Title: Load balancing in cloud computing systems using density based clustering approach

Authors: Pearly Charles; S. Vimala

Addresses: Department of Computer Science, Mother Teresa Women's University, Kodaikanal, 624101, Tamil Nadu, India ' Department of Computer Science, Mother Teresa Women's University, Kodaikanal, 624101, Tamil Nadu, India

Abstract: Cloud computing, which uses clustering to load balance, is the current paradigm for providing ultimate services to society via the internet. This technology delivers all PAYG services. Privacy, security, reliability, and other problems offset infrastructure, platform, and software gains. Load balancing improves dispersed environments. Recent research prevents VM under- and over-loading. This research uses a density-based clustering-derive LB method. The turn around time (TAT) is much lower than K-Means. K-Means and DBSCAN cloud load balance. Clustering balances server loads. Similar queries let server clusters share the load. System performance, reaction time, and downtime improve the traditional load balancing works well. Round-robin sequence requests among servers. Cluster servers share the load. The least-connections approach sends requests to the server with the fewest active connections, ensuring each server has a similar capacity. Clustering load balances in real time. Clustering algorithms transfer groupings to other servers to balance demand. K-Means takes 269.875ms longer than anticipated.

Keywords: load balancing; TAT; turn around time; VM; virtual machine; cloud lets; cloud sim; clustering approach.

DOI: 10.1504/IJSSE.2024.143701

International Journal of System of Systems Engineering, 2024 Vol.14 No.6, pp.565 - 582

Received: 23 Feb 2023
Accepted: 09 May 2023
Published online: 06 Jan 2025 *

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