Eagle Strategy with Cauchy Mutation Particle Swarm Optimization for Energy Management in Cloud Computing

Kollu, Archana; Vadlamudi, Sucharita

doi:10.22266/ijies2020.1231.05

Cited by 4 publications

(3 citation statements)

References 18 publications

(24 reference statements)

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“…CM is a continuous probability distribution having two parameters, where p 0 indicates the location parameter and γ is the scale parameter used to determine the shape of the Cauchy distribution [29][30][31]. CM aims to solve the premature convergence problem and local stagnation problem of any optimization algorithm by taking controlled small steps.…”

Section: Cauchy Mutation (Cm)mentioning

confidence: 99%

An Improved Reptile Search Algorithm Based on Cauchy Mutation for Intrusion Detection

Duraibi¹

2023

Computer Systems Science and Engineering

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With the growth of the discipline of digital communication, the topic has acquired more attention in the cybersecurity medium. The Intrusion Detection (ID) system monitors network traffic to detect malicious activities. The paper introduces a novel Feature Selection (FS) approach for ID. Reptile Search Algorithm (RSA)-is a new optimization algorithm; in this method, each agent searches a new region according to the position of the host, which makes the algorithm suffers from getting stuck in local optima and a slow convergence rate. To overcome these problems, this study introduces an improved RSA approach by integrating Cauchy Mutation (CM) into the RSA's structure. Thus, the CM can effectively expand search space and enhance the performance of the RSA. The developed RSA-CM is assessed on five publicly available ID datasets: KDD-CUP99, NSL-KDD, UNSW-NB15, CIC-IDS2017, and CIC-IDS2018 and two engineering problems. The RSA-CM is compared with the original RSA, and three other state-of-theart FS methods, namely particle swarm optimization, grey wolf optimization, and multi-verse optimizer, and quantitatively is evaluated using fitness value, the number of selected optimum features, accuracy, precision, recall, and F1score evaluation measures. The results reveal that the developed RSA-CM got better results than the other competitive methods applied for FS on the ID datasets and the examined engineering problems. Moreover, the Friedman test results confirm that RSA-CM has a significant superiority compared to other methods as an FS method for ID.

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Section: Cauchy Mutation (Cm)mentioning

confidence: 99%

An Improved Reptile Search Algorithm Based on Cauchy Mutation for Intrusion Detection

Duraibi¹

2023

Computer Systems Science and Engineering

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“…The result analysis highlighted that the proposed method performs efficiently than MGA, MOACO, and MPSO for various QoS parameters. A task mapping approach using the PSO and Eagle Strategy was designed in [4]. The simulation results indicate that the proposed procedure is improved than the original PSO and other existing methods like RALBA, NMT-FOLS, etc.…”

Section: Related Workmentioning

confidence: 99%

“…To fulfill these services, cloud service providers provide virtual machines to the users in order to execute their tasks. It is necessary to map all the tasks on each virtual machine carefully to optimize the performance of the cloud [4] [5]. A service level agreement needs to be signed by the user and the service provider.…”

Section: Introductionmentioning

confidence: 99%

Independent Task Scheduling in Cloud Computing using Meta-Heuristic HC-CSO Algorithm

Bhagwan¹,

Kumar²

2021

IJACSA

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Cloud computing is a vital paradigm of emerging technologies. It provides hardware, software, and development platforms to end-users as per their demand. Task scheduling is an exciting job in the cloud computing environment. Tasks can be divided into two categories dependent and independent. Independent tasks are not connected to any type of parent-child concept. Various meta-heuristic algorithms have come into force to schedule the independent tasks. In this, paper a hybrid HC-CSO algorithm has been simulated using independent tasks. This hybrid algorithm has been designed by using the HEFT algorithm, Self-Motivated Inertia Weight factor, and standard Cat Swarm Optimization algorithm. The Crow Search algorithm has been applied to overcome the problem of premature convergence and to avoid the H-CSO algorithm getting stuck in the local fragment. The simulation was carried out using 500-1300 random lengths independent tasks and it was found that the H-CSO algorithm has beaten PSO, ACO, and CSO algorithms whereas the hybrid algorithm HC-CSO is working fine despite Cat Swarm Optimization, Particle Swarm Optimization, and H-CSO algorithm in the name of processing cost and makespan. For all scenarios, the HC-CSO algorithm is found overall 4.15% and 7.18% efficient than the H-CSO and standard CSO respectively in comparison to the makespan and in case of computation cost minimization, 9.60% and 14.59% than the H-CSO and the CSO, respectively.

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Eagle Strategy in Nature-Inspired Optimization: Theory, Analysis, Applications, and Comparative Study

Dhal,

Das,

Sasmal

et al. 2023

Arch Computat Methods Eng

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Eagle Strategy with Cauchy Mutation Particle Swarm Optimization for Energy Management in Cloud Computing

Cited by 4 publications

References 18 publications

An Improved Reptile Search Algorithm Based on Cauchy Mutation for Intrusion Detection

An Improved Reptile Search Algorithm Based on Cauchy Mutation for Intrusion Detection

Independent Task Scheduling in Cloud Computing using Meta-Heuristic HC-CSO Algorithm

Eagle Strategy in Nature-Inspired Optimization: Theory, Analysis, Applications, and Comparative Study

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