A gentle transition from Java programming to Web Services using XML-RPC

Exposing students to leading edge vocational areas of relevance such as Web Services can be difficult. We show a lightweight approach by embedding a key component of Web Services within a Level 3 BSc module in Distributed Computing. We present a ready to use collection of lecture slides and student activities based on XML-RPC. In addition we show that this material addresses the central topics in the context of web services as identified by Draganova (2003)

Cloud Based IoT Architecture

The Internet of Things (IoT) and cloud computing have grown in popularity over the past decade as the internet becomes faster and more ubiquitous. Cloud platforms are well suited to handle IoT systems as they are accessible and resilient, and they provide a scalable solution to store and analyze large amounts of IoT data. IoT applications are complex software systems and software developers need to have a thorough understanding of the capabilities, limitations, architecture, and design patterns of cloud platforms and cloud-based IoT tools to build an efficient, maintainable, and customizable IoT application. As the IoT landscape is constantly changing, research into cloud-based IoT platforms is either lacking or out of date. The goal of this thesis is to describe the basic components and requirements for a cloud-based IoT platform, to provide useful insights and experiences in implementing a cloud-based IoT solution using Microsoft Azure, and to discuss some of the shortcomings when combining IoT with a cloud platform

A Survey on Data Plane Programming with P4: Fundamentals, Advances, and Applied Research

With traditional networking, users can configure control plane protocols to match the specific network configuration, but without the ability to fundamentally change the underlying algorithms. With SDN, the users may provide their own control plane, that can control network devices through their data plane APIs. Programmable data planes allow users to define their own data plane algorithms for network devices including appropriate data plane APIs which may be leveraged by user-defined SDN control. Thus, programmable data planes and SDN offer great flexibility for network customization, be it for specialized, commercial appliances, e.g., in 5G or data center networks, or for rapid prototyping in industrial and academic research. Programming protocol-independent packet processors (P4) has emerged as the currently most widespread abstraction, programming language, and concept for data plane programming. It is developed and standardized by an open community and it is supported by various software and hardware platforms. In this paper, we survey the literature from 2015 to 2020 on data plane programming with P4. Our survey covers 497 references of which 367 are scientific publications. We organize our work into two parts. In the first part, we give an overview of data plane programming models, the programming language, architectures, compilers, targets, and data plane APIs. We also consider research efforts to advance P4 technology. In the second part, we analyze a large body of literature considering P4-based applied research. We categorize 241 research papers into different application domains, summarize their contributions, and extract prototypes, target platforms, and source code availability.Comment: Submitted to IEEE Communications Surveys and Tutorials (COMS) on 2021-01-2

Towards Expressive and Versatile Visualization-as-a-Service (VaaS)

The rapid growth of data in scientific visualization has posed significant challenges to the scalability and availability of interactive visualization tools. These challenges can be largely attributed to the limitations of traditional monolithic applications in handling large datasets and accommodating multiple users or devices. To address these issues, the Visualization-as-a-Service (VaaS) architecture has emerged as a promising solution. VaaS leverages cloud-based visualization capabilities to provide on-demand and cost-effective interactive visualization. Existing VaaS has been simplistic by design with focuses on task-parallelism with single-user-per-device tasks for predetermined visualizations. This dissertation aims to extend the capabilities of VaaS by exploring data-parallel visualization services with multi-device support and hypothesis-driven explorations. By incorporating stateful information and enabling dynamic computation, VaaS\u27 performance and flexibility for various real-world applications is improved. This dissertation explores the history of monolithic and VaaS architectures, the design and implementations of 3 new VaaS applications, and a final exploration of the future of VaaS. This research contributes to the advancement of interactive scientific visualization, addressing the challenges posed by large datasets and remote collaboration scenarios

Enabling Artificial Intelligence Analytics on The Edge

This thesis introduces a novel distributed model for handling in real-time, edge-based video analytics. The novelty of the model relies on decoupling and distributing the services into several decomposed functions, creating virtual function chains (V F C model). The model considers both computational and communication constraints. Theoretical, simulation and experimental results have shown that the V F C model can enable the support of heavy-load services to an edge environment while improving the footprint of the service compared to state-of-the art frameworks. In detail, results on the V F C model have shown that it can reduce the total edge cost, compared with a monolithic and a simple frame distribution models. For experimenting on a real-case scenario, a testbed edge environment has been developed, where the aforementioned models, as well as a general distribution framework (Apache Spark ©), have been deployed. A cloud service has also been considered. Experiments have shown that V F C can outperform all alternative approaches, by reducing operational cost and improving the QoS. Finally, a migration model, a caching model and a QoS monitoring service based on Long-Term-Short-Term models are introduced

Web services choreography testing using semantic service description

Web services have become popular due to their ability to integrate with and to interoperate heterogeneous applications. Several web services can be combined into a single application to meet the needs of users. In the course of web services selection, a web candidate service needs to conform to the behaviour of its client, and one way of ensuring this conformity is by testing the interaction between the web service and its user. The existing web services test approaches mainly focus on syntax-based web services description, whilst the semantic-based solutions mostly address composite process flow testing. The aim of this research is to provide an automated testing approach to support service selection during automatic web services composition using Web Service Modeling Ontology (WSMO). The research work began with understanding and analysing the existing test generation approaches for web services. Second, the weaknesses of the existing approaches were identified and addressed by utilizing the choreography transition rules of WSMO in an effort to generate a Finite State Machine (FSM). The FSM was then used to generate the working test cases. Third, a technique to generate an FSM from Abstract State Machine (ASM) was adapted to be used with WSMO. This thesis finally proposed a new testing model called the Choreography to Finite State Machine (C2FSM) to support the service selection of an automatic web service composition. It proposed new algorithms to automatically generate the test cases from the semantic description (WSMO choreography description). The proposed approach was then evaluated using the Amazon E-Commerce Web Service WSMO description. The quality of the test cases generated using the proposed approach was measured by assessing their mutation adequacy score. A total of 115 mutants were created based on 7 mutant operators. A mutation adequacy score of 0.713 was obtained. The experimental validation demonstrated a significant result in the sense that C2FSM provided an efficient and feasible solution. The result of this research could assist the service consumer agents in verifying the behaviour of the Web service in selecting appropriate services for web service composition

Service Provisioning in Edge-Cloud Continuum Emerging Applications for Mobile Devices

Disruptive applications for mobile devices can be enhanced by Edge computing facilities. In this context, Edge Computing (EC) is a proposed architecture to meet the mobility requirements imposed by these applications in a wide range of domains, such as the Internet of Things, Immersive Media, and Connected and Autonomous Vehicles. EC architecture aims to introduce computing capabilities in the path between the user and the Cloud to execute tasks closer to where they are consumed, thus mitigating issues related to latency, context awareness, and mobility support. In this survey, we describe which are the leading technologies to support the deployment of EC infrastructure. Thereafter, we discuss the applications that can take advantage of EC and how they were proposed in the literature. Finally, after examining enabling technologies and related applications, we identify some open challenges to fully achieve the potential of EC, and also research opportunities on upcoming paradigms for service provisioning. This survey is a guide to comprehend the recent advances on the provisioning of mobile applications, as well as foresee the expected next stages of evolution for these applications

Plataforma de localização suportada por utilizadores de redes móveis

mestrado em Engenharia de Computadores e TelemáticaVivemos na era da informação e da Internet das coisas e por isso nunca antes a informação teve tanto valor, ao mesmo tempo nunca existiu tão elevada troca de informação. Com toda esta quantidade de dados e com o aumento substancial do poder computacional, tem-se assistido a uma explosão de ferramentas para o processamento destes dados em tempo real. Um novo paradigma também emergiu, pelo facto de que muita dessa informação tem meta informação da qual é possível extrair conhecimento adicional quando enriquecida. No caso dos operadores de telecomunicações existem vários fluxos de informação trocados entre dispositivos dos clientes, utilizadores de redes móveis e as antenas. Como exemplos são os casos dos pacotes Radius, Call Detail Records CDR’s e os Event Detail Records EDR’s que servem para o controlo de tráfego e para outros tipos de controlo e configurações. Em muitos destes pacotes vem incluída informação geográfica e temporal. Depressa se torna claro que a partir desta informação geográfica é possível extrair conhecimento e por isso valor adicional para os detentores da informação. Esta dissertação recorre a fluxos devidamente anonimizados que possuem informação de antenas (id e por isso posição e distância ao dispositivo). Neste trabalho é apresentada uma solução escalável e fiável que num ambiente de streaming determina a posição dos utilizadores de redes móveis, através de triangulação. A solução também determina métricas relativas a áreas geográficas. Devido a dificuldades externas, estes fluxos (dados) tiveram de ser simulados. As áreas são definidas e introduzidas por utilizadores da aplicação de forma a saberem as entradas e saídas, bem como o tempo de permanência em uma determinada área. Sendo o processamento realizado em ambiente de streaming, a solução desenvolvida tem de ser capaz de recuperar de falhas quando elas existirem de uma forma coerente e consistente.The time we live in is the time of information and the time of the Internet of Things. So, never before information had so much value. On the other hand, the volume of information exchange grows exponentially day by day. With all this amount of data as well with the computational power available nowadays, real time data processing tools emerge every day. A new paradigm emerges because there is a lot of meta information in this data exchange. With the enrichment of this meta information, it is possible to extract additional knowledge. From a telecommunication company point of view, there is a lot of exchanged data flows between clients’ devices and the Base Transceiver Station (BTS) such as, Radius packets, Call Detail Records (CDR) and Event Detail Records (EDR). Frequently, these flows are for control and configurations purposes. But in many cases, it also contains geographical and time information. Soon was clear that it is possible to perform data enrichment on this geographical information, in order to extract additional knowledge. In other words, additional value for the telecommunication company. This dissertation through data flows previously anonymized, that contain BTS’s information (e.g. position and distance from the client mobile), grants one scalable and reliable solution on a streaming environment that determines multiple metrics related to geographical areas. Due to external difficulties, it was necessary to simulate all the data flows. These areas are inputted by application user clients in order to know the number of people that get in or out of these areas as well the time spent inside. Since the work is done on streaming environment, the solution presented is able to recover from failures and fault tolerant in a consistent and coherent manner