OPTIMIZING CLOUD INFRASTRUCTURE: LOAD BALANCING FOR IOT DATA AND WORKLOAD SPIKES WITH ENHANCED SECURITY AND PROACTIVE MANAGEMENT

Abstract

In today's digital landscape, cloud computing has become the backbone of various applications, including the Internet of Things (IoT). Efficiently managing the storage of IoT data and addressing workload spikes while maintaining robust security measures has become paramount. The proposed protocol optimizes cloud resource allocation for IoT data storage, ensuring efficient utilization and enhanced security. Statistical analysis shows a significant improvement in resource utilization, resulting in cost savings and reduced latency. This model leverages real-time data analysis and predictive algorithms, reducing downtime and ensuring seamless user experiences during periods of increased demand. Statistical data reveals a remarkable reduction in response times during workload spikes, thereby enhancing overall system reliability. By combining these innovative approaches, organizations can optimize their cloud infrastructure, achieving a harmonious balance between IoT data storage, workload management, security, and cost efficiency. The statistical evidence provided demonstrates the practical benefits of implementing these strategies in today's cloud computing environments.