# Centralized vs. Decentralized Cloud Computing in Healthcare
## 5 Centralized Cloud Computing
[58] explored the potential of using centralized cloud computing to improve emergency healthcare services in India, proposing the use of palm vein pattern recognition to provide secure access to patient records, optimal medical accuracy, a quick admissions process, and the development of cloud-based services for the healthcare industry. This biometric authentication provides a higher level of security and privacy compared to traditional methods like smart cards or magnetic stripe cards. In their analysis, the authors compared the response times of cloud and web services to client queries, finding that the cloud demonstrated a faster response time and could handle more queries than web services. While the framework proposed was undoubtedly innovative, the reliance on palm vein pattern recognition can be an expensive technology compared with the alternatives. In addition, ref. [59] presented a conceptual framework for a cloud-based emergency healthcare service paradigm that sought to provide a healthcare application to assist patients in emergencies. The system proposed storing individuals' medical histories in a centralized cloud database, enabling easy retrieval in an emergency. A prototype of the system proposed was implemented using fingerprint matching to obtain concise medical records in a unified document from the centralized server. The system integrates users' biometric details with unique reference numbers and employs multi-document summarization to create a single medical record. The suggested model has improved the system response time and reduced latency by centralizing patient medical data in the cloud. This enables the faster retrieval of information during emergencies. Patient data privacy is enhanced using stringent security criteria such as cryptography, multi-layered access control, and harmonized information safeguarding frameworks. The model is also cost-effective as it leverages cloud computing benefits, including pay-as-you-go pricing, shared resources, and integration with existing government identification systems. However, the implementation of the model might be challenging, due to the system's reliance on biometric data to protect sensitive patient data. Finally, ref. [60] explored the utilization of an 'eHealth Cloud' in the healthcare sector. This cloud-based application was designed to store electronic medical records in a three-tier architecture. The application has been created with the RIA (Rich Internet program) as the client, SimpleDB cloud as the server, and a logic layer. Through offloading processor-intensive tasks to the cloud server, the burden on client devices is reduced, leading to improved overall system responsiveness. The use of REST (Representational State Transfer) interfaces between client and server tiers enables efficient data transfer and reduced latency. The logic layer, situated between the client and server, enforces rules and security measures to safeguard data privacy and control access. The government ministry manages the logic layer and enforces data privacy regulations. It integrates insurance and pharmaceuticals while protecting patient data privacy. However, it does not specify the security mechanisms and protocols for safeguarding patient data confidentiality and integrity. The SimpleDB cloud has limited data storage for the growing volume of EMR data. This causes issues that would be quickly exhausted by large EMR datasets and requires careful planning and management. The paper does not detail how the \"eHealth Cloud\" model addresses cost in cloud-based healthcare but mentions the cost-effectiveness of cloud computing as a key benefit. Table 2 summarizes the previously mentioned research in relation to their strengths and limitations.