An Effective Offloading Model Based on Genetic Markov Process for Cloud Mobile Applications

2020 ◽  
pp. 38-50
Author(s):  
Mohamed S. Zalat ◽  
Saad M. Darwish ◽  
Magda M. Madbouly
Keyword(s):  
Markov Process ◽  
Mobile Applications ◽  
Model Based

scholarly journals A novel wideband dynamic directional indoor channel model based on a Markov process

2005 ◽  
Vol 4 (4) ◽  
pp. 1539-1552 ◽  
Author(s):  
Chia-Chin Chong ◽  
Chor-Min Tan ◽  
D.I. Laurenson ◽  
S. McLaughlin ◽  
M.A. Beach ◽  
...  
Keyword(s):  
Markov Process ◽  
Channel Model ◽  
Model Based

scholarly journals An Analysis and Testing of Functional Availability Military Vehicles, in the Aspect of Reliability

2019 ◽  
Vol 49 (1) ◽  
pp. 405-423
Author(s):  
Kamil Przybysz
Keyword(s):  
Mathematical Model ◽  
Markov Process ◽  
Model Based ◽  
Military Vehicles ◽  
Different Types ◽  
The Military ◽  
Exploitation Intensity ◽  
The Way

Abstract The paper pertains to matters related to the quantification of functional availability of military vehicles, with reference to exploitation intensity and reliability aspects. The conducted exploitation research paved the way for elaborating methods of determining functional availability for military vehicles, in particular focusing on exploitation intensity and reliability. The essential research was conducted using the developed mathematical model based on the probabilistic, stochastic Markov process, which allowed modelling the process of changes in the exploitation states of military vehicles. In the course of the research, which enabled the authors to estimate the functional availability value, four-layered probes of the military vehicles were used (different types and makes), from the second exploitation phase, with varied mileage from the beginning of the exploitation and average mileage per year.

scholarly journals Performance Analysis of Spotify® for Android with Model-Based Testing

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Ana Rosario Espada ◽  
María del Mar Gallardo ◽  
Alberto Salmerón ◽  
Pedro Merino
Keyword(s):  
Experimental Study ◽  
Mobile Applications ◽  
Test Cases ◽  
Traffic Patterns ◽  
User Interactions ◽  
Model Based ◽  
User Behaviors ◽  
Model Based Testing ◽  
The Impact ◽  
User Actions

This paper presents the foundations and the real use of a tool to automatically detect anomalies in Internet traffic produced by mobile applications. In particular, our MVE tool is focused on analyzing the impact that user interactions have on the traffic produced and received by the smartphones. To make the analysis exhaustive with regard to the potential user behaviors, we follow a model-based approach to automatically generate test cases to be executed on the smartphones. In addition, we make use of a specification language to define traffic patterns to be compared with the actual traffic in the device. MVE also includes monitoring and verification support to detect executions that do not fit the patterns. In these cases, the developer will obtain detailed information on the user actions that produce the anomaly in order to improve the application. To validate the approach, the paper presents an experimental study with the well-known Spotify app for Android, in which we detected some interesting behaviors. For instance, some HTTP connections do not end successfully due to timeout errors from the remote Spotify service.

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