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All Journal Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science
Muaayed F. Al-Rawi
Mustansiriyah University
Electrical & Electronics Engineering

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Novel load balancing approach based on ant colony optimization technique in cloud computing Yasameen A. Ghani Alyouzbaki; Muaayed F. Al-Rawi
Bulletin of Electrical Engineering and Informatics Vol 10, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i4.2947

Abstract

The cloud is the framework in which communication is connected with virtual machines, data centers, hosts, and brokers. The broker searches for a highly reliable cloudlet virtual machine for execution. Vulnerability can occur in the network because of which framework gets overburden. A research strategy is introduced in this article to expand the fault tolerance of the framework. The proposed approach improvement depends on the algorithm of ant colony optimization (ACO) that can choose the better virtual machine on which is to migrate the cloudlet to reduce the execution time and energy consumption. The efficiency of the proposed approach simulated in terms of execution time, energy consumption and examined with CloudSim. The introduction is provided in this article with a detailed description of cloud computing and, in addition, green cloud computing with its models. This article also discussed the virtual machine (VM) in more depth in the introduction section, which allows cloud service providers to supervise cloud resources competently while dispensing with the need for human oversight. Then the article submitted and explained the related works with their discussion and then it explained the novel proposed load balancing based on ACO technique and concluded that the execution time and energy consumption of the proposed technique is better than the three-threshold energy saving algorithm (TESA) technique that is commonly used in cloud load balancing.
Model based adaptive controller with grasshopper optimization algorithm for upper-limb rehabilitation robot Aliaa Adnan; Ekhlas H. Karam; Muaayed F. Al-Rawi
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 2: May 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i2.pp723-731

Abstract

Model based adaptive controllers (MBACs) are considered one of the most common adaptive controllers that are used with robotic systems due to their ensuring nonlinear robust scheme with global asymptotic stability for controlling nonlinear systems. However, this controller requires precise mathematical models of the controlled systems. In this paper, an optimal model-based adaptive controller (OMBAC) is suggested for controlling a two-link upper limb rehabilitation robot. This controller, in the presence of model uncertainties, can guarantee the robustness of the rehabilitation robot. Although the OMBAC is an adaptive and model-based controller, some of its parameters need to be determined precisely. In this paper, these parameters are determined by the grasshopper optimization algorithm (GOA). The Lyapunov method is used to analyze the stability assurance of controlled rehabilitation. The results of the simulation for two tested trajectories (linear and nonlinear trajectories) demonstrate the efficiency of the suggested OMBAC with fast settling time, minimum error steady state, and very small overshoot.
Co-Authors Aliaa Adnan Ekhlas H. Karam Yasameen A. Ghani Alyouzbaki