Identification of Health, Safety and Environmental (HSE) Parameters Affecting Cloud Computing in Providing Intelligent Services in Rail Transportation System

Background and Objective: The present study was designed and conducted to identify and determine the parameters of health, safety, and environment (HSE) affecting cloud computing in providing intelligent services in the rail transportation system. Materials and Methods: This cross-sectional study was carried out based on the Delphi technique and expert opinions on the rail transportation system in 2020. This research was performed in five steps, including a comprehensive review of the related literature, identification, presentation of HSE parameters affecting cloud computing in providing intelligent services in the rail transportation system, and three Delphi rounds. Sixteen experts participated in the field of HSE and rail transportation. The coefficient of variation (CV) and desirability of each parameter were considered at < 20% and ≥ 4, respectively. Results: Based on this Delphi study, 15 parameters related to HSE and influential on cloud computing technology in the provision of intelligent services in the rail transportation system were introduced. Moreover, the CV index was estimated at 8.0%. The parameters of future research, the existence of a skilled workforce, and cloud service resource management tools had the highest degree of desirability (4.875). Conclusion: The findings indicated that identifying functions and challenges of HSE regarding cloud computing technology in the rail transportation system could help decision-makers to improve effective services in the rail transportation system and reduce the associated risks

Use of Cloud Gaming in Education

The use of digital games in education has been the subject of research for many years and their usefulness has been confirmed by many studies and research projects. Standardized tests, such as PISA test, show that respondents achieved better reading, math and physics results if they used the computer more for gaming-related activities. It has been proven that the application of video games in education increases student motivation, improves several types of key skills—social and intellectual skills, reflexes and concentration. Nevertheless, there are several challenges associated with the application of video games in schools and they can be categorized as technical (network and end device limitations), competency (teachers’ knowledge in the area), qualitative (lack of educational games of high quality), and financial (high cost of purchasing games and equipment). The novel architecture for delivery of gaming content commonly referred to as “cloud gaming” has the potential to solve most of the present challenges of using games in education. A well-designed cloud gaming platform would enable seamless and simple usage for both students and teachers. While solving most of the present problems, cloud gaming introduces a set of new research challenges which will be discussed in this section

Modelo de Calidad para Servicios Cloud

[EN] Modelo de Calidad para Servicios Cloud 4 Abstract Context: Cloud computing is a model of provision and consumption of services that offers many advantages to companies (high availability, flexibility, maximum utilization of resources, etc.) that result in quality requirements that must be met by the servi ce. In recent years there have been proposed numerous quality attributes and metrics for cloud services, but there is no study to collect this information and classified it with respect to internal and external characteristics of service (Quality of Servic e - QoS) and characteristics in use of the service (Quality of Experience - QoE). Objective: The objective of this final master ’s work is to define a model specific quality cloud services aligned with the ISO / IEC 25010, which integrate the quality feature s, attributes and metrics proposed in the literature and which allow to assess the quality cloud of artifacts in various stages of the life cycle. Method: We performed a systematic review of the literature in order to identify and analyze the attributes an d quality metrics proposed to assess the quality of cloud services. This method has been widely used in the field of Software Engineering and has proven useful to collect and analyze existing information on a particular research topic. Results: The result is a quality model for cloud services which has been built from 178 attributes and 364 metric obtained as a result of the systematic review. In particular, the results of the review indicate that 48% of proposals are metrics to measure performance efficien cy, reliability metrics following him with 23%. With respect to the phase of the life cycle, 55% of these metrics are used in the operation phase and 32% in the acquisition phase. Regarding the point of view of stakeholders, 39% of the metrics are oriented to the service provider, 33% consumer, 7% to the facilitator (broker) and only 5% service developer. With respect to cloud evaluated artifacts, most metrics (97%) are applied to the cloud service being tested or deployed in the cloud; only 2% of the metri cs are applied to the service architecture and 1% on the service specification. With regard to the validation, the results show that 99% of metric proposals lack any type of validation, although 44% presents a proof of concept illustrating how the metrics can be used. Additionally, we identified 27 attributes for cloud services, the elasticity was the most named, with 14%. Conclusions: The results of this work have provided relevant information on the current status and gaps that exist in the field of quali ty assessment of cloud services. They have also allowed us to define a quality model to meet some identified shortcomings. As future work, we intend to refine the proposed model, propose new metrics and adapt some existing architectures for evaluating clou d and empirical studies to provide evidence about theusefulness of a set of metrics[ES] El trabajo consiste en definir un modelo de calidad que determine las características de los servicios cloud y proporcione los mecanismos necesarios para evaluar su calidad. Se realizará una revisión sistemática de la literatura con el objetivo de identificar un conjunto de atributos de calidad, métricas e indicadores que permitirán medir las características identificadas. Como resultado se obtendrá un modelo de calidad alineado con la ISO/IEC 25010 que integrará las características de calidad, atributos, métricas e indicadores que dan soporte a su evaluación.[CA] Context: La computacio en el nuvol es un model de prestacio i consum de servicis que oferix moltes ventages a les empreses (alta disponibilitat, elasticitat, maxim aprofitament de recursos, etc.) que se traduixen en requisits de calitat que deuen ser complits pel servici. En els ultims anys s'han propost numerosos atributs de calitat i metriques per a servicis cloud, pero no existix un estudi que recoja esta informacio i la classifique en respecte a les caracteristiques internes i externes del servici (Quality of Service – QoS), aixina com caracteristiques en us del servici (Quality of Experience – QoE). Objectiu: L'objectiu d'este treball de fi de máster es definir un model de calitat especifica per a servicis cloud, enringlerat en l'ISO/IEC 25010, que integre les caracteristiques de calitat, atributs i metriques proposts en la lliteratura i que permeten evaluar la calitat dels artefactes cloud en distintes fases del cicle de vida. Metodo: S'ha realisat una revisio sistematica de la lliteratura en l'objectiu d'identificar i analisar els atributs i metriques de calitat propostes per a evaluar la calitat dels servicis cloud. Este metodo ha segut utilisat extensament en l'ambit de l'Ingenieria del Software i ha demostrat ser util per a recopilar i analisar l'informacio existent relativa a un determinat tema d'investigacio. Resultats: El resultat es un model de calitat per a servicis cloud que ha segut construit a partir dels 178 atributs i 364 metriques obtingudes com resultat de la revisio sistematica. En particular, els resultats de la revisio indiquen que el 48% de les metriques propostes son per a mesurar Eficiencia de desempenyorament, seguint-li les metriques de fiabilidad en en un 23%. En respecte a la fase del cicle de vida, un 55% d'estes metriques s'utilisen en la fase d'Operacio i un 32% en la fase d'Adquisicio. En respecte al punt de vista dels stakeholders, el 39% de les metriques estan orientades al proveïdor del servici, el 33% al consumidor, el 7% al facilitador (bróker) i nomes un 5% al desarrollador del servici. En respecte als artefactes cloud valorats, la majoria de les metriques (97%) s'apliquen sobre el servici cloud en fase de proves o desplegat en el cloud; nomes un 2% de les metriques s'apliquen sobre l'arquitectura del servici i un 1% sobre l'especificacio del servici. En respecte a la validacio, els resultats mostren que el 99% de les metriques propostes carixen de qualsevol tipo de validacio, encara que el 44% presenta una prova de concepte que ilustra com se pot utilisar les metriques. Adicionalment identifiquem 27 atributs propis dels servicis cloud, sent l'elasticitat el mes nomenat, en 14%. Conclusions: Els resultats del treball han proporcionat informacio rellevant sobre l'estat actual i les carencies que existixen en l'ambit de l'evaluacio de la calitat dels servicis cloud. Tambe mos han permes definir un model de calitat per a suplir algunes carencies identificades. Com trabajos futurs, pretenem refinar el model propost, propondre noves metriques i adaptar algunes existents per a l'evaluacio d'arquitectures cloud, aixina com realisar estudios empirics per a proporcionar evidencia al voltant de l'utilitat d'un conjunt de metriquesNavas Rosales, RM. (2016). Modelo de Calidad para Servicios Cloud. http://hdl.handle.net/10251/77847TFG

Modelo Comparativo de Plataformas Cloud y Evaluación de Microsoft Azure, Google App Engine y AmazonEC2

[ES] Existe una gran cantidad de proveedores de servicios en la nube siendo los más importantes Microsoft, Google y Amazon. Otros proveedores también son Rackspace, IBM, Oracle, Salesforce, etc. Un aspecto relevante para los desarrolladores y clientes es conocer las características de estos proveedores para tener información objetiva de cómo elegir entre una plataforma u otra dependiendo de sus objetivos y necesidades. En este proyecto se ha realizado un estudio para determinar las características de calidad relevantes de las plataformas cloud y se ha propuesto un modelo de calidad basado en la ISO/IEC 25010 para guiar a los usuarios en la comparación y selección de dichas plataformas. El modelo está soportado por un sistema de recomendación que permite a los usuarios especificar sus objetivos y comparar plataformas cloud mediante un conjunto de atributos y métricas de calidad. Este modelo se ha aplicado a un estudio para comparar las plataformas Microsoft Azure, Google App Engine y Amazon Elastic Compute Cloud (EC2) permitiendo la evaluación de sus características de calidad más relevantes.[EN] There is a large number of cloud service providers being the most important Microsoft, Google and Amazon. Other providers are also Rackspace, IBM, Oracle, Salesforce, etc. A relevant aspect for developers and customers is to determine the characteristics of these providers to have objective information on how to choose between one platform or another depending on their objectives and needs. In this project, we have carried out a study to determine the relevant quality characteristics of cloud platforms and a quality model based on ISO/IEC 25010 has been proposed to guide users in the comparison and selection of these platforms. The model is supported by a recommendation system that allows users to specify their objectives and compare cloud platforms through a set of quality attributes and metrics. This model has been applied to a case study which compares the Microsoft Azure, Google App Engine and Amazon Elastic Compute Cloud (EC2) platforms allowing the evaluation of its most relevant quality characteristics.Álvarez Vañó, JM. (2018). Modelo Comparativo de Plataformas Cloud y Evaluación de Microsoft Azure, Google App Engine y AmazonEC2. http://hdl.handle.net/10251/101221TFG

Exploring traffic and QoS management mechanisms to support mobile cloud computing using service localisation in heterogeneous environments

In recent years, mobile devices have evolved to support an amalgam of multimedia applications and content. However, the small size of these devices poses a limit the amount of local computing resources. The emergence of Cloud technology has set the ground for an era of task offloading for mobile devices and we are now seeing the deployment of applications that make more extensive use of Cloud processing as a means of augmenting the capabilities of mobiles. Mobile Cloud Computing is the term used to describe the convergence of these technologies towards applications and mechanisms that offload tasks from mobile devices to the Cloud. In order for mobile devices to access Cloud resources and successfully offload tasks there, a solution for constant and reliable connectivity is required. The proliferation of wireless technology ensures that networks are available almost everywhere in an urban environment and mobile devices can stay connected to a network at all times. However, user mobility is often the cause of intermittent connectivity that affects the performance of applications and ultimately degrades the user experience. 5th Generation Networks are introducing mechanisms that enable constant and reliable connectivity through seamless handovers between networks and provide the foundation for a tighter coupling between Cloud resources and mobiles. This convergence of technologies creates new challenges in the areas of traffic management and QoS provisioning. The constant connectivity to and reliance of mobile devices on Cloud resources have the potential of creating large traffic flows between networks. Furthermore, depending on the type of application generating the traffic flow, very strict QoS may be required from the networks as suboptimal performance may severely degrade an application’s functionality. In this thesis, I propose a new service delivery framework, centred on the convergence of Mobile Cloud Computing and 5G networks for the purpose of optimising service delivery in a mobile environment. The framework is used as a guideline for identifying different aspects of service delivery in a mobile environment and for providing a path for future research in this field. The focus of the thesis is placed on the service delivery mechanisms that are responsible for optimising the QoS and managing network traffic. I present a solution for managing traffic through dynamic service localisation according to user mobility and device connectivity. I implement a prototype of the solution in a virtualised environment as a proof of concept and demonstrate the functionality and results gathered from experimentation. Finally, I present a new approach to modelling network performance by taking into account user mobility. The model considers the overall performance of a persistent connection as the mobile node switches between different networks. Results from the model can be used to determine which networks will negatively affect application performance and what impact they will have for the duration of the user's movement. The proposed model is evaluated using an analytical approac