balancing cost and availability, latency and other security requirements. It uses era- sure coding for fault-tolerant data distribution and weighted sum strategies to evaluate cloud providers based on normalized cost and availability metrics while enhancing overall security. Finally, it demonstrates the model’s adaptability to varying priorities, achieving significant cost savings and high reliability multi cloud environment.