CLOUD RESOURCE OPTIMIZATION THROUGH ADAPTIVE LOAD BALANCING AND SCALABILITY TECHNIQUES
Keywords:
Cloud Resource Optimization, Adaptive Load Balancing, Horizontal Scalability, Vertical Scalability, Cloud Computing, Real-Time, Traffic Monitoring, Server Utilization, Cloud Performance, Elastic Load Balancer, AWS, NetflixAbstract
Cloud resource optimization is critical for ensuring efficient use of computational resources in modern cloud environments. This paper explores the effectiveness of adaptive load balancing and scalability techniques in optimizing cloud resource utilization. Adaptive load balancing algorithms, such as Least Connections and Weighted Least Connections, dynamically distribute workloads based on real-time system conditions, enhancing performance and minimizing server overloads. Scalability techniques, particularly horizontal scalability, allow cloud systems to expand capacity in response to fluctuating demands, ensuring high availability and minimizing response times. Case studies from leading cloud providers like AWS and Netflix demonstrate the practical application of these techniques, showing improvements in system performance, fault tolerance, and cost efficiency. This research highlights the importance of combining adaptive load balancing with well-managed scalability policies to create robust and flexible cloud infrastructures.
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Copyright (c) 2018 Himanshu Sharma (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
