Title
Predictive model to determine quality of service on Cloud Computing: Service Dependence Graph
Abstract
Absence of standards in technology providers such as Cloud Computing and Software as a Service (SaaS), becomes a clear risk factor that may involve their investments, while users may represent a constraint to effective competition within a market, and therefore their ability to choose as service applications and platforms. Therefore it is necessary to establish a risk management program that is flexible enough to deal with an environment variable and evolving risk. One of the main problems experienced by Cloud Computing services is the lack of documentation on the design of infrastructure, and the hardware used for the storage of information, so that the users are not sure how or where they are stored their data for example. This work aims to generate a model of assessment of the availability and efficiency within the available applications in the SaaS in order to establish priority of use through a statistical simulation and graphs. This needs be analyzing the non-functional requirements of the applications available in the SaaS which in turn make indirect use of Infrastructure as a Service (IaaS). Thus our model is projected as a guide that provides us design parameters for its evaluation and the availability based on the evolution of applications from the point of view of the user. To create this model, it is necessary to take into account an analysis of potential risks during application execution and data analysis consultation providing users, in order to efficiently manage resources in an organization.
Year
DOI
Venue
2016
10.1109/ICNSC.2016.7478997
2016 IEEE 13th International Conference on Networking, Sensing, and Control (ICNSC)
Keywords
Field
DocType
Statistical simulation,Assessment SaaS,Quality of service
Service design,Service level objective,Computer science,Risk analysis (engineering),Service provider,Software as a service,Service catalog,Control engineering,Utility computing,Data as a service,Database,Cloud computing
Conference
ISSN
Citations 
PageRank 
1810-7869
0
0.34
References 
Authors
1
4