Hybrid Stochastic Ranking and Opposite Differential Evolution-Based Enhanced Firefly Optimization Algorithm for Extending Network Lifetime Through Efficient Clustering in WSNs

2021 ◽  
Vol 29 (3) ◽  
Author(s):  
A. Balamurugan ◽  
M. Deva Priya ◽  
Sengathir Janakiraman ◽  
A. Christy Jeba Malar
Keyword(s):  
Differential Evolution ◽  
Network Lifetime ◽  
Optimization Algorithm ◽  
Firefly Optimization ◽  
Firefly Optimization Algorithm

Evaluation of the trust values among human resources in the enterprise cloud using an optimization algorithm and fuzzy logic

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lantian Li ◽  
Bahareh Pahlevanzadeh
Keyword(s):  
Optimization Algorithm ◽  
Heuristic Algorithms ◽  
Human Life ◽  
Cloud Services ◽  
Cloud Provider ◽  
Suggested Approach ◽  
Content Type ◽  
Firefly Optimization ◽  
Security Costs ◽  
Firefly Optimization Algorithm

PurposeCloud eases information processing, but it holds numerous risks, including hacking and confidentiality problems. It puts businesses at risk in terms of data security and compliance. This paper aims to maximize the covered human resource (HR) vulnerabilities and minimize the security costs in the enterprise cloud using a fuzzy-based method and firefly optimization algorithm.Design/methodology/approachCloud computing provides a platform to improve the quality and availability of IT resources. It changes the way people communicate and conduct their businesses. However, some security concerns continue to derail the expansion of cloud-based systems into all parts of human life. Enterprise cloud security is a vital component in ensuring the long-term stability of cloud technology by instilling trust. In this paper, a fuzzy-based method and firefly optimization algorithm are suggested for optimizing HR vulnerabilities while mitigating security expenses in organizational cloud environments. MATLAB is employed as a simulation tool to assess the efficiency of the suggested recommendation algorithm. The suggested approach is based on the firefly algorithm (FA) since it is swift and reduces randomization throughout the lookup for an optimal solution, resulting in improved performance.FindingsThe fuzzy-based method and FA unveil better performance than existing met heuristic algorithms. Using a simulation, all the results are verified. The study findings showed that this method could simulate complex and dynamic security problems in cloud services.Practical implicationsThe findings may be utilized to assist the cloud provider or tenant of the cloud infrastructure system in taking appropriate risk mitigation steps.Originality/valueUsing a fuzzy-based method and FA to maximize the covered HR vulnerabilities and minimize the security costs in the enterprise cloud is the main novelty of this paper.

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