Research on Methods for Discovering and Selecting Cloud Infrastructure Services Based on Feature Modeling

Nowadays more and more cloud infrastructure service providers are providing large numbers of service instances which are a combination of diversified resources, such as computing, storage, and network. However, for cloud infrastructure services, the lack of a description standard and the inadequate research of systematic discovery and selection methods have exposed difficulties in discovering and choosing services for users. First, considering the highly configurable properties of a cloud infrastructure service, the feature model method is used to describe such a service. Second, based on the description of the cloud infrastructure service, a systematic discovery and selection method for cloud infrastructure services are proposed. The automatic analysis techniques of the feature model are introduced to verify the model’s validity and to perform the matching of the service and demand models. Finally, we determine the critical decision metrics and their corresponding measurement methods for cloud infrastructure services, where the subjective and objective weighting results are combined to determine the weights of the decision metrics. The best matching instances from various providers are then ranked by their comprehensive evaluations. Experimental results show that the proposed methods can effectively improve the accuracy and efficiency of cloud infrastructure service discovery and selection

A Taxonomy of Quality Metrics for Cloud Services

[EN] A large number of metrics with which to assess the quality of cloud services have been proposed over the last years. However, this knowledge is still dispersed, and stakeholders have little or no guidance when choosing metrics that will be suitable to evaluate their cloud services. The objective of this paper is, therefore, to systematically identify, taxonomically classify, and compare existing quality of service (QoS) metrics in the cloud computing domain. We conducted a systematic literature review of 84 studies selected from a set of 4333 studies that were published from 2006 to November 2018. We specifically identified 470 metric operationalizations that were then classified using a taxonomy, which is also introduced in this paper. The data extracted from the metrics were subsequently analyzed using thematic analysis. The findings indicated that most metrics evaluate quality attributes related to performance efficiency (64%) and that there is a need for metrics that evaluate other characteristics, such as security and compatibility. The majority of the metrics are used during the Operation phase of the cloud services and are applied to the running service. Our results also revealed that metrics for cloud services are still in the early stages of maturity only 10% of the metrics had been empirically validated. The proposed taxonomy can be used by practitioners as a guideline when specifying service level objectives or deciding which metric is best suited to the evaluation of their cloud services, and by researchers as a comprehensive quality framework in which to evaluate their approaches.This work was supported by the Spanish Ministry of Science, Innovation and Universities through the Adapt@Cloud Project under Grant TIN2017-84550-R. The work of Ximena Guerron was supported in part by the Universidad Central del Ecuador (UCE), and in part by the Banco Central del Ecuador.Guerron, X.; Abrahao Gonzales, SM.; Insfran, E.; Fernández-Diego, M.; González-Ladrón-De-Guevara, F. (2020). A Taxonomy of Quality Metrics for Cloud Services. IEEE Access. 8:131461-131498. https://doi.org/10.1109/ACCESS.2020.3009079S131461131498

New method for summative evaluation of UML class diagrams based on graph similarities

This paper deals with the problem of the evaluation of the student's productions during the construction of a UML class diagram from textual speciations, which can be a tedious task for teachers. The main objective is to propose a method of summative and semi-automatic evaluation of the class diagrams produced by the students, in order to provide an educational reaction on the learning process, and to reduce the evaluation work for the teachers. To achieve this objective, we must analyze these productions and study the transformation, matching, similarity measurement and comparison of several UML graphs. From this study, we adopted a method based on the comparison and matching of the components of several UML diagrams. This proposal is applied to evaluate UML class diagrams and focuses on the structural and semantic aspects of the UML graph produced by students compared to several solutions proposed by the teacher

Modelling Inter-Organizational Business Processes Governance

Digital transformation requires decentralizing business process governance due to the increasing interdependencies of organizations and more complex business pipelines enabled by information technologies. We present a modelling approach to assist companies in their inter-organizational business process governance (IO-BPG). The results emerge from a design science research conducted with a major European telecommunications service provider. They include (1) the key domain attributes, (2) a domain-specific ontology, and (3) a BPMN extension instantiated in IO-BPG scenarios of Software-as-a-Service, covering structure, processes, and relational mechanisms. For theory, this paper extends the literature on business process governance with a modelling approach evaluated in one of the most regulated and dynamic economic sectors. For practice, our proposal may help appraise accountability, confidentiality, compliance, autonomy, authority, traceability, and collaboration configurations that are crucial to IO-BPG

A Conceptual Framework for Accountability in Cloud Computing Service Provision

This paper uses a comprehensive review of the academic and professional literature in relation to accountability in the area of cloud computing service provision. It identifies four key conceptual factors that are necessary for an organisation to be considered as accountable. The four factors were found to be: responsibility, assurance, transparency and remediation. A key finding of the paper is that in order to be considered as an accountable cloud service provider, all four factors need to be implemented and be demonstrable by the organisation

Trust engineering framework for software services

La presente tesis presenta un marco de trabajo que abarca distintas fases del ciclo de vida de los servicios software y que permite a ingenieros de requisitos, diseñadores y desarrolladores la integración en dichos servicios de modelos de confianza y reputación. En la fase de planificación, proponemos una metodología para evaluar la confianza en proveedores de Cloud antes de decidir si el sistema, o parte de él, se traslada al mismo. En la fase de análisis, ofrecemos una notación para la captura y representación de requisitos de confianza y reputación. Asimismo en esta misma fase, desarrollamos una metodología que permite detectar amenazas internas en un sistema a través de análisis de relaciones de confianza. Para la fase de diseño, proponemos un perfil UML que permite la especificación de modelos de confianza y reputación, lo cual facilita la siguiente fase de implementación, para la que desarrollamos un marco de trabajo que los desarrolladores pueden usar para implementar una amplia variedad de modelos de confianza y reputación. Finalmente, para la fase de verificación en tiempo de ejecución, presentamos un marco de trabajo desarrollado sobre una plataforma de sistemas auto-adaptativos que implementa el paradigma de modelos en tiempo de ejecución. Con dicho marco de trabajo, hacemos posible que los desarrolladores puedan implementar modelos de confianza y reputación, y que puedan usar la información proporcionada por dichos modelos para especificar políticas de reconfiguración en tiempo de ejecución. Esto permite que el sistema se adapte de forma que se mantengan niveles tolerables de confianza y reputación en los componentes de los que consiste. Todo los trabajos anteriores se apoyan sobre un marco conceptual que captura y relaciona entre sí las nociones más relevantes en los dominios de la confianza y la reputación

How Accountable is Zakat Management in Indonesia? An Evidence from BAZNAS of North Sulawesi

This study was motivated by some zakat management accountability issues discovered in preliminary studies conducted in several zakat agencies throughout the North Sulawesi province. This study investigates zakat management accountability in three chapters/sub-chapters of the National Zakat Agency (Badan Amil Zakat Nasional – BAZNAS) in North Sulawesi province: the BAZNAS provincial chapter, the BAZNAS of Manado City sub-chapter, and the BAZNAS of Kotamobagu City sub-chapter. Data were collected using documentation studies and in-depth interviews with zakat administrators from the zakat institutions using purposive and snowball sampling techniques. To analyze the data, this study employed an Action Research (AR) approach, while the results were interpreted using a four-stage qualitative analysis: domain analysis, taxonomic analysis, componential analysis, and theme analysis. The findings indicate that zakat management in the targeted institutions has not fully met the accountability standard outlined in Law No. 23/2011, specifically in terms of 1) the absence of certain accountability indicators, 2) inefficient use of websites, 3) ineffective use of social media, and 4) the absence of an internal audit unit (SAI). The findings have implications for improving BAZNAS in North Sulawesi province and throughout Indonesia. In particular, this study suggests optimizing institution websites and social media by integrating them with provincial zakat institutions. Consequently, it is crucial to employ an IT expert who specializes in in-out information from/to society. The establishment of SAI and the employment of shariah auditors are also noteworthy. Collaboration with Islamic universities could be a first step towards a solution.==================================================================================================== ABSTRAK – Seberapa Akuntabelkah Pengelolaan Zakat di Indonesia? Kajian pada BAZNAS Sulawesi Utara. Kajian ini dilatarbelakangi oleh beberapa persoalan akuntabilitas pada pengelolaan zakat di beberapa BAZNAS dalam lingkungan provinsi Sulawesi Utara. Tulisan ini bertujuan untuk mengkaji akuntabilitas pada tiga BAZNAS di provinsi Sulawesi Utara, yaitu BAZNAS provinsi, BAZNAS Kota Manado, dan BAZNAS Kota Kotamobagu. Selain dari studi dokumentasi, data juga dikumpulkan melalui wawancara mendalam administrator zakat dari ketiga BAZNAS terkait yang dipilih berdasarkan teknik sampling purposif dan bola salju (snowball). Untuk menganalisis data, kajian ini menggunakan metode Action Research (AR), yang kemudian diinterpretasikan dalam empat tahapan analisis, yaitu analisis domain, analisis taksonomi, analisis komponensial, and analisis tema. Kajian ini menemukan bahwa pengelolaan zakat di objek penelitian tersebut belum sepenuhnya memenuhi kriteria akuntabilitas sebagaimana disebutkan dalam UU No. 23/2011, terutama dalam hal: 1) kealpaan dari dari beberapa indikator akuntabilitas, 2) websitenya belum optimal, 3) sosial media belum dimanfaatkan dengan baik, dan 4) ketiadaan dari satuan pengawasan internal. Hasil kajian ini berimplikasi pada perbaikan institusi BAZNAS di Sulawesi Utara secara khusus dan Indonesia secara umum. Kajian ini merekomendasikan adanya optimalisasi website dan media sosial dengan pengintegrasian ke dalam website BAZNAS provinsi. Oleh karenanya, diperlukan seorang profesional di bidang IT yang khusus mengelola segala informasi dari luar ke dalam dan sebaliknya. Selain itu, membangun sistem pengawasan internal dengan merekrut tenaga audit syariah juga sangat penting. Pada tahap awal, hal ini dapat dilakukan melalui kerjasama dengan PTKIN

Elastic neural network method for load prediction in cloud computing grid

Cloud computing still has no standard definition, yet it is concerned with Internet or network on-demand delivery of resources and services. It has gained much popularity in last few years due to rapid growth in technology and the Internet. Many issues yet to be tackled within cloud computing technical challenges, such as Virtual Machine migration, server association, fault tolerance, scalability, and availability. The most we are concerned with in this research is balancing servers load; the way of spreading the load between various nodes exists in any distributed systems that help to utilize resource and job response time, enhance scalability, and user satisfaction. Load rebalancing algorithm with dynamic resource allocation is presented to adapt with changing needs of a cloud environment. This research presents a modified elastic adaptive neural network (EANN) with modified adaptive smoothing errors, to build an evolving system to predict Virtual Machine load. To evaluate the proposed balancing method, we conducted a series of simulation studies using cloud simulator and made comparisons with previously suggested approaches in the previous work. The experimental results show that suggested method betters present approaches significantly and all these approaches