Computer Networks and Distributed Systems
Sara Mohammadi; Parvaneh Asghari; Amir Masoud Rahmani
Articles in Press, Accepted Manuscript, Available Online from 02 December 2022
Abstract
As a new technology, cloud computing is a key part of making systems more efficient and better and improving the Internet of Things. One of the significant challenges in fog computing is trust management, taking into account the processing, storage, and network constraints of fog devices. This study ...
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As a new technology, cloud computing is a key part of making systems more efficient and better and improving the Internet of Things. One of the significant challenges in fog computing is trust management, taking into account the processing, storage, and network constraints of fog devices. This study suggests that a multi-objective imperialist competitive optimization algorithm be used to increase trust and decrease response time in fog environments. After formulating trust, delay, and accuracy, the multi-objective imperialist competitive optimization algorithm is developed and evaluated for fog server selection. Evaluations show that the proposed method is more efficient and works well in terms of accuracy, delay, and trust than other algorithms.
Pattern Analysis and Intelligent Systems
Seyed Mojtaba Saif
Volume 2, Issue 2 , May 2016, , Pages 23-32
Abstract
Meta-heuristic algorithms inspired by the natural processes are part of the optimization algorithms that they have been considered in recent years, such as genetic algorithm, particle swarm optimization, ant colony optimization, Firefly algorithm. Recently, a new kind of evolutionary algorithm has been ...
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Meta-heuristic algorithms inspired by the natural processes are part of the optimization algorithms that they have been considered in recent years, such as genetic algorithm, particle swarm optimization, ant colony optimization, Firefly algorithm. Recently, a new kind of evolutionary algorithm has been proposed that it is inspired by the human sociopolitical evolution process. This new algorithm has been called Imperialist Competitive Algorithm (ICA). The ICA is a population-based algorithm where the populations are represented by countries that are classified as colonies or imperialists. This paper is going to present a modified ICA with considerable accuracy, referred to here as ICA2. The ICA2 is tested with six well-known benchmark functions. Results show high accuracy and avoidance of local optimum traps to reach the minimum global optimal.Three important policies are in the ICA, and assimilation policy is the most important of them. This research focuses on an assimilation policy in the ICA to propose a meta-heuristic optimization algorithm for optimizing function with high accuracy and avoiding to trap in local optima rather than using original ICA by a new assimilation strategy.