A high-performance communication topology for decentralized protocols

Preserving transaction atomicity and ensuring its commitment is key to the maintenance of data integrity in a distributed database. The distributed consensus protocol is a prominent example of a mechanism used to accomplish safe commitment of a distributed transaction. These protocols are based primarily on repeated message exchange among all sites/nodes and their performance is characterized not only by the number of these messages but also by the underlying communication topology. This thesis proposes a measure of performance known as average message complexity and proposes a communication structure based on folded even graphs called the Folded Even Network (FEN). Performance of FEN is compared to other known structures and is shown to outperform them for various values of the number of nodes in the network. It is also shown that large topologies can be generated by connecting multiple FENs together. The expanded structure is also shown to have the same complexity as a single FEN

Practical Distributed Control Synthesis

Classic distributed control problems have an interesting dichotomy: they are either trivial or undecidable. If we allow the controllers to fully synchronize, then synthesis is trivial. In this case, controllers can effectively act as a single controller with complete information, resulting in a trivial control problem. But when we eliminate communication and restrict the supervisors to locally available information, the problem becomes undecidable. In this paper we argue in favor of a middle way. Communication is, in most applications, expensive, and should hence be minimized. We therefore study a solution that tries to communicate only scarcely and, while allowing communication in order to make joint decision, favors local decisions over joint decisions that require communication.Comment: In Proceedings INFINITY 2011, arXiv:1111.267

Systematizing Decentralization and Privacy: Lessons from 15 Years of Research and Deployments

Decentralized systems are a subset of distributed systems where multiple authorities control different components and no authority is fully trusted by all. This implies that any component in a decentralized system is potentially adversarial. We revise fifteen years of research on decentralization and privacy, and provide an overview of key systems, as well as key insights for designers of future systems. We show that decentralized designs can enhance privacy, integrity, and availability but also require careful trade-offs in terms of system complexity, properties provided, and degree of decentralization. These trade-offs need to be understood and navigated by designers. We argue that a combination of insights from cryptography, distributed systems, and mechanism design, aligned with the development of adequate incentives, are necessary to build scalable and successful privacy-preserving decentralized systems

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

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

Service selection and transactional management for web service composition

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