Blockchain technology is a distributed ledger with records of data containing all details of the transactions carried out and distributed among the nodes present in the network. All the transactions carried out in the system are confirmed by consensus mechanisms, and the data once stored cannot be altered. Blockchain technology is the necessary technology behind Bitcoin, which is a popular digital Cryptocurrency. “Cloud computing is a practice of using a network of remote servers hosted on the internet to store, manage, and process data, rather than a local server or a personal computer.” It is still facing many challenges like data security, data management, compliance, reliability. In this article, we have mentioned some of the significant challenges faced by the cloud and proposed solutions by integrating it with blockchain technology. We tend to investigate a brief survey on earlier studies focused on blockchain integrating with the cloud to depict their supremacy. In this survey, we have also developed architecture integrating blockchain with cloud revealing the communication between blockchain and cloud.

Cloud computing has gained precise attention from the research community and management of IT, due to its scalable and dynamic capabilities. It is evolving as a vibrant technology to modernize and restructure healthcare organization to provide best services to the consumers. The rising demand for healthcare services and applications in cloud computing leads to the imbalance in resource usage and drastically increases the power consumption resulting in high operating cost. To achieve fast execution time and optimum utilization of the virtual machines, we propose a multi-objective hybrid fruitfly optimization technique based on simulated annealing to improve the convergence rate and optimization accuracy. The proposed approach is used to achieve the optimal resource utilization and reduces the energy consumption and cost in cloud computing environment. The result attained in our proposed technique provides an improved solution. The experimental results show that the proposed algorithm efficiently outperforms compared to the existing load balancing algorithms. Keywords: Cloud computing, Electronic Health Records (EHR), Load balancing, Fruitfly Optimization Algorithm (FOA), Simulated Annealing (SA), Energy consumptio

Blockchain technology has fascinated and significantly sparked research activities and industries due to its transparency in transactions and data sharing. The striking proliferation of blockchain technology is used to confront the challenges associated with trust, transparency, security, centralization, supply chain traceability, and regulatory compliance. The promising technology has the potential to enable several boons across diverse fields like healthcare, supply chain management, manufacturing, cross-border payments, finance, and energy trading. Telemedicine primarily aims to facilitate the transmission of healthcare data through electronic channels, enabling users to access medical services. It supports healthcare services around the globe, aids in early diagnosis and treatment, and assists with remote care by provisioning effective healthcare that is safe, secure, and reliable. However, there are challenges associated with Personal Health Records (PHR) due to lack of ownership of the data, accuracy, reliability, and data transaction security. The architecture presented in this work enables us to benefit from telemedicine and securely share PHR. The proposed model offers a permissioned network-based Hyperledger Fabric blockchain framework for secure PHR sharing amongst healthcare providers. The Byzantine Fault Tolerance consensus mechanism protects patient privacy, and the IPFS protocol is used to store the data off-chain. Additionally, the smart contract is utilized for providing patients with granular access control over PHR data. Hyperledger Caliper is used as a benchmarking tool to test this technology and determine the average latency rate for viewing and updating the PHR by healthcare providers along with analysis of CPU and memory utilization. As a result, our goals in telemedicine to improve secure sharing and give the patient access control are achieved.