KUBERNETES CLUSTER MANAGEMENT FOR CLOUD COMPUTING PLATFORM: A SYSTEMATIC LITERATURE REVIEW

Kubernetes is designed to automate the deployment, scaling, and operation of containerized applications. With the scalability feature of Kubernetes technology, container automation processes can be implemented according to the number of concurrent users accessing them. Therefore, this research focuses on how Kubernetes as cluster management is implemented on several cloud computing platforms. Standard literature review method employing a manual search for several journals and conference proceedings. From 15 relevant studies, 5 addressed Kubernetes performance and scalability. Seven literature review addressed Kubernetes deployments. Two articles addressed Kubernetes comparison and the rest is addressed Kubernetes in IoT. Regarding the cloud computing cluster management challenges that must be overcome using Kubernetes: it is necessary to ensure that all configuration and management required for Docker containers are successfully set up on on-premises systems before deploying to the cloud or on-premises. Data from Kubernetes deployments can be leveraged to support capacity planning and design Kubernetes-based elastic applications

Blockchain and Property Technology

Blockchain technology has emerged as a revolutionary force in the real estate sector, promis ing transformative changes in how properties are bought, sold, and managed. This study delves into the integration of blockchain in real estate, emphasizing the development and testing of a practical proof-of-concept application. The research, undertaken during an internship at DevScope, critically examines the potential of blockchain to enhance trans parency, security, and efficiency in managing exclusivity contracts. The research starts with a comprehensive review of blockchain literature, exploring its diverse applications within the real estate industry. It delves into the intricacies of challenges faced and opportunities presented during the implementation of blockchain technology in this context. Through rigorous analysis, the study assesses the profound impact of blockchain on the real estate landscape, elucidating the multifaceted benefits and challenges inherent in deploying blockchain-based solutions. Furthermore, this research not only contributes valuable insights to the ongoing discourse surrounding blockchain in real estate but also presents practical implications. The findings are poised to inform strategic decisions, providing DevScope with a nuanced perspective on integrating blockchain technology into their products. Specifically, this study evaluates the feasibility of incorporating a blockchain-based solution into MaxWork, one of DevScope’s products, thereby paving the way for innovative advancements within the realm of Multiple Listing Service solutions.A tecnologia Blockchain emergiu como uma força revolucionária no setor imobiliário, prom etendo mudanças na forma como as propriedades são transacionadas e geridas. Este estudo explora a integração da blockchain no setor imobiliário, a partir do desenvolvimento de uma aplicação de prova de conceito. A pesquisa, realizada durante um estágio na DevScope, examina o potencial da Blockchain para melhorar a transparência, segurança e eficiência nas transações imobiliárias. A pesquisa inicia-se com uma revisão da literatura sobre Blockchain e Distributed Ledger Technology (DLT), explorando as diversas aplicações dentro da indústria imobiliária. O estudo avalia o impacto da blockchain no cenário imobiliário, elucidando os benefícios e desafios inerentes à implementação de soluções baseadas em Blockchain. Além disso, esta pesquisa não só contribui com insights valiosos para o contínuo debate sobre Blockchain no setor imobiliário, como também apresenta implicações práticas. As descobertas deste estudo proporcionam à DevScope uma perspectiva detalhada sobre a integração da tecnologia Blockchain. Especificamente, este estudo avalia a viabilidade de incorporar uma solução baseada em Blockchain no MaxWork, um dos principais produtos da DevScope, abrindo caminho para avanços inovadores no âmbito dos Multiple Listing Services (MLS)

Armazenamento de dados eficiente tolerante a faltas bizantinas em múltiplas nuvens com coordenação de metadados integrada a um gerenciador de containers

Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Ciência da Computação, Florianópolis, 2017.O armazenamento de dados em nuvens tem se tornado uma opção para permitir a geo-replicação. No contexto de aplicações críticas, é preciso garantir tolerância a faltas para que essas aplicações possam depender dos dados armazenados nas nuvens. Esta tese apresenta soluções para tornar mais simples e eficiente a operação de sistemas críticos que armazenam dados em múltiplos provedores de nuvem (Intercloud). Três contribuições integram esta tese. A primeira contribuição consiste em uma técnica denominada Antecipação de Pedidos (AdP) cujo objetivo é melhorar a eficiência de protocolos baseados em quóruns. Essa técnica é otimista e considera a latência dos provedores envolvidos na operação para paralelizar parcialmente fases de um protocolo. A aplicação da AdP no contexto desta tese resulta no RafeStore, um sistema confiável e eficiente de armazenamento de dados em múltiplas nuvens. O RafeStore considera uma categoria específica de dados multiversão, denominada Dado de Conteúdo Independente, cuja formação de novos valores não depende de valores anteriores. A avaliação do RafeStore usando provedores de nuvem comerciais demonstra que o mesmo requer menores latência e custo, quando comparado a outros sistemas baseados em quóruns bizantinos. A segunda contribuição desta tese refere-se à organização da execução de requisições, necessária quando múltiplos clientes atualizam simultaneamente um mesmo dado. Para tal fim, é proposto o sistema DORADO, que coordena metadados segundo a estratégia de replicação de máquinas de estado. O DORADO é projetado para funcionar no gerenciador de containers Kubernetes, visando o uso dessa emergente tecnologia de virtualização. A incorporação do DORADO ao Kubernetes por meio de integração torna a coordenação de metadados transparente sob a perspectiva do usuário. A avaliação de uma integração parcial demonstra a viabilidade dessa proposta. A contribuição final desta tese é o sistema denominado FITS, cuja função é orquestrar os sistemas RafeStore e DORADO. Dessa maneira, obtém-se um sistema de armazenamento de dados eficiente e tolerante a faltas que opera na Intercloud.Abstract : Storing data in clouds has become an option in enabling geo-replication. In the context of critical systems, fault tolerance is required in order for the applications to be able to rely on the data stored in the cloud. This thesis presents solutions to simplify and make the operation of critical systems which store data in multiple cloud providers (Intercloud) more efficient. The contributions in this Thesis are threefold. The first contribution of this thesis consists in a technique to improve the efficiency of quorum-based protocols. We named it Requests Anticipation. This technique is optimistic and considers latency of providers to partially parallelize phases in a protocol. Applying request anticipation in the storage context results in RafeStore, a dependable and efficient system which stores data in multiple clouds. RafeStore considers a specific multiversion data type, named Data with Independent Content. With this type of data, new values are not necessarily related to previous ones. Our evaluation of RafeStore in commercial providers demonstrates that it requires lower latency and costs, when compared to other Byzantine quorum-based systems. The second contribution of this thesis refers to the organization of requests when multiple users simultaneously update the same data (i.e., race condition). To accomplish that, we propose DORADO: a system that manages metadata according to the strategy of state machine replication. DORADO was designed to work inside the container management system called Kubernetes, aiming at taking advantage of its emerging virtualization technology. Incorporating DORADO in Kubernetes via integration makes the metadata coordination transparent to the user. Our preliminary evaluation of the proposed approach demonstrates its viability. The third and final contribution of this thesis is FITS, a system that orchestrates RafeStore and DORADO. FITS enables the operation of an efficient and fault tolerant storage data system in the Intercloud

Introducing the new paradigm of Social Dispersed Computing: Applications, Technologies and Challenges

[EN] If last decade viewed computational services as a utility then surely this decade has transformed computation into a commodity. Computation is now progressively integrated into the physical networks in a seamless way that enables cyber-physical systems (CPS) and the Internet of Things (IoT) meet their latency requirements. Similar to the concept of ¿platform as a service¿ or ¿software as a service¿, both cloudlets and fog computing have found their own use cases. Edge devices (that we call end or user devices for disambiguation) play the role of personal computers, dedicated to a user and to a set of correlated applications. In this new scenario, the boundaries between the network node, the sensor, and the actuator are blurring, driven primarily by the computation power of IoT nodes like single board computers and the smartphones. The bigger data generated in this type of networks needs clever, scalable, and possibly decentralized computing solutions that can scale independently as required. Any node can be seen as part of a graph, with the capacity to serve as a computing or network router node, or both. Complex applications can possibly be distributed over this graph or network of nodes to improve the overall performance like the amount of data processed over time. In this paper, we identify this new computing paradigm that we call Social Dispersed Computing, analyzing key themes in it that includes a new outlook on its relation to agent based applications. We architect this new paradigm by providing supportive application examples that include next generation electrical energy distribution networks, next generation mobility services for transportation, and applications for distributed analysis and identification of non-recurring traffic congestion in cities. The paper analyzes the existing computing paradigms (e.g., cloud, fog, edge, mobile edge, social, etc.), solving the ambiguity of their definitions; and analyzes and discusses the relevant foundational software technologies, the remaining challenges, and research opportunities.Garcia Valls, MS.; Dubey, A.; Botti, V. (2018). Introducing the new paradigm of Social Dispersed Computing: Applications, Technologies and Challenges. Journal of Systems Architecture. 91:83-102. https://doi.org/10.1016/j.sysarc.2018.05.007S831029

Vertical Pod Autoscaling in Kubernetes for Elastic Container Collaborative Framework

Kubernetes is an open-source container management tool that automates container deployment, container load balancing, and container(de)scaling, including Horizontal Pod Autoscaler (HPA), Vertical Pod Autoscaler (VPA). HPA enables flawless operation, interactively scaling the number of resource units, or pods, without downtime. Default Resource Metrics, such as CPU and memory use of host machines and pods, are monitored by Kubernetes. Cloud Computing has emerged as a platform for individuals besides the corporate sector. It provides cost-effective infrastructure, platform, and software services in a shared environment. On the other hand, the emergence of industry 4.0 brought new challenges for the adaptability and infusion of cloud computing. As the global work environment is adapting constituents of industry 4.0 in terms of robotics, artificial intelligence, and IoT devices, it is becoming eminent that one emerging challenge is collaborative schematics. Provision of such autonomous mechanism that can develop, manage and operationalize digital resources like CoBots to perform tasks in a distributed and collaborative cloud environment for optimized utilization of resources, ensuring schedule completion. Collaborative schematics are also linked with Bigdata management produced by large-scale industry 4.0 setups. Different use cases and simulation results showed a significant improvement in Pod CPU utilization, latency, and throughput over Kubernetes environment

Kontteihin perustuva videoprosessointi

In recent years, the development and proliferation of mobile devices and the increasing speed of data communication have accelerated the rapid growth of video creation and consumption. Social media, for instance, has embraced video as its essential part. However, different devices and platforms with various screen resolutions, video format capabilities and data communication speeds have created new challenges for video transcoding systems. Especially, system scalability is an important aspect to ensure a proper user experience for end-users by maintaining a high rate of overall transcoding speed despite usage peaks and fluctuating system load. One way to build a scalable, rapidly deployable video transcoding service is to wrap transcoding instances into lightweight, portable containers, virtualized at the operating system level. Since containers share the kernel of the host operating system, new instances can be quickly launched when necessary. First, this thesis discusses Linux container technology, its main derivatives and related tools. Furthermore, this thesis describes various utilities that facilitate the orchestration of Linux containers but also typical video processing and internet video technologies are introduced. In order to investigate the advantages of using containers, we implemented a video transcoding service that uses application containers virtualized in CoreOS operating systems. The transcoding service is run on Amazon EC2 (Elastic Compute Cloud) instances. In addition to evaluating the service in terms of functionality, the thesis also discusses the strengths and weaknesses of the development process and use of container technologies within the scope of this project.Viime vuosina mobiililaitteiden kehittyminen ja nopea leviäminen sekä nopeutuvat tietoliikenneyhteydet ovat kiihdyttäneet videoiden luonnin ja kulutuksen ripeää kasvua. Videosta on tullut olennainen osa sosiaalista mediaa. Erilaiset laitteet ja alustat vaihtelevilla näyttöresoluutioilla, videoformaattituilla sekä tietoliikenneyhteyksien nopeuksilla ovat kuitenkin luoneet uusia haasteita videoiden prosessointiin. Erityisesti skaalautuvuus on olennainen aspekti yritettäessä varmistaa loppukäyttäjille asianmukainen käyttökokemus ylläpitämällä korkeaa prosessointinopeutta huolimatta käyttöpiikeistä ja vaihtelevasta systeemin kuormituksesta. Eräs tapa rakentaa skaalautuva, ripeästi käyttöönotettava videoiden prosessointipalvelu on paketoida prosessointi-instanssit kevytrakenteisiin, helposti liikuteltaviin kontteihin, jotka virtualisoidaan käyttöjärjestelmätasolla. Koska kontit käyttävät samaa käyttöjärjestelmän ydintä, uusia instansseja voidaan luoda tarpeen vaatiessa hyvin nopeasti. Tässä työssä esitellään Linux-kontteja ja joitakin sen johdannaisia sekä aiheeseen liittyviä työkaluja. Lisäksi erilaisia konttien orkestrointia helpottavia apuohjelmia käydään läpi, kuten myös videoprosessoinnin peruskäsitteitä ja Internetissä käytettyjä videoteknologioita. Tutkiaksemme konttien käytöstä saatavia hyötyjä toteutettiin videoiden prosessointipalvelu, joka käyttää CoreOS-käyttöjärjestelmän päälle virtualisoituja sovelluskontteja. Se rakennetaan Amazonin EC2-instanssien päälle. Palvelua ei arvioida ainoastaan toiminnallisuuden kannalta, vaan myös kehittämisvaiheen sekä konttien käytön hyviä ja huonoja puolia käsitellään