Almeida PS, Moreno CB, Farach-Colton M, Jesus P, Mosteiro M.  2011.  Fault-Tolerant Aggregation: Flow-Updating Meets Mass-Distribution. Principles of Distributed Systems. 7109:513–527. Abstract1109.4373v1.pdf

Flow-Updating (FU) is a fault-tolerant technique that has proved to be efficient in practice for the distributed computation of aggregate functions in communication networks where individual processors do not have access to global information. Previous distributed aggregation protocols, based on repeated sharing of input values (or mass) among processors, sometimes called Mass-Distribution (MD) protocols, are not resilient to communication failures (or message loss) because such failures yield a loss of mass.

In this paper, we present a protocol which we call Mass-Distribution with Flow-Updating (MDFU). We obtain MDFU by applying FU techniques to classic MD. We analyze the convergence time of MDFU showing that stochastic message loss produces low overhead. This is the first convergence proof of an FU-based algorithm. We evaluate MDFU experimentally, comparing it with previous MD and FU protocols, and verifying the behavior predicted by the analysis. Finally, given that MDFU incurs a fixed deviation proportional to the message-loss rate, we adjust the accuracy of MDFU heuristically in a new protocol called MDFU with Linear Prediction (MDFU-LP). The evaluation shows that both MDFU and MDFU-LP behave very well in practice, even under high rates of message loss and even changing the input values dynamically.

Gonçalves R, Almeida PS, Moreno CB, Fonte V, Preguiça N.  2011.  Evaluating Dotted Version Vectors in Riak. INForum - Simpósio de Informática. :474–479. Abstractmain.pdf

The NoSQL movement is rapidly increasing in importance, acceptance and usage in major (web) applications, that need the partition-tolerance and availability of the CAP theorem for scalability purposes, thus sacrificing the consistency side. With this approach, paradigms such as Eventual Consistency became more widespread. An eventual consistent system must handle data divergence and conflicts, that have to be carefully accounted for. Some systems have tried to use classic Version Vectors (VV) to track causality, but these reveal either scalability problems or loss of accuracy (when pruning is used to prevent vector growth).

Dotted Version Vectors (DVV) is a novel mechanism for dealing with data versioning in eventual consistent systems, that allows both accurate causality tracking and scalability both in the number of clients and servers, while limiting vector size to replication degree.

In this paper we describe briefly the challenges faced when incorporating DVV in Riak (a distributed key-value store), evaluate its behavior and performance, and discuss the advantages and disadvantages of this specific implementation.

Borges M, Moreno CB, Jesus P, Almeida PS.  2011.  Estimativa Contínua e Tolerante a Faltas de Funções Distribuição Cumulativa em Redes de Larga Escala. INForum - Simpósio de Informática. Abstractsimposio_de_informatica_inforum_2011_borges.pdf

Em ambientes descentralizados de larga escala como é o caso das redes de sensores sem fios, P2P e outras, a recolha de dados é praticável apenas se houver agregação dos mesmos. No estado da arte actual, as estratégias de resolução desta questão não são satisfatórias dado exigirem que os protocolos sejam reiniciados sempre que os valores iniciais mudam ou quando o rácio de entrada/saída de nodos é não nulo. Acresce que nenhuma estratégia satisfaz a estimativa de CDFs (funções de dis- tribuição cumulativa). A abordagem apresentada neste trabalho mostra como é possível o cálculo de funções de distribuição cumulativa em redes distribuídas, permitindo o seguimento dinâmico dos valores amostrados, sem que seja necessário reiniciar o protocolo em condições adversas de funcionamento da rede (perda de mensagens, entrada/saída de nodos). Esta abordagem é baseada num protocolo de averaging tolerante a faltas. Com este trabalho pretende-se também contribuir com uma estratégia que reduz o custo de comunicação entre nodos, com base em decisões locais e sensível à taxa de variação de estimativas. Os resultados de simulação mostram a resiliência deste protocolo, permitindo a estimativa contínua de CDFs em presença de dinamismo (perda de mensagens, alteração de valor amostrado, churn). Mostram também a convergência rápida na estimativa de CDFs para diferentes configurações de rede.

Jesus P, Moreno CB, Almeida PS.  2010.  Fault-Tolerant Aggregation for Dynamic Networks. 29th Symposium on Reliable Distributed Systems (SRDS). :37–43. Abstractfu_dynamic_agg.pdf

Data aggregation is a fundamental building block of modern distributed systems. Averaging based approaches, commonly designated gossip-based, are an important class of aggregation algorithms as they allow all nodes to produce a result, converge to any required accuracy, and work independently from the network topology. However, existing approaches exhibit many dependability issues when used in faulty and dynamic environments. This paper extends our own technique, Flow Updating, which is immune to message loss, to operate in dynamic networks, improving its fault tolerance characteristics. Experimental results show that the novel version of Flow Updating vastly outperforms previous averaging algorithms, it self adapts to churn without requiring any periodic restart, supporting node crashes and high levels of message loss.

Moreno CB, Almeida PS, Menezes R.  2009.  Fast estimation of aggregates in unstructured networks. Fifth International Conference on Autonomic and Autonomous Systems - ICAS. :88–93. Abstractieeefastfinalicas2009.pdf

Aggregation of data values plays an important role on distributed computations, in particular over peer-to-peer and sensor networks, as it can provide a summary of some global system property and direct the actions of self-adaptive distributed algorithms. Examples include using estimates of the network size to dimension distributed hash tables or estimates of the average system load to direct loadbalancing. Distributed aggregation using non-idempotent functions, like sums, is not trivial as it is not easy to prevent a given value from being accounted for multiple times; this is especially the case if no centralized algorithms or global identifiers can be used.This paper introduces Extrema Propagation, a probabilistic technique for distributed estimation of the sum of positive real numbers. The technique relies on the exchange of duplicate insensitive messages and can be applied in flood and/or epidemic settings, where multi-path routing occurs; it is tolerant of message loss; it is fast, as the number of message exchange steps equals the diameter; and it is fully distributed, with no single point of failure and the result produced at every node.

Jesus P, Moreno CB, Almeida PS.  2009.  Fault-Tolerant Aggregation by Flow Updating. Distributed Applications and Interoperable Systems. 5523:73–86. Abstractflow_updating.pdf

Data aggregation plays an important role in the design of scalable systems, allowing the determination of meaningful system-wide properties to direct the execution of distributed applications. In the particular case of wireless sensor networks, data collection is often only practicable if aggregation is performed. Several aggregation algorithms have been proposed in the last few years, exhibiting different properties in terms of accuracy, speed and communication tradeoffs. Nonetheless, existing approaches are found lacking in terms of fault tolerance. In this paper, we introduce a novel fault-tolerant averaging based data aggregation algorithm. It tolerates substantial message loss (link failures), while competing algorithms in the same class can be affected by a single lost message. The algorithm is based on manipulating flows (in the graph theoretical sense), that are updated using idempotent messages, providing it with unique robustness capabilities. Furthermore, evaluation results obtained by comparing it with other averaging approaches have revealed that it outperforms them in terms of time and message complexity.

Moreno CB, Almeida PS, Cardoso J.  2009.  Probabilistic estimation of network size and diameter. Fourth Latin-American Symposium on Dependable Computing - LADC. :33–40. Abstractartigoladcfinal.pdf

Determining the size of a network and its diameter are important functions in distributed systems, as there are a number of algorithms which rely on such parameters, or at least on estimates of those values. The Extrema Propagation technique allows the estimation of the size of a network in a fast, distributed and fault tolerant manner. The technique was previously studied in a simulation setting where rounds advance synchronously and where there is no message loss.This work presents two main contributions. The first, is the study of the Extrema Propagation technique under asynchronous rounds and integrated in the Network Friendly Epidemic Multicast (NeEM) framework. The second, is the evaluation of a diameter estimation technique associated with the Extrema Propagation. This study also presents a small enhancement the Extrema Propagation in terms of communication cost and points out some other possible enhancements. Results show that there is a clear trade-off between time and communication that must be considered when configuring the protocol—a faster convergence time implies a higher communication cost. Results also show that its possible to reduce the total communication cost by more than 18% using a simple approach. The diameter estimation technique is shown to have a relative error of less than10% even when using a small sample of nodes.

Jesus P, Moreno CB, Almeida PS.  2009.  Using Less Links to Improve Fault-Tolerant Aggregation. 4th Latin-American Symposium on Dependable Computing - LADC. Abstractfast_abstract

Data aggregation plays a basal role in the design of scalable distributed applications, allowing the determination of meaningful system-wide properties to direct the execution of the system. For instance, aggregation can be used to estimate: the size of the network to dimension of Distributed Hash Table (DHT) structures, or to set a quorum in dynamic settings; the average system load to guide local loadbalancing decisions; the total network disk space in a P2P sharing system. In the particular case of Wireless Sensor Networks (WSN), due to energy constraints, data collection is often only practicable if aggregation is performed.

Jesus P, Moreno CB, Almeida PS.  2009.  Dependability in Aggregation by Averaging. INForum - Simpósio de Informática. :457–470. Abstractsimposio_de_informatica_inforum_2009_jesus.pdf

Aggregation is an important building block of modern distributed applications, allowing the determination of meaningful properties (e.g. network size, total storage capacity, average load, majorities, etc.) that are used to direct the execution of the system. In the recent years, several approaches have been proposed to compute aggregation functions on distributed settings, exhibiting different characteristics, in terms of accuracy, time and communication complexity. However, the majority of the existing aggregation algorithms exhibit relevant dependability issues, when prospecting their use in real application environments. In this paper, we reveal some dependability issues of aggregation algorithms based on iterative averaging techniques, giving some directions to solve them. This class of algorithms is considered robust (when compared to common tree-based approaches), being independent from the used routing topology and providing an aggregation result at all nodes. However, their robustness is strongly challenged and their correctness often compromised, when changing the assumptions of their working environment to more realistic ones. The correctness of this class of algorithms relies on the maintenance of a fundamental invariant, commonly designated as mass conservation. We will argue that this main invariant is often broken in practical settings, and that additional mechanisms and modifications are required to maintain it, incurring in some degradation of the algorithms performance. In particular, we discuss the behavior of three representative algorithms (Push-Sum Protocol [1], Push- Pull Gossip protocol [2] and Distributed Random Grouping [3]) under asynchronous and faulty (with message loss and node crashes) environments. More specifically, we propose and evaluate two new versions of the Push-Pull Gossip protocol, which solve its message interleaving problem (evidenced even in a synchronous operation mode).

Almeida PS, Moreno CB, Fonte V.  2008.  Interval tree clocks. 12th International Conference on Principles of Distributed Systems - OPODIS. 5401 Abstractitc.pdf

Causality tracking mechanisms, such as vector clocks and version vectors, rely on mappings from globally unique identifiers to integer counters. In a system with a well known set of entities these ids can be preconfigured and given distinct positions in a vector or distinct names in a mapping. Id management is more problematic in dynamic systems, with large and highly variable number of entities, being worsened when network partitions occur. Present solutions for causality tracking are not appropriate to these increasingly common scenarios. In this paper we introduce Interval Tree Clocks, a novel causality tracking mechanism that can be used in scenarios with a dynamic number of entities, allowing a completely decentralized creation of processes/replicas without need for global identifiers or global coordination. The mechanism has a variable size representation that adapts automatically to the number of existing entities, growing or shrinking appropriately. The representation is so compact that the mechanism can even be considered for scenarios with a fixed number of entities, which makes it a general substitute for vector clocks and version vectors.

Almeida PS, Pinto JS, Vilaça M.  2007.  A Tool for Programming with Interaction Nets. Proceedings of RULE . Abstract07tpin.pdf

This paper introduces INblobs, a visual tool developed at Minho for integrated development with Interaction Nets. Most of the existing tools take as input interaction nets and interaction rules represented in a textual format. INblobs is first of all a visual editor that allows users to edit interaction systems (both interaction nets and interaction rules) graphically, and to convert them to textual notation. This can then be used as input to other tools that implement reduction of nets. INblobs also allows the user to reduce nets within the tool, and includes a mechanism that automatically selects the next active pair to be reduced, following one of the given reduction strategies. The paper also describes other features of the tool, such as the creation of rules from pre-defined templates.

Jesus P, Moreno CB, Almeida PS.  2006.  ID Generation in Mobile Environments. Conference on Mobile and Ubiquitous Systems (CSMU). Abstractjesus-148.pdf

This work is focused in the ID generation problem in mobile environments. We discuss the suitability of traditional mechanisms and techniques to generate IDs in mobile environments. Based on the “Birthday Problem”, we deduced some formulas to evaluate the ID trust that is directly related to the number of entities in the system. The estimation of the system size revels to be the main problem of our approach. To deal with it, we develop a recursive schema that needs to be evaluated. Alternatively, we also design an aggregation algorithm to estimate the system size, which results are currently been analyzed.

Preguiça N, Moreno CB, Martins JL, Shapiro M, Almeida PS, Domingos H, Fonte V, Duarte S, others.  2005.  Few: File management for portable devices. International Workshop on Software Support for Portable Storage (IWSSPS). Abstractfew-iwssps2005-final2.pdf

In recent years, an increasing number of portable devices with large amounts of storage have become widely used. In this paper, we present the early design of the FEW system, a system that aims to ease file management in the new mobile environment. To this end, the system will manage file replicas stored in fixed and portable storage devices. It will provide an automatic mechanism to establish new file replicas by analyzing file system activity. The system will automatically and incrementally synchronize all file replicas exploring the available network connectivity and the availability of portable storage devices. To merge concurrent updates, operational transformation techniques will be used.

Almeida JB, Almeida PS, Moreno CB.  2004.  Bounded Version Vectors. International Conference on Distributed Computing - ICDCS. 3274:102-116. Abstract04bvv.pdf

Version vectors play a central role in update tracking under optimistic distributed systems, allowing the detection of obsolete or inconsistent versions of replicated data. Version vectors do not have a bounded representation; they are based on integer counters that grow indefinitely as updates occur. Existing approaches to this problem are scarce; the mechanisms proposed are either unbounded or operate only under specific settings. This paper examines version vectors as a mechanism for data causality tracking and clarifies their role with respect to vector clocks. Then, it introduces bounded stamps and proves them to be a correct alternative to integer counters in version vectors. The resulting mechanism, bounded version vectors, represents the first bounded solution to data causality tracking between replicas subject to local updates and pairwise symmetrical synchronization.

Almeida PS, Moreno CB, Fonte V.  2002.  Version stamps-decentralized version vectors. Proceedings 22nd International Conference on Distributed Computing Systems - ICDCS. :544–551. Abstract10.

Version vectors and their variants play a central role in update tracking in optimistic distributed systems. Existing mechanisms for a variable number of participants use a mapping from identities to integers, and rely on some form of global configuration or distributed naming protocol to assign unique identifiers to each participant. These approaches are incompatible with replica creation under arbitrary partitions, a typical mode of operation in mobile or poorly connected environments. We present an update tracking mechanism that overcomes this limitation; it departs from the traditional mapping and avoids the use of integer counters, while providing all the functionality of version vectors in what concerns version tracking.