arXiv subjects

Nuno Preguiça

Publications and source records attributed to Nuno Preguiça.

At least 19 recordsLinked to original sources

arXiv2022

Babel: A Framework for Developing Performant and Dependable Distributed Protocols

Prototyping and implementing distributed algorithms, particularly those that address challenges related with fault-tolerance and dependability, is a time consuming task. This is, in part, due to the need of addressing low level aspects such as management of communication channels, controlling timeouts or periodic tasks, and dealing with concurrency issues. This has a significant impact for researchers that want to build prototypes for conducting experimental evaluation; practitioners that want to compare different design alternatives/solutions; and even for practical teaching activities on distributed algorithms courses. In this paper we present Babel, a novel framework to develop, implement, and execute distributed protocols and systems. Babel promotes an event driven programming and execution model that simplifies the task of translating typical specifications or descriptions of algorithms into performant prototypes, while allowing the programmer to focus on the relevant challenges of these algorithms by transparently handling time consuming low level aspects. Furthermore, Babel provides, and allows the definition of, networking components that can capture different network capabilities (e.g., P2P, Client/Server, phi-accrual Failure Detector), making the code mostly independent from the underlying communication aspects. Babel was built to be generic and can be used to implement a wide variety of different classes of distributed protocols. We conduct our experimental work with two relevant case studies, a Peer-to-Peer application and a State Machine Replication application, that show the generality and ease of use of Babel and present competitive performance when compared with significantly more complex implementations.

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arXiv2022

Geo-located data for better dynamic replication

An increasing number of mobile applications share location-dependent information, from collaborative applications and social networks to location-based games. For such applications, peer-to-peer architectures where mobile devices share information directly may grant lower latency and reduce server load. In this work, we propose a framework to support these applications, providing location-dependent replication. Data has an associated location and is replicated in the mobile devices that show interest and are close to that location. Our proposal combines peer-to-peer synchronisation among mobile devices and replication at edge servers. Our preliminary results are promising.

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arXiv2020

Lazy State Determination: More concurrency for contending linearizable transactions

The concurrency control algorithms in transactional systems limits concurrency to provide strong semantics, which leads to poor performance under high contention. As a consequence, many transactional systems eschew strong semantics to achieve acceptable performance. We show that by leveraging semantic information associated with the transactional programs to increase concurrency, it is possible to significantly improve performance while maintaining linearizability. To this end, we introduce the lazy state determination API to easily expose the semantics of application transactions to the database, and propose new optimistic and pessimistic concurrency control algorithms that leverage this information to safely increase concurrency in the presence of contention. Our evaluation shows that our approach can achieve up to 5x more throughput with 1.5c less latency than standard techniques in the popular TPC-C benchmark.

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arXiv2019

Towards Enabling Novel Edge-Enabled Applications

Edge computing has emerged as a distributed computing paradigm to overcome practical scalability limits of cloud computing. The main principle of edge computing is to leverage on computational resources outside of the cloud for performing computations closer to data sources, avoiding unnecessary data transfers to the cloud and enabling faster responses for clients. While this paradigm has been successfully employed to improve response times in some contexts, mostly by having clients perform pre-processing and/or filtering of data, or by leveraging on distributed caching infrastructures, we argue that the combination of edge and cloud computing has the potential to enable novel applications. However, to do so, some significant research challenges have to be tackled by the computer science community. In this paper, we discuss different edge resources and their potential use, motivated by envisioned use cases. We then discuss concrete research challenges that are in the critical path towards realizing our edge vision. We conclude by proposing a research agenda to allow the full exploitation of the potential for the emerging hybrid cloud/edge paradigm.

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arXiv2019

Set CRDT com Múltiplas Políticas de Resolução de Conflitos

Um CRDT é um tipo de dados que pode ser replicado e modificado concorrentemente sem coordenação, garantindo-se a convergência das réplicas através da resolução automática de conflitos. Cada CRDT implementa uma política específica para resolver conflitos. Por exemplo, um conjunto CRDT add-wins dá prioridade ao "add" aquando da execução concorrente de um "add" e "rem" do mesmo elemento. Em algumas aplicações pode ser necessário usar diferentes políticas para diferentes execuções de uma operação -- por exemplo, uma aplicação que utilize um conjunto CRDT add-wins pode querer que alguns "removes" ganhem sobre "adds" concorrentes. Neste artigo é apresentado e avaliado o desenho dum conjunto CRDT que implementa as semânticas referidas. --- Conflict-Free Replicated Data Types (CRDTs) allow objects to be replicated and concurrently modified without coordination. CRDTs solve conflicts automatically and provide eventual consistency. Typically each CRDT uses a specific policy for solving conflicts. For example, in an add-wins set CRDT, when an element is concurrently add and removed in different replicas, priority is given to add, i.e., the element stays in the set. Unfortunately, this may be inadequate for some applications - it may be desired to overrule the default policy for some operation executions. For example, an application using an add-wins set may want some removes to win over concurrent adds. This paper present the design of a set CRDT that implements such semantics.

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arXiv2019

Antidote SQL: Relaxed When Possible, Strict When Necessary

Geo-replication poses an inherent trade-off between low latency, high availability and strong consistency. While NoSQL databases favor low latency and high availability, relaxing consistency, more recent cloud databases favor strong consistency and ease of programming, while still providing high scalability. In this paper, we present Antidote SQL, a database system that allows application developers to relax SQL consistency when possible. Unlike NoSQL databases, our approach enforces primary key, foreign key and check SQL constraints even under relaxed consistency, which is sufficient for guaranteeing the correctness of many applications. To this end, we defined concurrency semantics for SQL constraints under relaxed consistency and show how to implement such semantics efficiently. For applications that require strict SQL consistency, Antidote SQL provides support for such semantics at the cost of requiring coordination among replicas.

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arXiv2018

Conflict-free Replicated Data Types: An Overview

Internet-scale distributed systems often replicate data at multiple geographic locations to provide low latency and high availability, despite node and network failures. Geo-replicated systems that adopt a weak consistency model allow replicas to temporarily diverge, requiring a mechanism for merging concurrent updates into a common state. Conflict-free Replicated Data Types (CRDT) provide a principled approach to address this problem. This document presents an overview of Conflict-free Replicated Data Types research and practice, organizing the presentation in the aspects relevant for the application developer, the system developer and the CRDT developer.

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arXiv2018

Conflict-free Replicated Data Types (CRDTs)

A conflict-free replicated data type (CRDT) is an abstract data type, with a well defined interface, designed to be replicated at multiple processes and exhibiting the following properties: (1) any replica can be modified without coordinating with another replicas; (2) when any two replicas have received the same set of updates, they reach the same state, deterministically, by adopting mathematically sound rules to guarantee state convergence.

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arXiv2018

IPA: Invariant-preserving Applications for Weakly-consistent Replicated Databases

Storage systems based on Weak Consistency provide better availability and lower latency than systems that use Strong Consistency, especially in geo-replicated settings. However, under Weak Consistency, it is harder to ensure the correctness of applications, as the execution of uncoordinated operations may lead to invalid states. In this paper we show how to modify an application to make it run correctly under Weak Consistency. We developed an analysis that detects which operations need to be corrected, and proposes possible modifications to operations to prevent inconsistencies. This analysis allows the programmer to choose the preferred semantics for each problematic execution, while preserving the original semantics of operations when no conflicts occur. The modified application runs with small overhead when compared with its Weak Consistency counterpart, which cannot preserve application correctness.

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arXiv2018

Just-Right Consistency: reconciling availability and safety

By the CAP Theorem, a distributed data storage system can ensure either Consistency under Partition (CP) or Availability under Partition (AP), but not both. This has led to a split between CP databases, in which updates are synchronous, and AP databases, where they are asynchronous. However, there is no inherent reason to treat all updates identically: simply, the system should be as available as possible, and synchronised just enough for the application to be correct. We offer a principled Just-Right Consistency approach to designing such applications, reconciling correctness with availability and performance, based on the following insights:(i) The Conflict-Free Replicated Data Type (CRDTs) data model supports asynchronous updates in an intuitive and principled way.(ii) Invariants involving joint or mutually-ordered updates are compatible with AP and can be guaranteed by Transactional Causal Consistency, the strongest consistency model that does not compromise availability. Regarding the remaining, "CAP-sensitive" invariants:(iii) For the common pattern of Bounded Counters, we provide encapsulated data type that is proven correct and is efficient; (iv) in the general case, static analysis can identify when synchronisation is not necessary for correctness.Our Antidote cloud database system supports CRDTs, Transactional Causal Consistency and the Bounded Counter data type. Support tools help design applications by static analysis and proof of CAP-sensitive invariants. This system supports industrial-grade applications and has been tested experimentally with hundreds of servers across several geo-distributed data centres.

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arXiv2017

Time-Aware Publish/Subscribe for Networks of Mobile Devices

Smart mobile devices are increasingly ubiquitous and are the primary source of user-generated content, and current communication infrastructures are failing in keeping up with the rising demand for the avid sharing of such content. To alleviate this problem and fully harness the amount of resources currently available at the network edge, mobile edge paradigms started to emerge. Though, application developers still struggle to tap that potential at the edge due to the lack of adequate communication and interaction abstractions. Thus, we propose a high-level abstraction that can be easily exploited by developers to design mobile edge applications focused on data dissemination. In this paper, we propose Thyme, a novel extended topic-based, time-aware publish/subscribe system for networks of mobile devices. In Thyme, time is a rst order dimension. Each subscription has an associated time frame, starting and ending either in the future, present, or past. Making the past available requires both subscriptions and publications to be persistently stored. We present the design of Thyme and evaluate it using simulation, discussing and characterizing the scenarios best suited for its use.

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arXiv2017

Non-uniform Replication

Replication is a key technique in the design of efficient and reliable distributed systems. As information grows, it becomes difficult or even impossible to store all information at every replica. A common approach to deal with this problem is to rely on partial replication, where each replica maintains only a part of the total system information. As a consequence, a remote replica might need to be contacted for computing the reply to some given query, which leads to high latency costs particularly in geo-replicated settings. In this work, we introduce the concept of non-uniform replication, where each replica stores only part of the information, but where all replicas store enough information to answer every query. We apply this concept to eventual consistency and conflict-free replicated data types. We show that this model can address useful problems and present two data types that solve such problems. Our evaluation shows that non-uniform replication is more efficient than traditional replication, using less storage space and network bandwidth.

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arXiv2015

Eventually Consistent Register Revisited

In order to converge in the presence of concurrent updates, modern eventually consistent replication systems rely on causality information and operation semantics. It is relatively easy to use semantics of high-level operations on replicated data structures, such as sets, lists, etc. However, it is difficult to exploit semantics of operations on registers, which store opaque data. In existing register designs, concurrent writes are resolved either by the application, or by arbitrating them according to their timestamps. The former is complex and may require user intervention, whereas the latter causes arbitrary updates to be lost. In this work, we identify a register construction that generalizes existing ones by combining runtime causality ordering, to identify concurrent writes, with static data semantics, to resolve them. We propose a simple conflict resolution template based on an application-predefined order on the domain of values. It eliminates or reduces the number of conflicts that need to be resolved by the user or by an explicit application logic. We illustrate some variants of our approach with use cases, and how it generalizes existing designs.

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arXiv2015

Extending Eventually Consistent Cloud Databases for Enforcing Numeric Invariants

Geo-replicated databases often operate under the principle of eventual consistency to offer high-availability with low latency on a simple key/value store abstraction. Recently, some have adopted commutative data types to provide seamless reconciliation for special purpose data types, such as counters. Despite this, the inability to enforce numeric invariants across all replicas still remains a key shortcoming of relying on the limited guarantees of eventual consistency storage. We present a new replicated data type, called bounded counter, which adds support for numeric invariants to eventually consistent geo-replicated databases. We describe how this can be implemented on top of existing cloud stores without modifying them, using Riak as an example. Our approach adapts ideas from escrow transactions to devise a solution that is decentralized, fault-tolerant and fast. Our evaluation shows much lower latency and better scalability than the traditional approach of using strong consistency to enforce numeric invariants, thus alleviating the tension between consistency and availability.

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arXiv2013

SwiftCloud: Fault-Tolerant Geo-Replication Integrated all the Way to the Client Machine

Client-side logic and storage are increasingly used in web and mobile applications to improve response time and availability. Current approaches tend to be ad-hoc and poorly integrated with the server-side logic. We present a principled approach to integrate client- and server-side storage. We support mergeable and strongly consistent transactions that target either client or server replicas and provide access to causally-consistent snapshots efficiently. In the presence of infrastructure faults, a client-assisted failover solution allows client execution to resume immediately and seamlessly access consistent snapshots without waiting. We implement this approach in SwiftCloud, the first transactional system to bring geo-replication all the way to the client machine. Example applications show that our programming model is useful across a range of application areas. Our experimental evaluation shows that SwiftCloud provides better fault tolerance and at the same time can improve both latency and throughput by up to an order of magnitude, compared to classical geo-replication techniques.

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arXiv2013

Non-Monotonic Snapshot Isolation

Many distributed applications require transactions. However, transactional protocols that require strong synchronization are costly in large scale environments. Two properties help with scalability of a transactional system: genuine partial replication (GPR), which leverages the intrinsic parallelism of a workload, and snapshot isolation (SI), which decreases the need for synchronization. We show that, under standard assumptions (data store accesses are not known in advance, and transactions may access arbitrary objects in the data store), it is impossible to have both SI and GPR. To circumvent this impossibility, we propose a weaker consistency criterion, called Non-monotonic Snapshot Isolation (NMSI). NMSI retains the most important properties of SI, i.e., read-only transactions always commit, and two write-conflicting updates do not both commit. We present a GPR protocol that ensures NMSI, and has lower message cost (i.e., it contacts fewer replicas and/or commits faster) than previous approaches.

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arXiv2012

An optimized conflict-free replicated set

Eventual consistency of replicated data supports concurrent updates, reduces latency and improves fault tolerance, but forgoes strong consistency. Accordingly, several cloud computing platforms implement eventually-consistent data types. The set is a widespread and useful abstraction, and many replicated set designs have been proposed. We present a reasoning abstraction, permutation equivalence, that systematizes the characterization of the expected concurrency semantics of concurrent types. Under this framework we present one of the existing conflict-free replicated data types, Observed-Remove Set. Furthermore, in order to decrease the size of meta-data, we propose a new optimization to avoid tombstones. This approach that can be transposed to other data types, such as maps, graphs or sequences.

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arXiv2010

Dotted Version Vectors: Logical Clocks for Optimistic Replication

In cloud computing environments, a large number of users access data stored in highly available storage systems. To provide good performance to geographically disperse users and allow operation even in the presence of failures or network partitions, these systems often rely on optimistic replication solutions that guarantee only eventual consistency. In this scenario, it is important to be able to accurately and efficiently identify updates executed concurrently. In this paper, first we review, and expose problems with current approaches to causality tracking in optimistic replication: these either lose information about causality or do not scale, as they require replicas to maintain information that grows linearly with the number of clients or updates. Then, we propose a novel solution that fully captures causality while being very concise in that it maintains information that grows linearly only with the number of servers that register updates for a given data element, bounded by the degree of replication.

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