Hybrid Invasive Weed Improved Grasshopper Optimization Algorithm for Cloud Load Balancing

Abstract

In cloud computing, the processes of load balancing and task scheduling are major concerns as they are the primary mechanisms responsible for executing tasks by allocating and utilizing the resources of Virtual Machines (VMs) in a more optimal way. This problem of balancing loads and scheduling tasks in the cloud computing scenario can be categorized as an NP-hard problem. This problem of load balancing needs to be efficiently allocated tasks to VMs and sustain the trade-off among the complete set of VMs. It also needs to maintain equilibrium among VMs with the objective of maximizing throughput with a minimized time span. In this paper, a Hybrid Invasive Weed Improved Grasshopper Optimization Algorithm-based-efficient Load Balancing (HIWIGOA-LB) technique is proposed by adopting the merits of the Invasive Weed Optimization Algorithm (IWOA) into the Grasshopper Optimization Algorithm (GOA) for determining the near-optimal solution that facilitates optimal load balancing. In particular, the random walk strategy is adopted to prevent the local point of optimality problem. It also utilized the strategy of grouping to modify the exploitation coefficient associated with the traditional GOA for balancing the rate of exploration and exploitation. The simulation investigations of the proposed HIWIGOA-LB scheme confirmed its better performance in minimizing the make span and response time by 13.21% and 16.71%, with a maximized throughput of 19.28%, better than the baseline approaches considered for investigation.

Perspicacious Fuzzy Clustering Franchised by Grasshopper Optimization Dexterity for Robust Resource Scheduling with Effective Load Balancing in Cloud Precedent

“…They used every job in work queue to accomplish balanced scheduling between virtual machines, resource assignment conceded out while taking decrease in makespan into account. Naveen Durai et al [11] suggested HIWIGOA-LB technique exploits IWOA and GOA algorithms to ensure that expected grade of examination and utilization further well-adjusted method, hence achieving potential task scheduling besides load balancing. It combines GOA as well as IWOA utilizing stochastic process and clustering approach to enhance capacity to explore during optimizing and to increase exploitation causes majority of escalation techniques to become trapped in local solutions, outcomes demonstrated that suggested HIWIGO-LB architecture featuring varying sets of fog nodes enlarged resource utilization efficiency.…”

Human Robot Interaction: Applications, Challenges and Future Directions

“…This form of unemployment is an inherent component of the technologically-driven phenomenon known as creative destruction, as described by [35] and incorporated into Kondratieff's theory of long waves in economic expansion. It is not unfounded to postulate, then, that the introduction of technical advancements may, in the beginning stages, potentially have a negative implication on individuals' overall satisfaction of life by leading to a significant increase in unemployment rates.…”

Enhancing Safety and Collaboration in Human Robot Interaction for Industrial Robotics

“…Additionally, robot factors (RF), like automation and reliability, as well as human factors (HF), including experience, and qualities, also play a significant role in shaping HRC. According to [38], conventional manufacturing robots exert an impact on human-robot collaboration (HRC) without including feedback mechanisms. This implies that in traditional robotics, the responsibility for adapting to various elements of HRC falls on the operator rather than the robot itself.…”