System Resource Sharing for Synchronous Collaboration

We describe problems associated with accessing data resources external to the application, which we term externalities, in replicated synchronous collaborative applications (e.g., a multiuser text editor). Accessing externalities such as les, databases, network connections, environment variables and the system clock is not as straightforward in replicated collaborative software as in single-user applications and centralized collaborative systems. We describe ad hoc solutions that have been used previously. Our primary objection to the ad hoc solutions is that the developer must program dierent behavior into the dierent replicas of a multi-user application, which increases the cost and complexity of development. We introduce a novel general approach to accessing externalities uniformly in a replicated collaborative system. The approach uses a semi-replicated architecture where the actual externality resides at a single location and is accessed via replicated proxies. The proxies multiplex input to and output from the single instance of the externality. This approach facilitates the creation of replicated synchronous groupware in two ways: (1) developers use the same mechanisms as in traditional single-user applications (2) developers program all replicas to execute the same behavior. We describe a general design for proxied access to read{only, write{only and read{write externalities. We discuss the tradeos of this semi- replicated approach over full, literal replication and the class of applications to which this approach can be successfully applied. We also describe details of a prototype implementation of this approach within a replicated collaboration-transparency system, called Flexible JAMM (Java Applets Made Multi-user)

A decentralized framework for cross administrative domain data sharing

Federation of messaging and storage platforms located in remote datacenters is an essential functionality to share data among geographically distributed platforms. When systems are administered by the same owner data replication reduces data access latency bringing data closer to applications and enables fault tolerance to face disaster recovery of an entire location. When storage platforms are administered by different owners data replication across different administrative domains is essential for enterprise application data integration. Contents and services managed by different software platforms need to be integrated to provide richer contents and services. Clients may need to share subsets of data in order to enable collaborative analysis and service integration. Platforms usually include proprietary federation functionalities and specific APIs to let external software and platforms access their internal data. These different techniques may not be applicable to all environments and networks due to security and technological restrictions. Moreover the federation of dispersed nodes under a decentralized administration scheme is still a research issue. This thesis is a contribution along this research direction as it introduces and describes a framework, called \u201cWideGroups\u201d, directed towards the creation and the management of an automatic federation and integration of widely dispersed platform nodes. It is based on groups to exchange messages among distributed applications located in different remote datacenters. Groups are created and managed using client side programmatic configuration without touching servers. WideGroups enables the extension of the software platform services to nodes belonging to different administrative domains in a wide area network environment. It lets different nodes form ad-hoc overlay networks on-the-fly depending on message destinations located in distinct administrative domains. It supports multiple dynamic overlay networks based on message groups, dynamic discovery of nodes and automatic setup of overlay networks among nodes with no server-side configuration. I designed and implemented platform connectors to integrate the framework as the federation module of Message Oriented Middleware and Key Value Store platforms, which are among the most widespread paradigms supporting data sharing in distributed systems

Data trust framework using blockchain and smart contracts

Lack of trust is the main barrier preventing more widespread data sharing. The lack of transparent and reliable infrastructure for data sharing prevents many data owners from sharing their data. Data trust is a paradigm that facilitates data sharing by forcing data controllers to be transparent about the process of sharing and reusing data. Blockchain technology has the potential to present the essential properties for creating a practical and secure data trust framework by transforming current auditing practices and automatic enforcement of smart contracts logic without relying on intermediaries to establish trust. Blockchain holds an enormous potential to remove the barriers of traditional centralized applications and propose a distributed and transparent administration by employing the involved parties to maintain consensus on the ledger. Furthermore, smart contracts are a programmable component that provides blockchain with more flexible and powerful capabilities. Recent advances in blockchain platforms toward smart contracts' development have revealed the possibility of implementing blockchain-based applications in various domains, such as health care, supply chain and digital identity. This dissertation investigates the blockchain's potential to present a framework for data trust. It starts with a comprehensive study of smart contracts as the main component of blockchain for developing decentralized data trust. Interrelated, three decentralized applications that address data sharing and access control problems in various fields, including healthcare data sharing, business process, and physical access control system, have been developed and examined. In addition, a general-purpose application based on an attribute-based access control model is proposed that can provide trusted auditability required for data sharing and access control systems and, ultimately, a data trust framework. Besides auditing, the system presents a transparency level that both access requesters (data users) and resource owners (data controllers) can benefit from. The proposed solutions have been validated through a use case of independent digital libraries. It also provides a detailed performance analysis of the system implementation. The performance results have been compared based on different consensus mechanisms and databases, indicating the system's high throughput and low latency. Finally, this dissertation presents an end-to-end data trust framework based on blockchain technology. The proposed framework promotes data trustworthiness by assessing input datasets, effectively managing access control, and presenting data provenance and activity monitoring. A trust assessment model that examines the trustworthiness of input data sets and calculates the trust value is presented. The number of transaction validators is defined adaptively with the trust value. This research provides solutions for both data owners and data users’ by ensuring the trustworthiness and quality of the data at origin and transparent and secure usage of the data at the end. A comprehensive experimental study indicates the presented system effectively handles a large number of transactions with low latency

BECA: A Blockchain-Based Edge Computing Architecture for Internet of Things Systems

The scale of Internet of Things (IoT) systems has expanded in recent times and, in tandem with this, IoT solutions have developed symbiotic relationships with technologies, such as edge Computing. IoT has leveraged edge computing capabilities to improve the capabilities of IoT solutions, such as facilitating quick data retrieval, low latency response, and advanced computation, among others. However, in contrast with the benefits offered by edge computing capabilities, there are several detractors, such as centralized data storage, data ownership, privacy, data auditability, and security, which concern the IoT community. This study leveraged blockchain’s inherent capabilities, including distributed storage system, non-repudiation, privacy, security, and immutability, to provide a novel, advanced edge computing architecture for IoT systems. Specifically, this blockchain-based edge computing architecture addressed centralized data storage, data auditability, privacy, data ownership, and security. Following implementation, the performance of this solution was evaluated to quantify performance in terms of response time and resource utilization. The results show the viability of the proposed and implemented architecture, characterized by improved privacy, device data ownership, security, and data auditability while implementing decentralized storage

Trustworthy Federated Learning: A Survey

Federated Learning (FL) has emerged as a significant advancement in the field of Artificial Intelligence (AI), enabling collaborative model training across distributed devices while maintaining data privacy. As the importance of FL increases, addressing trustworthiness issues in its various aspects becomes crucial. In this survey, we provide an extensive overview of the current state of Trustworthy FL, exploring existing solutions and well-defined pillars relevant to Trustworthy . Despite the growth in literature on trustworthy centralized Machine Learning (ML)/Deep Learning (DL), further efforts are necessary to identify trustworthiness pillars and evaluation metrics specific to FL models, as well as to develop solutions for computing trustworthiness levels. We propose a taxonomy that encompasses three main pillars: Interpretability, Fairness, and Security & Privacy. Each pillar represents a dimension of trust, further broken down into different notions. Our survey covers trustworthiness challenges at every level in FL settings. We present a comprehensive architecture of Trustworthy FL, addressing the fundamental principles underlying the concept, and offer an in-depth analysis of trust assessment mechanisms. In conclusion, we identify key research challenges related to every aspect of Trustworthy FL and suggest future research directions. This comprehensive survey serves as a valuable resource for researchers and practitioners working on the development and implementation of Trustworthy FL systems, contributing to a more secure and reliable AI landscape.Comment: 45 Pages, 8 Figures, 9 Table

Byzantine state machine replication for the masses

Tese de doutoramento, Informática (Ciência da Computação), Universidade de Lisboa, Faculdade de Ciências, 2018The state machine replication technique is a popular approach for building Byzantine fault-tolerant services. However, despite the widespread adoption of this paradigm for crash fault-tolerant systems, there are still few examples of this paradigm for real Byzantine fault-tolerant systems. Our view of this situation is that there is a lack of robust implementations of Byzantine fault-tolerant state machine replication middleware, and that the performance penalty is too high, specially for geo-replication. These hindrances are tightly coupled to the distributed protocols used for enforcing such resilience. This thesis has the objective of finding methodologies for enhancing robustness and performance of state machine replication systems. The first contribution is Mod-SMaRt, a modular protocol that preserves optimal latency in terms of the communications steps exchanged among processes. By being a modular protocol, it becomes simpler to validate and implement, thus resulting in greater robustness; by also preserving optimal message-exchanges among processes, the protocol is capable of delivering desirable performance. The second contribution is concerned with implementing Mod-SMaRt into BFTSMART, a reliable and high-performance codebase that was maintained and improved over the entire course of the PhD that offers multicore-awareness, reconfiguration support, and a flexible API. The third contribution presents WHEAT, a protocol derived from Mod-SMaRt that uses optimizations shown to be effective in reducing latency via a practical evaluation conducted in a geo distributed environment. We additionally conducted an evaluation of both BFT-SMART and WHEAT applied to a relational database middleware and an ordering service for a permissioned blockchain platform. These evaluations revealed encouraging results for both systems and validated our work conducted in the geo-distributed context.A técnica de replicação máquina de estados é um paradigma popular usado em vários sistemas distribuídos modernos. No entanto, apesar da adoção deste paradigma em sistemas reais tolerantes a faltas por paragem, ainda existem poucos exemplos de sistemas reais tolerantes a faltas bizantinas. Segundo a nossa experiência nesta área de investigação, isto deve-se ao fato de existirem poucas concretizações robustas para replicação máquina de estados tolerante a faltas bizantinas, assim como uma perda de desempenho demasiado elevada, especialmente em ambientes geo-replicados. A razão fundamental para a existência destes obstáculos vem dos protocolos distribuídos necessários para assegurar este tipo de resiliência. Esta tese tem como objetivo explorar metodologias para a robustez e eficiência da replicação máquina de estados. A primeira contribuição da tese é o algoritmo Mod-SMaRt, um protocolo modular que preserva latência ótima em termos de passos de comunicação executados pelos processos. Sendo um protocolo modular, torna-se mais simples de validar e concretizar, o que resulta em maior robustez; ao preservar troca de mensagens ótima entre processos, também é capaz de entregar um desempenho desejável. A segunda contribuição consiste em concretizar o protocolo Mod SMaRt na ferramenta BFT-SMART, uma biblioteca fiável de alto desempenho, mantida e melhorada ao longo de todo o período correspondente ao doutoramento, capaz de suportar arquiteturas multi-núcleo, reconfiguração do grupo de réplicas, e uma API de programação flexível. A terceira contribuição consiste em um protocolo derivado do Mod-SMaRt designado WHEAT, que usa otimizações que demostraram serem eficientes na redução da latência segundo uma avaliação prática em ambiente geo-replicado. Adicionalmente, foram também realizadas avaliações de ambos os protocolos quando aplicados num middleware para base de dados relacionais, e num serviço de ordenação para uma plataforma blockchain. Ambas as avaliações revelam resultados encorajadores para ambos os sistemas e validam o trabalho realizado em contexto geo-distribuído.Projeto IRCoC (PTDC/EEI-SCR/6970/2014); Comissão Europeia, FP7 (Seventh Framework Programme for Research and Technological Development), projetos FP7/2007-2013, ICT-25724

Framework for Real-time collaboration on extensive Data Types using Strong Eventual Consistency

La collaboration en temps réel est un cas spécial de collaboration où les utilisateurs travaillent sur le même élément simultanément et sont au courant des modifications des autres utilisateurs en temps réel. Les données distribuées doivent rester disponibles et consistant tout en étant répartis sur plusieurs systèmes physiques. "Strong Consistency" est une approche qui crée un ordre total des opérations en utilisant des mécanismes tel que le "locking". Cependant, cela introduit un "bottleneck". Ces dix dernières années, les algorithmes de concurrence ont été étudiés dans le but de garder la convergence de tous les replicas sans utiliser de "locking" ni de synchronisation. "Operational Trans- formation" et "Conflict-free Replicated Data Types (CRDT)" sont utilisés dans ce but. Cependant, la complexité de ces stratégies les rend compliquées à intégrer dans des logicielles conséquents, comme les éditeurs de modèles, spécialement pour des data structures complexes comme les graphes. Les implémentations actuelles intègrent seulement des data linéaires tel que le texte. Dans ce mémoire, nous présentons CollabServer, un framework pour construire des environnements de collaboration. Il a une implémentation de CRDTs pour des data structures complexes tel que les graphes et donne la possibilité de construire ses propres data structures.Real-time collaboration is a special case of collaboration where users work on the same artefact simultaneously and are aware of each other’s changes in real-time. Shared data should remain available and consistent while dealing with its physically distributed aspect. Strong Consistency is one approach that enforces a total order of operations using mechanisms, such as locking. This however introduces a bottleneck. In the last decade, algorithms for concurrency control have been studied to keep convergence of all replicas without locking or synchronization. Operational Transformation and Conflict free Replicated Data Types (CRDT) are widely used to achieve this purpose. However, the complexity of these strategies makes it hard to integrate in large software, such as modeling editors, especially for complex data types like graphs. Current implementations only integrate linear data, such as text. In this thesis, we present CollabServer, a framework to build collaborative environments. It features a CRDTs implementation for complex data types such as graphs and gives possibility to build other data structures

Self-management for large-scale distributed systems

Autonomic computing aims at making computing systems self-managing by using autonomic managers in order to reduce obstacles caused by management complexity. This thesis presents results of research on self-management for large-scale distributed systems. This research was motivated by the increasing complexity of computing systems and their management. In the first part, we present our platform, called Niche, for programming self-managing component-based distributed applications. In our work on Niche, we have faced and addressed the following four challenges in achieving self-management in a dynamic environment characterized by volatile resources and high churn: resource discovery, robust and efficient sensing and actuation, management bottleneck, and scale. We present results of our research on addressing the above challenges. Niche implements the autonomic computing architecture, proposed by IBM, in a fully decentralized way. Niche supports a network-transparent view of the system architecture simplifying the design of distributed self-management. Niche provides a concise and expressive API for self-management. The implementation of the platform relies on the scalability and robustness of structured overlay networks. We proceed by presenting a methodology for designing the management part of a distributed self-managing application. We define design steps that include partitioning of management functions and orchestration of multiple autonomic managers. In the second part, we discuss robustness of management and data consistency, which are necessary in a distributed system. Dealing with the effect of churn on management increases the complexity of the management logic and thus makes its development time consuming and error prone. We propose the abstraction of Robust Management Elements, which are able to heal themselves under continuous churn. Our approach is based on replicating a management element using finite state machine replication with a reconfigurable replica set. Our algorithm automates the reconfiguration (migration) of the replica set in order to tolerate continuous churn. For data consistency, we propose a majority-based distributed key-value store supporting multiple consistency levels that is based on a peer-to-peer network. The store enables the tradeoff between high availability and data consistency. Using majority allows avoiding potential drawbacks of a master-based consistency control, namely, a single-point of failure and a potential performance bottleneck. In the third part, we investigate self-management for Cloud-based storage systems with the focus on elasticity control using elements of control theory and machine learning. We have conducted research on a number of different designs of an elasticity controller, including a State-Space feedback controller and a controller that combines feedback and feedforward control. We describe our experience in designing an elasticity controller for a Cloud-based key-value store using state-space model that enables to trade-off performance for cost. We describe the steps in designing an elasticity controller. We continue by presenting the design and evaluation of ElastMan, an elasticity controller for Cloud-based elastic key-value stores that combines feedforward and feedback control

Quantum Computing Standards & Accounting Information Systems

This research investigates the potential implications of quantum technology on accounting information systems, and business overall. This endeavor focuses on the vulnerabilities of quantum computers and the emergence of quantum-resistant encryption algorithms. This paper critically analyzes quantum standards and their transformative effects on the efficiency, expediency, and security of commerce. By comparing the differences, similarities, and limitations of quantum standards, the research presents a collection of best practices and adaptation methods to fortify organizations against cyber threats in the quantum era. The study provides a guide to understanding and navigating the interplay between quantum technology and standard-setting organizations, enabling organizations to safeguard the integrity of their practices and adapt proactively to the challenges ushered in by the advent of quantum supremacy. This endeavor also contributes to research by painting the standard-setting ecosystem and noting its intricate processes. The findings include the identification of organizations involved with quantum standards, as well as observed distinctions, similarities, and limitations between American and European standards