Downloads: 2
Research Paper | Information Technology | Volume 13 Issue 9, September 2024 | Pages: 1745 - 1750 | United States
Design and Analysis of High-Performance Cloud Architectures for Data-Intensive Systems
Abstract: High-performance cloud architectures are a wide field of research that responds to the increasing computational and storage needs of the modern data-intensive systems of analytics, scientific workloads, and digital services. Architecture solutions to support efficient management of big data must implement a tradeoff of scalability, responsiveness, and fault tolerance. The paper will give a new design of the cloud architecture that is designed to support high throughput and latency sensitive data processing. The suggested methodology will integrate adaptive workload-sensitive resource provisioning, pipeline-based data placement techniques, and cross-layer optimization among the subsystems of the compute, storage and network. The use of analytical models and controlled experiments are used to assess the behavior of the system under heterogeneous and bursty workload evaluation. The analysis of comparative performance shows that the proposed architecture is statistically better in the efficiency of data processing (by about 30 per cent), minimization of service latency (by almost 25 per cent), and stability of resource utilization compared with the traditional monolith and container-based cloud architectures. This proves that architectural optimization enables the optimization of data intensive cloud platforms and performance and robustness is achievable through these approaches and is therefore appropriate to support the next generation scalable computing environment.
Keywords: Cloud computing, high-performance cloud architecture, data-intensive systems, resource orchestration, workload-aware scheduling, scalable distributed systems, performance optimization
How to Cite?: Anil Vijarnia, Sunil Netra, "Design and Analysis of High-Performance Cloud Architectures for Data-Intensive Systems ", Volume 13 Issue 9, September 2024, International Journal of Science and Research (IJSR), Pages: 1745-1750, https://www.ijsr.net/getabstract.php?paperid=SR24915104228, DOI: https://dx.dx.doi.org/10.21275/SR24915104228