Modelling and Simulation of QoS-Aware Service Selection in Cloud Computing

Eisa, Mona; Younas, Muhammad; Basu, Kashinath; Awan, Irfan

doi:10.1016/j.simpat.2020.102108

Cited by 39 publications

(28 citation statements)

References 17 publications

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“…This value will enable detecting all IT services, the functionality of which can match the sub-set ITacm 1 separated at Step 1. 4, at least by 25 % (similar to [16]).…”

Section: Checking the Possibility To Implement An Assessment Of The Degree Of Match Of The Information Technology Services And The Formulmentioning

confidence: 56%

“…As it follows from [16], the value of function (4) will aim to 2 if the description of the functional requirements implemented by the reusable IT service perfectly matches the description of the functional requirements for the process or the problem set by a customer.…”

Section: Results Of the Improvement Of The Model Of Precedent Of Automated Business Processmentioning

confidence: 99%

“…Thus, in [15], the scheme of choosing cloud services, based on a multi-purpose model of task planning by their cost and calculation time, was proposed. A multi-critical model for selecting cloud services taking into consideration their quality indicators, the values of which are determined from different sources, was developed in study [16]. A similar problem, but for conventional corporate networks, was considered in research [17].…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

“…A similar problem, but for conventional corporate networks, was considered in research [17]. In general, it should be recognized that the problems of selecting services, explored in [15][16][17], are based on the assumption that the functional requirements of users of these services are met as fully as possible. The validity of this assumption in [15][16][17] is not verified.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

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Improving a method for selecting information technology services

Рetrychenko

Левыкин

Iuriev

2021

EEJET

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The main purpose of modern information systems (IS) is to support the procedures of controlling many business processes (BP) of an enterprise. At the same time, due to a weak formalization of BP, processes of development, reengineering of various service-oriented IS and IT services are a complex problem. To address this problem, the task to improve the method for choosing IT services that meet an assigned set of functional and non-functional limitations was stated. The specific features of the original method for choosing IT services were analyzed, its main shortcomings were identified. The model of the BP precedent was modified to establish the relationship between descriptions of the precedent, functional requirements, and the used IT services. The method for selecting IT services for the IS was improved by adding the functions of requirements analysis and searching for descriptions of IT services that partially meet the stated functional requirements. In the method, the adaptive linear associator of the mADALIN neuron was used to quantify the degree of match of the functional requirement and the description of the function of the IT service. These proposals were the basis for the improved method for selecting the IT service that best fits the set of constraints that are formed. Based on the result of the conducted research, an experimental test of the improved method for selecting an IT service to solve the problem of automation of the activities of sale force of the electronic policy OSAGO was carried out. The information technology implementing the original method for choosing IT services was compared to the improved method. It was shown that the improved method makes it possible to identify situations of a match of functional requirements of a customer and the descriptions of IT services. This makes it possible to select those IT services that match the functional requirements to a degree above the assigned minimum limit

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“…This value will enable detecting all IT services, the functionality of which can match the sub-set ITacm 1 separated at Step 1. 4, at least by 25 % (similar to [16]).…”

Section: Checking the Possibility To Implement An Assessment Of The Degree Of Match Of The Information Technology Services And The Formulmentioning

confidence: 56%

Section: Results Of the Improvement Of The Model Of Precedent Of Automated Business Processmentioning

confidence: 99%

Section: Literature Review and Problem Statementmentioning

confidence: 99%

Section: Literature Review and Problem Statementmentioning

confidence: 99%

See 2 more Smart Citations

Improving a method for selecting information technology services

Рetrychenko

Левыкин

Iuriev

2021

EEJET

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“…[4][5][6] One of the main research trends of autonomic computing application is self-adaptive Cloud systems. [7][8][9][10][11][12][13][14] Indeed, within large datacenters running some large-scale applications, the autonomicity of the underlying systems is a key feature to meet the performance, availability and service level agreements (SLAs) while ensuring a cost effectiveness of offered services. During our study, we identified two topics in the context of self-adaptive Cloud systems that got increasing attention over the last years: (a) self-adaptive resource allocation in an on-demand basis and (b) self-healing feature that provides fault-tolerance capabilities.…”

Section: Introductionmentioning

confidence: 99%

Designing a methodological framework for modeling and performance forecasting of self‐adaptive cloud systems

Sliem

Salmi

Ioualalen

2021

Concurrency and Computation

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Autonomic computing got an increasing attention during past years in the context of Cloud computing in order to optimize the Cloud systems performance and increase their cost-effectiveness. In that direction, a broad range of various self-adaptability strategies have been proposed to overcome uncertainties related to Cloud systems like workload variations, hardware failures and malicious attacks. A special attention in the literature has been paid to resource allocation for cost and performance optimization, and self-healing for better faut-tolerance. However, while a lot of progress has been done on these topics, there is still a lack of a standardized methodology, easily reproducible and allowing validation and comparison of a self-adaptability strategies.This article proposes a methodology allowing to forecast the autonomic Cloud systems performances. The idea is to compare different self-adaptability approaches at the design stage, and identify the most adequate and optimized configuration. This methodology is based on a new architecture description language and a stochastic Petri nets-based modeling and simulation approach. We illustrate our methodology in this article through a running example and a set of experiments.

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Recommending cloud services based on social trust: An overview

Lebib,

Kichou

2024

Concurrency and Computation

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The continued expansion and development of the business requires great computing power and massive data storage systems. Cloud services deliver these resources in a simple, flexible and secure way. There is now a wide range of similar cloud services with different capabilities, which requires a recommendation system. Recommendation based on Quality of Service (QoS) is the first generation of service recommendation systems that only takes into account the rating information of all users without distinction. However, these systems suffer from many shortcomings, such as cold start and data sparsity issues, as well as poor accuracy and reliability of recommendation results. To address these issues and improve the quality of recommendations, a new generation of recommender systems has emerged, such as context‐aware, domain‐specific, and trust‐aware recommender systems. These systems now focus more on how to leverage social data generated from user interactions with each other in social networks to recommend more suitable and reliable services in response to user needs. Due to the importance of considering trust in cloud environments, this study aims to provide an overview of the research on trust‐based cloud service recommendation approaches proposed so far and highlights the current trend towards use new technologies such as deep learning to deal with certain challenges.

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Modelling and Simulation of QoS-Aware Service Selection in Cloud Computing

Cited by 39 publications

References 17 publications

Improving a method for selecting information technology services

Improving a method for selecting information technology services

Designing a methodological framework for modeling and performance forecasting of self‐adaptive cloud systems

Recommending cloud services based on social trust: An overview

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