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Some efficient algorithms to deal with redundancy allocation problems

Es-Sadqi Mustapha, Idrissi Abdellah, Benhassine Ahlem

Journal of Automation Mobile Robotics and Intelligent Systems

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2020

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Vol. 14, No. 4

48--57

EN

In this paper, we will discuss some algorithms in order to better optimize the problems of redundancy allocation in multi-state systems. The goal is to find the optimal configuration of the system that maximizes the availability and minimizes the investment cost. The availability will be evaluated using the universal generating function. In first step, our contribution consists in improving the genetic algorithm. In a second step, in the framework of the Constraint Programming, we propose a new method of optimization based on the Forward Checking as solver. Finally, we used the top-k method in our choice that helps us to get the best k elements from all possible values with highest availability. In comparison with the chosen study, our methods yield better results that satisfy the constraints of the problem in a shorter time.

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Preface to special issue on modern intelligent systems concepts

Idrissi Abdellah

Journal of Automation Mobile Robotics and Intelligent Systems

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2020

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Vol. 14, No. 3

48--49

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Preface to special issue on Modern Intelligent Systems Concepts II

Idrissi Abdellah

Journal of Automation Mobile Robotics and Intelligent Systems

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2020

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Vol. 14, No. 4

35--36

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Modeling of a dynamic and intelligent simulator at the infrastructure level of cloud services

Zegrari Faouzia, Idrissi Abdellah

Journal of Automation Mobile Robotics and Intelligent Systems

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2020

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Vol. 14, No. 3

65--70

EN

Cloud environments made up of a large number of compute and storage servers provide ondemand services in a usage-based consumption model (pay-as-you-go). Load balancing is one of the major problems in the cloud. Indeed, the dynamics of demand requirements and QoS, as well as the variability of cloud resources and its provisioning models make difficult the operation of performance evaluation of the system. To face this issue and to ensure the viability of cloud computing, IT resources must be managed effectively by a dynamic monitoring of the current workload of virtual machines (VMs). In this study, we propose the design of a cloud services simulation tool at the infrastructure level based on cloud computing simulation platform named CloudSim. It allows real-time monitoring of a load of each VM in terms of CPU utilization, memory utilization and bandwidth utilization ratio. The result of this case study can be useful for carry out dynamic environment simulations for VMs monitoring and fast decision making that can be used in load balancing mechanisms.