129 research outputs found

    Collaborative, Intelligent, and Adaptive Systems for the Low-Power Internet of Things

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    With the emergence of the Internet of Things (IoT), more and more devices are getting equipped with communication capabilities, often via wireless radios. Their deployments pave the way for new and mission-critical applications: cars will communicate with nearby vehicles to coordinate at intersections; industrial wireless closed-loop systems will improve operational safety in factories; while swarms of drones will coordinate to plan collision-free trajectories. To achieve these goals, IoT devices will need to communicate, coordinate, and collaborate over the wireless medium. However, these envisioned applications necessitate new characteristics that current solutions and protocols cannot fulfill: IoT devices require consistency guarantees from their communication and demand for adaptive behavior in complex and dynamic environments.In this thesis, we design, implement, and evaluate systems and mechanisms to enable safe coordination and adaptivity for the smallest IoT devices. To ensure consistent coordination, we bring fault-tolerant consensus to low-power wireless communication and introduce Wireless Paxos, a flavor of the Paxos algorithm specifically tailored to low-power IoT. We then present STARC, a wireless coordination mechanism for intersection management combining commit semantics with synchronous transmissions. To enable adaptivity in the wireless networking stack, we introduce Dimmer and eAFH. Dimmer combines Reinforcement Learning and Multi-Armed Bandits to adapt its communication parameters and counteract the adverse effects of wireless interference at runtime while optimizing energy consumption in normal conditions. eAFH provides dynamic channel management in Bluetooth Low Energy by excluding and dynamically re-including channels in scenarios with mobility. Finally, we demonstrate with BlueSeer that a device can classify its environment, i.e., recognize whether it is located in a home, office, street, or transport, solely from received Bluetooth Low Energy signals fed into an embedded machine learning model. BlueSeer therefore increases the intelligence of the smallest IoT devices, allowing them to adapt their behaviors to their current surroundings

    Coordination and Self-Adaptive Communication Primitives for Low-Power Wireless Networks

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    The Internet of Things (IoT) is a recent trend where objects are augmented with computing and communication capabilities, often via low-power wireless radios. The Internet of Things is an enabler for a connected and more sustainable modern society: smart grids are deployed to improve energy production and consumption, wireless monitoring systems allow smart factories to detect faults early and reduce waste, while connected vehicles coordinate on the road to ensure our safety and save fuel. Many recent IoT applications have stringent requirements for their wireless communication substrate: devices must cooperate and coordinate, must perform efficiently under varying and sometimes extreme environments, while strict deadlines must be met. Current distributed coordination algorithms have high overheads and are unfit to meet the requirements of today\u27s wireless applications, while current wireless protocols are often best-effort and lack the guarantees provided by well-studied coordination solutions. Further, many communication primitives available today lack the ability to adapt to dynamic environments, and are often tuned during their design phase to reach a target performance, rather than be continuously updated at runtime to adapt to reality.In this thesis, we study the problem of efficient and low-latency consensus in the context of low-power wireless networks, where communication is unreliable and nodes can fail, and we investigate the design of a self-adaptive wireless stack, where the communication substrate is able to adapt to changes to its environment. We propose three new communication primitives: Wireless Paxos brings fault-tolerant consensus to low-power wireless networking, STARC is a middleware for safe vehicular coordination at intersections, while Dimmer builds on reinforcement learning to provide adaptivity to low-power wireless networks. We evaluate in-depth each primitive on testbed deployments and we provide an open-source implementation to enable their use and improvement by the community

    Byzantine state machine replication for the masses

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    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

    Synchronous and Concurrent Transmissions for Consensus in Low-Power Wireless

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    With the emergence of the Internet of Things, autonomous vehicles and the Industry 4.0, the need for dependable yet adaptive network protocols is arising. Many of these applications build their operations on distributed consensus. For example, UAVs agree on maneuvers to execute, and industrial systems agree on set-points for actuators.Moreover, such scenarios imply a dynamic network topology due to mobility and interference, for example. Many applications are mission- and safety-critical, too.Failures could cost lives or precipitate economic losses.In this thesis, we design, implement and evaluate network protocols as a step towards enabling a low-power, adaptive and dependable ubiquitous networking that enables consensus in the Internet of Things. We make four main contributions:- We introduce Orchestra that addresses the challenge of bringing TSCH (Time Slotted Channel Hopping) to dynamic networks as envisioned in the Internet of Things. In Orchestra, nodes autonomously compute their local schedules and update automatically as the topology evolves without signaling overhead. Besides, it does not require a central or distributed scheduler. Instead, it relies on the existing network stack information to maintain the schedules.- We present A2 : Agreement in the Air, a system that brings distributed consensus to low-power multihop networks. A2 introduces Synchrotron, a synchronous transmissions kernel that builds a robust mesh by exploiting the capture effect, frequency hopping with parallel channels, and link-layer security. A2 builds on top of this layer and enables the two- and three-phase commit protocols, and services such as group membership, hopping sequence distribution, and re-keying.- We present Wireless Paxos, a fault-tolerant, network-wide consensus primitive for low-power wireless networks. It is a new variant of Paxos, a widely used consensus protocol, and is specifically designed to tackle the challenges of low-power wireless networks. By utilizing concurrent transmissions, it provides a dependable low-latency consensus.- We present BlueFlood, a protocol that adapts concurrent transmissions to Bluetooth. The result is fast and efficient data dissemination in multihop Bluetooth networks. Moreover, BlueFlood floods can be reliably received by off-the-shelf Bluetooth devices such as smartphones, opening new applications of concurrent transmissions and seamless integration with existing technologies

    QuePaxa: Escaping the tyranny of timeouts in consensus

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    Leader-based consensus algorithms are fast and efficient under normal conditions, but lack robustness to adverse conditions due to their reliance on timeouts for liveness. We present QuePaxa, the first protocol offering state-of-the-art normal-case efficiency without depending on timeouts. QuePaxa uses a novel randomized asynchronous consensus core to tolerate adverse conditions such as denial-of-service (DoS) attacks, while a one-round-trip fast path preserves the normal-case efficiency of Multi-Paxos or Raft. By allowing simultaneous proposers without destructive interference, and using short hedging delays instead of conservative timeouts to limit redundant effort, QuePaxa permits rapid recovery after leader failure without risking costly view changes due to false timeouts. By treating leader choice and hedging delay as a multi-armed-bandit optimization, QuePaxa achieves responsiveness to prevalent conditions, and can choose the best leader even if the current one has not failed. Experiments with a prototype confirm that QuePaxa achieves normal-case LAN and WAN performance of 584k and 250k cmd/sec in throughput, respectively, comparable to Multi-Paxos. Under conditions such as DoS attacks, misconfigurations, or slow leaders that severely impact existing protocols, we find that QuePaxa remains live with median latency under 380ms in WAN experiments

    Understanding Scalability Issues in Sharded Blockchains

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    Since the release of Bitcoin in 2008, cryptocurrencies have attracted attention from academia, government, and enterprises. Blockchain, the backbone ledger in many cryptocurrencies, has shown its potential to be a data structure carrying information over the network securely without the need for a centralized trust party. In this thesis, I delve into the consensus protocols used in permissioned blockchains and analyze the sharding technique that aims to improve the scalability in blockchain systems. I discuss a permissioned sharded blockchain that I use to examine different methods to interleave blocks, referred to as strong temporal coupling and weak temporal coupling. I provide empirical experiments to show the roles of lightweight nodes in solving the scalability issues in sharded blockchain systems. The results suggest that the weak temporal coupling method performs worse than the strong temporal coupling method and is more susceptible to an increase in network latency. The results also show the importance of separating the roles of nodes and adding lightweight nodes to improve the performance and scalability of sharded blockchain systems
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