A learning automata-based ensemble resource usage prediction algorithm for cloud computing environment

2018 ◽  
Vol 79 ◽  
pp. 54-71 ◽  
Author(s):  
Ali Asghar Rahmanian ◽  
Mostafa Ghobaei-Arani ◽  
Sajjad Tofighy
Keyword(s):  
Cloud Computing ◽  
Learning Automata ◽  
Prediction Algorithm ◽  
Resource Usage ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Resource Usage Prediction

scholarly journals An Efficient Resource Provisioned Technique in Cloud Computing Environment.

2020 ◽  
Vol 9 (3) ◽  
pp. 2133-2136
Keyword(s):  
Cloud Computing ◽  
Distributed Computing ◽  
Service Providers ◽  
Resource Provisioning ◽  
Resource Usage ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Efficient Resource ◽  
Cloud Framework

Different ICT-empowered service providers additionally have either embraced distributed computing or began moving administrations to cloud framework. Be that as it may, the expanding interest for cloud based foundation has come about into extreme issue of managing the resources and adjusting of load for cloud specialist providers and customers. Specialists have recommended various resource provisioning techniques for effective resource usage. An epic burden adjusting procedure addressing the movement of the outstanding task at hand from over-stacked VM to gently stacked VM in distributed computing conditions is presented in this paper. An undertaking is made to help the cloud accomplices to beat the imbalanced asset utilization issue is shown in this paper.

scholarly journals Performance of Noise Map Service Working in Cloud Computing Environment

2016 ◽  
Vol 41 (2) ◽  
pp. 297-302 ◽  
Author(s):  
Karolina Marciniuk ◽  
Maciej Szczodrak ◽  
Bożena Kostek
Keyword(s):  
Cloud Computing ◽  
Web Application ◽  
Prediction Models ◽  
Traffic Noise ◽  
Prediction Algorithm ◽  
Noise Prediction ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Map Service ◽  
Noise Map

Abstract In the paper, a noise map service designated for the user interested in environmental noise is presented. Noise prediction algorithm and source model, developed for creating acoustic maps, are working in the cloud computing environment. In the study, issues related to the noise modelling of sound propagation in urban spaces are discussed with a particular focus on traffic noise. Examples of results obtained through a web application created for that purpose are shown. In addition, these are compared to results obtained from the commercial software simulations based on two road noise prediction models. Moreover, the computing performance of the developed application is investigated and analyzed. In the paper, a flowchart simulating the operation of the noise web-based service is presented showing that the created application is easy to use even for people with little experience in computer technology.

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