SaaS-palvelun konfigurointi ja kustomointi: konfiguroinninhallintatyökalu digitaaliselle allekirjoituspalvelulle

Today, cloud computing – a result of combining existing technologies – is a popular paradigm that has brought many benefits for users and enterprises. Cloud computing fosters the provision and use of IT infrastructure, platforms, and applications of any kind in the form of services that are available on the Web. Expensive initial hardware and software investments are not necessary anymore as the resources can be acquired as a service from cloud providers with a pay-per-use pricing model. One aspect that cannot be overlooked in cloud computing is multi-tenancy. It is a property of a system where multiple customers, so-called tenants, transparently share the system's resources. It leverages economies of scale where users and cloud providers benefit from reduced costs, which is a result of higher system density and increased utilization rate of resources. This model surpasses the traditional methods of using single-tenant architecture and ASP model in which a single instance or server is provisioned solely for one customer. Customizability is an essential part of multi-tenant systems. Ideally cloud application vendors wish that every user would be satisfied with the standardized offering, but usually users have their own unique business needs. Customizability can be divided into configuration, which supports differentiation by pre-defined scope, and customization, which supports tenant's custom code. Software variations can be applied to user interface, business logic related workflows, underlying data and reporting utilities. Multi-tenancy shares a lot in common with software product line engineering. However, implementing multi-tenancy and supporting differentiation between tenants have to be carefully planned. Increased complexity may have an impact in maintenance costs and re-engineering costs can be significant. Goal of the thesis is to first examine the requirements for a multi-tenant application, and based on the research, to develop a prototype of a configuration management tool in order to solve the customization need produced by tenants' unique business requirements. The target environment consists of a new SaaS service called SignHero, which is a digital signature service suited for companies that want to shift their signing process to modern times. The scope includes three variability points: customizing the logo in the signing page, customizing the logo in the emails and saving a default workflow. The developed tool fulfills the requirements, and the main service was extended to apply the saved configurations. The implementation leaves many improvement possibilities related to customizability and cloud characteristics. Findings promote the fact that customizability has to be initially included in the product design

Architecting the deployment of cloud-hosted services for guaranteeing multitenancy isolation.

In recent years, software tools used for Global Software Development (GSD) processes (e.g., continuous integration, version control and bug tracking) are increasingly being deployed in the cloud to serve multiple users. Multitenancy is an important architectural property in cloud computing in which a single instance of an application is used to serve multiple users. There are two key challenges of implementing multitenancy: (i) ensuring isolation either between multiple tenants accessing the service or components designed (or integrated) with the service; and (ii) resolving trade-offs between varying degrees of isolation between tenants or components. The aim of this thesis is to investigate how to architect the deployment of cloud-hosted service while guaranteeing the required degree of multitenancy isolation. Existing approaches for architecting the deployment of cloud-hosted services to serve multiple users have paid little attention to evaluating the effect of the varying degrees of multitenancy isolation on the required performance, resource consumption and access privilege of tenants (or components). Approaches for isolating tenants (or components) are usually implemented at lower layers of the cloud stack and often apply to the entire system and not to individual tenants (or components). This thesis adopts a multimethod research strategy to providing a set of novel approaches for addressing these problems. Firstly, a taxonomy of deployment patterns and a general process, CLIP (CLoud-based Identification process for deployment Patterns) was developed for guiding architects in selecting applicable cloud deployment patterns (together with the supporting technologies) using the taxonomy for deploying services to the cloud. Secondly, an approach named COMITRE (COmponent-based approach to Multitenancy Isolation Through request RE-routing) was developed together with supporting algorithms and then applied to three case studies to empirically evaluate the varying degrees of isolation between tenants enabled by multitenancy patterns for three different cloud-hosted GSD processes, namely-continuous integration, version control, and bug tracking. After that, a synthesis of findings from the three case studies was carried out to provide an explanatory framework and new insights about varying degrees of multitenancy isolation. Thirdly, a model-based decision support system together with four variants of a metaheuristic solution was developed for solving the model to provide an optimal solution for deploying components of a cloud-hosted application with guarantees for multitenancy isolation. By creating and applying the taxonomy, it was learnt that most deployment patterns are related and can be implemented by combining with others, for example, in hybrid deployment scenarios to integrate data residing in multiple clouds. It has been argued that the shared component is better for reducing resource consumption while the dedicated component is better in avoiding performance interference. However, as the experimental results show, there are certain GSD processes where that might not necessarily be so, for example, in version control, where additional copies of the files are created in the repository, thus consuming more disk space. Over time, performance begins to degrade as more time is spent searching across many files on the disk. Extensive performance evaluation of the model-based decision support system showed that the optimal solutions obtained had low variability and percent deviation, and were produced with low computational effort when compared to a given target solution

Systematic analysis of software development in cloud computing perceptions

Cloud computing is characterized as a shared computing and communication infrastructure. It encourages the efficient and effective developmental processes that are carried out in various organizations. Cloud computing offers both possibilities and solutions of problems for outsourcing and management of software developmental operations across distinct geography. Cloud computing is adopted by organizations and application developers for developing quality software. The cloud has the significant impact on utilizing the artificial complexity required in developing and designing quality software. Software developmental organization prefers cloud computing for outsourcing tasks because of its available and scalable nature. Cloud computing is the ideal choice utilized for development modern software as they have provided a completely new way of developing real-time cost-effective, efficient, and quality software. Tenants (providers, developers, and consumers) are provided with platforms, software services, and infrastructure based on pay per use phenomenon. Cloud-based software services are becoming increasingly popular, as observed by their widespread use. Cloud computing approach has drawn the interest of researchers and business because of its ability to provide a flexible and resourceful platform for development and deployment. To determine a cohesive understanding of the analyzed problems and solutions to improve the quality of software, the existing literature resources on cloud-based software development should be analyzed and synthesized systematically. Keyword strings were formulated for analyzing relevant research articles from journals, book chapters, and conference papers. The research articles published in (2011–2021) various scientific databases were extracted and analyzed for retrieval of relevant research articles. A total of 97 research publications are examined in this SLR and are evaluated to be appropriate studies in explaining and discussing the proposed topic. The major emphasis of the presented systematic literature review (SLR) is to identify the participating entities of cloud-based software development, challenges associated with adopting cloud for software developmental processes, and its significance to software industries and developers. This SLR will assist organizations, designers, and developers to develop and deploy user-friendly, efficient, effective, and real time software applications.Qatar University Internal Grant - No. IRCC‐2021‐010

Efficient Learning Machines

Computer scienc

Computational Methods for Medical and Cyber Security

Over the past decade, computational methods, including machine learning (ML) and deep learning (DL), have been exponentially growing in their development of solutions in various domains, especially medicine, cybersecurity, finance, and education. While these applications of machine learning algorithms have been proven beneficial in various fields, many shortcomings have also been highlighted, such as the lack of benchmark datasets, the inability to learn from small datasets, the cost of architecture, adversarial attacks, and imbalanced datasets. On the other hand, new and emerging algorithms, such as deep learning, one-shot learning, continuous learning, and generative adversarial networks, have successfully solved various tasks in these fields. Therefore, applying these new methods to life-critical missions is crucial, as is measuring these less-traditional algorithms' success when used in these fields

Applications

Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel production and milling for quality control during manufacturing processes in traffic, logistics for smart cities and for mobile communications

Energy self-consumption policy, the future of distributed renewable generation?

Tese de mestrado integrado, Engenharia da Energia e do Ambiente, Universidade de Lisboa, Faculdade de Ciências, 2016The traditional energy system is undergoing a fundamental change, with demand profile trends created by growth stagnation, energy efficiency and self-consumption challenging conventional utility’s business model. At the same time political and structural transformations, such as the unbundling of the energy system itself, are redesigning stakeholders and how the whole system operates, symbolizing what could be the end of the term utility. This work looks into the growing trend of self-consumption policies for distributed generation of renewable energy systems, motivated by the crossing of socket parity and the phasing out of renewables subsidies. The work is divided into 4 main chapters, dedicated to: - An international assessment and characterization of existing self-consumption regimes,where 39 countries and 63 states were reviewed; - A proposal of operational and extended definitions to elucidate policy labelling, clarifying misconceptions around self-consumption, net-energy metering and net-energy billing terminologies; - A concept analysis to review the role of these policy instruments in the future of the energy system, its impacts and constrains; - And lastly, reflect on the potential of emerging concepts such as shared generation, peer-topeer energy trading, under regulations such as virtual metering, as a regulatory enhancement of existing self-consumption policies. The goal of this work is to provide key policy and regulatory considerations for devising more effective self-consumption policies. The future is still uncertain as policies and frameworks are yet to be consistent or stabilized, and a high degree of policy experimentalism is still present in these new grounds. We hope to portray a meaningful compilation of the main aspects regarding the concept, the typical implications and possible enhancements, to support regulators, the research community and decision makers in designing a path forward, that goes beyond utility scale renewable energy.O modus operandi do sistema energético tradicional está sob uma transformação de paradigma, com as alterações no perfil de consumo potenciadas pela estagnação do consumo, eficiência energética e autoconsumo de energia a desafiar os modelos de negócio dos agentes convencionais. Em paralelo existem transformações politicas e estruturais, como o unbundling do sistema energético, redesenhando os stakeholders e o funcionamento do sistema. Este trabalho investiga politicas de autoconsumo energético para produção de distribuída de energia renovável, uma tendência que ganha relevância com o atravessar da meta da paridade com a rede, e o abandono progressivo de subsídios à produção renovável. O trabalho está dividido em 4 capítulos principais, dedicados a:- Um levantamento internacional dos regimes de autoconsumo existentes, onde 39 países e 63 estados foram identificados;- Uma proposta de definições operacionais e de relações entre tipologias diferentes, para clarificar terminologias e evitar utilizações erróneas de conceitos como autoconsumo, net metering e net billing; - Uma análise de conceito para descrever o papel destes instrumentos políticos no futuro do sistema energético, os seus impactos e limitações.- Por fim, uma reflexão do potencial de conceitos emergentes como virtual metering, e o seu potencial para reforçar as politicas de autoconsumo tradicionais. O objetivo desta pesquisa é desenvolver considerações chave para o desenho de politicas de autoconsumo mais eficientes e adaptadas à realidade. O futuro destas politicas e regulamentações é ainda incerto, e estão longe de estabilizadas apresentando um grau de experimentalismo. Procurouse compilar de forma compreensiva e fundamentada os aspetos principais do conceito, as implicações usuais e possíveis melhoramentos, para apoiar reguladores, a comunidade cientifica e decisores políticos no design e desenvolvimento de caminhos, que vão além da produção centralizada de energias renováveis

User-Centric Traffic Engineering in Software Defined Networks

Software defined networking (SDN) is a relatively new paradigm that decouples individual network elements from the control logic, offering real-time network programmability, translating high level policy abstractions into low level device configurations. The framework comprises of the data (forwarding) plane incorporating network devices, while the control logic and network services reside in the control and application planes respectively. Operators can optimize the network fabric to yield performance gains for individual applications and services utilizing flow metering and application-awareness, the default traffic management method in SDN. Existing approaches to traffic optimization, however, do not explicitly consider user application trends. Recent SDN traffic engineering designs either offer improvements for typical time-critical applications or focus on devising monitoring solutions aimed at measuring performance metrics of the respective services. The performance caveats of isolated service differentiation on the end users may be substantial considering the growth in Internet and network applications on offer and the resulting diversity in user activities. Application-level flow metering schemes therefore, fall short of fully exploiting the real-time network provisioning capability offered by SDN instead relying on rather static traffic control primitives frequent in legacy networking. For individual users, SDN may lead to substantial improvements if the framework allows operators to allocate resources while accounting for a user-centric mix of applications. This thesis explores the user traffic application trends in different network environments and proposes a novel user traffic profiling framework to aid the SDN control plane (controller) in accurately configuring network elements for a broad spectrum of users without impeding specific application requirements. This thesis starts with a critical review of existing traffic engineering solutions in SDN and highlights recent and ongoing work in network optimization studies. Predominant existing segregated application policy based controls in SDN do not consider the cost of isolated application gains on parallel SDN services and resulting consequence for users having varying application usage. Therefore, attention is given to investigating techniques which may capture the user behaviour for possible integration in SDN traffic controls. To this end, profiling of user application traffic trends is identified as a technique which may offer insight into the inherent diversity in user activities and offer possible incorporation in SDN based traffic engineering. A series of subsequent user traffic profiling studies are carried out in this regard employing network flow statistics collected from residential and enterprise network environments. Utilizing machine learning techniques including the prominent unsupervised k-means cluster analysis, user generated traffic flows are cluster analysed and the derived profiles in each networking environment are benchmarked for stability before integration in SDN control solutions. In parallel, a novel flow-based traffic classifier is designed to yield high accuracy in identifying user application flows and the traffic profiling mechanism is automated. The core functions of the novel user-centric traffic engineering solution are validated by the implementation of traffic profiling based SDN network control applications in residential, data center and campus based SDN environments. A series of simulations highlighting varying traffic conditions and profile based policy controls are designed and evaluated in each network setting using the traffic profiles derived from realistic environments to demonstrate the effectiveness of the traffic management solution. The overall network performance metrics per profile show substantive gains, proportional to operator defined user profile prioritization policies despite high traffic load conditions. The proposed user-centric SDN traffic engineering framework therefore, dynamically provisions data plane resources among different user traffic classes (profiles), capturing user behaviour to define and implement network policy controls, going beyond isolated application management