Hybrid Spotted Hyena based Load Balancing algorithm (HSHLB)

Abstract

In this paper, we delve into the core of our proposed dynamic load balancing mechanism, the Hybrid Spotted Hyena based Load Balancing algorithm (HSHLB). We begin by presenting a comprehensive overview of the Spotted Hyena Optimization Algorithm (SHOA) and the fundamental behaviors it encompasses, namely migration and attacking. We then introduce the Load Balancing Algorithm (LB) and outline its principles, emphasizing its distinct characteristics. Recognizing the strengths and weaknesses of both SHOA and LB, we embark on a journey to hybridize these two optimization techniques, resulting in the potent HSHLB. We elucidate the intricate process of combining these algorithms, elucidating how HSHLB harnesses their respective strengths while mitigating their limitations. This hybridization is pivotal to the overarching goal of achieving dynamic load balancing within cloud computing environments. As we progress through this section, we provide invaluable insights into the inner workings of HSHLB, offering readers a comprehensive understanding of its algorithmic steps, parameters, and intricacies. For clarity and enhanced comprehension, we incorporate pseudocode or flowcharts to illustrate the practical implementation of HSHLB.  In sum, Section 3 lays the foundation for the practical application of HSHLB in achieving dynamic load balancing, setting the stage for subsequent sections where we delve into implementation details, results, and analysis. HSHLB emerges as a promising solution to the multifaceted challenges of load balancing in cloud computing, leveraging the unique strengths of SHOA and LB to optimize resource allocation and enhance Quality of Service (QoS).