Abstract
Conflict-free Replicated Datatypes (CRDT) are usually classified as either state-based or operation-based. However, the standard definition of op-based CRDTs is very encompassing, allowing even sending the full-state, blurring the distinction. We introduce pure op-based CRDTs, that can only send operations to other replicas, drawing a clear distinction from state-based ones. Datatypes with commutative operations can be trivially implemented as pure op-based CRDTs using standard reliable causal delivery. We propose an extended API - tagged reliable causal broadcast - that provides causality information upon delivery, and show how it can be used to also implement other datatypes having non-commutative operations, through the use of a PO-Log - a partially ordered log of operations - inside the datatype. A semanticallybased PO-Log compaction framework, using both causality and what we denote by causal stability, allows obtaining very compact replica state for pure op-based CRDTs, while also benefiting from small message sizes.

Abstract
Many state-machine Byzantine Fault Tolerant (BFT) protocols have been introduced so far. Each protocol addressed a different subset of conditions and use-cases. However, if the underlying conditions of a service span different subsets, choosing a single protocol will likely not be a best fit. This yields robustness and performance issues which may be even worse in services that exhibit fluctuating conditions and workloads. In this paper, we reconcile existing state-machine BFT protocols in a single adaptive BFT system, called ADAPT, aiming at covering a larger set of conditions and use-cases, probably the union of individual subsets of these protocols. At anytime, a launched protocol in ADAPT can be aborted and replaced by another protocol according to a potential change (an event) in the underlying system conditions. The launched protocol is chosen according to an 'evaluation process' that takes into consideration both: protocol characteristics and its performance. This is achieved by applying some mathematical formulas that match the profiles of protocols to given user (e.g., service owner) preferences. ADAPT can assess the profiles of protocols (e.g., throughput) at run-time using Machine Learning prediction mechanisms to get accurate evaluations. We compare ADAPT with well known BFT protocols showing that it outperforms others as system conditions change and under dynamic workloads. © 2015 IEEE.

Abstract
Eventual consistency (EC) is a relaxed data consistency model that, driven by the CAP theorem, trades prompt consistency for high availability. Although, this model has shown to be promising and greatly adopted by industry, the state of the art only assumes that replicas can crash and recover. However, a Byzantine replica (i.e., arbitrary or malicious) can hamper the eventual convergence of replicas to a global consistent state, thus compromising the entire service. Classical BFT state machine replication protocols cannot solve this problem due to the blocking nature of consensus, something at odd with the availability via replica divergence in the EC model. In this work in progress paper, we introduce a new secure highly available protocol for the EC model that assumes a fraction of replicas and any client can be Byzantine. To respect the essence of EC, the protocol gives priority to high availability, and thus Byzantine detection is performed off the critical path on a consistent data offset. The paper concisely explains the protocol and discusses its feasibility. We aim at presenting a more comprehensive and empirical study in the future.

Abstract
Edge/Fog Computing is an extension to the Cloud Computing model, primarily proposed to pull some of the load on cloud data center towards the edge of the network, i.e., closer to the clients. Despite being a promising model, the foundations to adopt and fully exploit the edge model are yet to be clear, and thus new ideas are continuously advocated. In his paper on \Life beyond Distributed Transactions: An Apostate's Opinion", Pat Helland proposed his vision to build\almost innite" scale future applications, demonstrating why Distributed Transactions are not very practical under scale. His approach models the applications data state as independent \entities" with separate serialization scopes, thus allowing ecient local transactions within an entity, but precluding transactions involving dierent entities. Accessing remote data (which is assumed rare) can be done through separate channels in a more message-oriented manner. In this paper, we recall Helland's vision in the aforementioned paper, explaining how his model ts the Edge Computing Model either regarding scalability, applications, or assumptions, and discussing the potential challenges leveraged . © 2016 ACM.

Abstract
Aggregation protocols allow for distributed lightweight computations deployed on ad-hoc networks in a peer-to-peer fashion. Due to reliance on wireless technology, the communication medium is often hostile which makes such protocols susceptible to correctness and performance issues. In this paper, we study the behavior of aggregation protocols when subject to communication failures: message loss, duplication, and network partitions. We show that resolving communication failures at the communication layer, through a simple reliable communication layer, reduces the overhead of using alternative fault tolerance techniques at upper layers, and also preserves the original accuracy and simplicity of protocols. The empirical study we drive shows that tradeoffs exist across various aggregation protocols, and there is no one-size-fits-all protocol.

Abstract
Cryptocurrency and blockchain technologies are recently gaining wide adoption since the introduction of Bitcoin, being distributed, authority-free, and secure. Proof of Work (PoW) is at the heart of blockchain's security, asset generation, and maintenance. Although simple and secure, a hash-based PoW like Bitcoin's puzzle is often referred to as "useless", and the used intensive computations are considered "waste" of energy. A myriad of Proof of "something" alternatives have been proposed to mitigate energy consumption; however, they either introduced new security threats and limitations, or the "work" remained far from being really "useful". In this work, we introduce Proof of eXercise (PoX): a sustainable alternative to PoW where an eXercise is a real world matrix-based scientific computation problem. We provide a novel study of the properties of Bitcoin's PoW, the challenges of a more "rational" solution as PoX, and we suggest a comprehensive approach for PoX.