scholarly journals An Inhomogeneous Hidden Markov Model for Efficient Virtual Machine Placement in Cloud Computing Environments

2016 ◽  
Author(s):  
Hugo Lewi Hammer ◽  
Anis Yazidi ◽  
Kyrre Begnum
Keyword(s):  
Cloud Computing ◽  
Markov Model ◽  
Hidden Markov Model ◽  
Virtual Machine ◽  
Hidden Markov ◽  
Virtual Machine Placement ◽  
Computing Environments

scholarly journals Dynamic Range Method using Hiddenmarkov Models in RSA and DSA Algorithm

2020 ◽  
Vol 8 (12s3) ◽  
pp. 101-106
Keyword(s):  
Cloud Computing ◽  
Markov Model ◽  
Hidden Markov Model ◽  
Wireless Sensors ◽  
Dynamic Range ◽  
Hidden Markov ◽  
Research Field ◽  
Wireless Technologies ◽  
The Future ◽  
Verification Time

Dynamic range approach has become a highest level of research field from last some year. The initiative beyond this process researched field is the reality that some particularrange are used in current environment and also which is used or deploy in an in effectivemanner. Theoverall wireless various range are allocated and fixed, but it is not need to be used. So, at this time the requirement for research in various wireless technologies expanding and there is no space for the wireless various rangesto assignimportant frequency bandsrelated to the future wireless technologies. Therefore, this is a reason to increase the use of the various ranges. To target this, we must be calculating the method for sharing the range. Our purpose to find out the wireless sensors’ techniques, artificial Intelligencetechniques, cloud computing techniques for updating verification time of dynamic range approach. So, we used in this paper the Hidden Markov Model for defining the various types of range characteristics and forecast therangesample that will be obtained in future related methods. This forecast is used to define the RSA and DSA in better its verification time. The method for utilization HMM technique for minimizing the verification time of RSA and DSA will be executed in NS2 and Matlab simulator

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