Computing in the RAIN: a reliable array of independent nodes

The RAIN project is a research collaboration between Caltech and NASA-JPL on distributed computing and data-storage systems for future spaceborne missions. The goal of the project is to identify and develop key building blocks for reliable distributed systems built with inexpensive off-the-shelf components. The RAIN platform consists of a heterogeneous cluster of computing and/or storage nodes connected via multiple interfaces to networks configured in fault-tolerant topologies. The RAIN software components run in conjunction with operating system services and standard network protocols. Through software-implemented fault tolerance, the system tolerates multiple node, link, and switch failures, with no single point of failure. The RAIN-technology has been transferred to Rainfinity, a start-up company focusing on creating clustered solutions for improving the performance and availability of Internet data centers. In this paper, we describe the following contributions: 1) fault-tolerant interconnect topologies and communication protocols providing consistent error reporting of link failures, 2) fault management techniques based on group membership, and 3) data storage schemes based on computationally efficient error-control codes. We present several proof-of-concept applications: a highly-available video server, a highly-available Web server, and a distributed checkpointing system. Also, we describe a commercial product, Rainwall, built with the RAIN technology

Dependable Distributed Computing for the International Telecommunication Union Regional Radio Conference RRC06

The International Telecommunication Union (ITU) Regional Radio Conference (RRC06) established in 2006 a new frequency plan for the introduction of digital broadcasting in European, African, Arab, CIS countries and Iran. The preparation of the plan involved complex calculations under short deadline and required dependable and efficient computing capability. The ITU designed and deployed in-situ a dedicated PC farm, in parallel to the European Organization for Nuclear Research (CERN) which provided and supported a system based on the EGEE Grid. The planning cycle at the RRC06 required a periodic execution in the order of 200,000 short jobs, using several hundreds of CPU hours, in a period of less than 12 hours. The nature of the problem required dynamic workload-balancing and low-latency access to the computing resources. We present the strategy and key technical choices that delivered a reliable service to the RRC06

Distributed evolutionary algorithms and their models: A survey of the state-of-the-art

The increasing complexity of real-world optimization problems raises new challenges to evolutionary computation. Responding to these challenges, distributed evolutionary computation has received considerable attention over the past decade. This article provides a comprehensive survey of the state-of-the-art distributed evolutionary algorithms and models, which have been classified into two groups according to their task division mechanism. Population-distributed models are presented with master-slave, island, cellular, hierarchical, and pool architectures, which parallelize an evolution task at population, individual, or operation levels. Dimension-distributed models include coevolution and multi-agent models, which focus on dimension reduction. Insights into the models, such as synchronization, homogeneity, communication, topology, speedup, advantages and disadvantages are also presented and discussed. The study of these models helps guide future development of different and/or improved algorithms. Also highlighted are recent hotspots in this area, including the cloud and MapReduce-based implementations, GPU and CUDA-based implementations, distributed evolutionary multiobjective optimization, and real-world applications. Further, a number of future research directions have been discussed, with a conclusion that the development of distributed evolutionary computation will continue to flourish

A consistent and fault-tolerant data store for software defined networks

Tese de mestrado em Segurança Informática, apresentada à Universidade de Lisboa, através da Faculdade de Ciências, 2013O sucesso da Internet é indiscutível. No entanto, desde há muito tempo que são feitas sérias críticas à sua arquitectura. Investigadores acreditam que o principal problema dessa arquitectura reside no facto de os dispositivos de rede incorporarem funções distintas e complexas que vão além do objectivo de encaminhar pacotes, para o qual foram criados [1]. O melhor exemplo disso são os protocolos distribuídos (e complexos) de encaminhamento, que os routers executam de forma a conseguir garantir o encaminhamento de pacotes. Algumas das consequências disso são a complexidade das redes tradicionais tanto em termos de inovação como de manutenção. Como resultado, temos redes dispendiosas e pouco resilientes. De forma a resolver este problema uma arquitectura de rede diferente tem vindo a ser adoptada, tanto pela comunidade científica como pela indústria. Nestas novas redes, conhecidas como Software Defined Networks (SDN), há uma separação física entre o plano de controlo do plano de dados. Isto é, toda a lógica e estado de controlo da rede é retirada dos dispositivos de rede, para passar a ser executada num controlador logicamente centralizado que com uma visão global, lógica e coerente da rede, consegue controlar a mesma de forma dinâmica. Com esta delegação de funções para o controlador os dispositivos de rede podem dedicar-se exclusivamente à sua função essencial de encaminhar pacotes de dados. Assim sendo, os dipositivos de redes permanecem simples e mais baratos, e o controlador pode implementar funções de controlo simplificadas (e possivelmente mais eficazes) graças à visão global da rede. No entanto um modelo de programação logicamente centralizado não implica um sistema centralizado. De facto, a necessidade de garantir níveis adequados de performance, escalabilidade e resiliência, proíbem que o plano de controlo seja centralizado. Em vez disso, as redes de SDN que operam a nível de produção utilizam planos de controlo distribuídos e os arquitectos destes sistemas têm que enfrentar os trade-offs fundamentais associados a sistemas distribuídos. Nomeadamente o equilíbrio adequado entre coerência e disponibilidade do sistema. Neste trabalho nós propomos uma arquitectura de um controlador distribuído, tolerante a faltas e coerente. O elemento central desta arquitectura é uma base de dados replicada e tolerante a faltas que mantém o estado da rede coerente, de forma a garantir que as aplicações de controlo da rede, que residem no controlador, possam operar com base numa visão coerente da rede que garanta coordenação, e consequentemente simplifique o desenvolvimento das aplicações. A desvantagem desta abordagem reflecte-se no decréscimo de performance, que limita a capacidade de resposta do controlador, e também a escalabilidade do mesmo. Mesmo assumindo estas consequências, uma conclusão importante do nosso estudo é que é possível atingir os objectivos propostos (i.e., coerência forte e tolerância a faltas) e manter a performance a um nível aceitável para determinados tipo de redes. Relativamente à tolerância a faltas, numa arquitectura SDN estas podem ocorrer em três domínios diferentes: o plano de dados (falhas do equipamento de rede), o plano de controlo (falhas da ligação entre o controlador e o equipamento de rede) e, finalmente, o próprio controlador. Este último é de uma importância particular, sendo que a falha do mesmo pode perturbar a rede por inteiro (i.e., deixando de existir conectividade entre os hosts). É portanto essencial que as redes de SDN que operam a nível de produção possuam mecanismos que possam lidar com os vários tipos de faltas e garantir disponibilidade perto de 100%. O trabalho recente em SDN têm explorado a questão da coerência a níveis diferentes. Linguagens de programação como a Frenetic [2] oferecem coerência na composição de políticas de rede, conseguindo resolver incoerências nas regras de encaminhamento automaticamente. Outra linha de trabalho relacionado propõe abstracções que garantem a coerência da rede durante a alteração das tabelas de encaminhamento do equipamento. O objectivo destes dois trabalhos é garantir a coerência depois de decidida a política de encaminhamento. O Onix (um controlador de SDN muitas vezes referenciado [3]) garante um tipo de coerência diferente: uma que é importante antes da política de encaminhamento ser tomada. Este controlador oferece dois tipos de coerência na salvaguarda do estado da rede: coerência eventual, e coerência forte. O nosso trabalho utiliza apenas coerência forte, e consegue demonstrar que esta pode ser garantida com uma performance superior à garantida pelo Onix. Actualmente, os controladores de SDN distribuídos (Onix e HyperFlow [4]) utilizam modelos de distribuição não transparentes, com propriedades fracas como coerência eventual que exigem maior cuidado no desenvolvimento de aplicações de controlo de rede no controlador. Isto deve-se à ideia (do nosso ponto de vista infundada) de que propriedades como coerência forte limitam significativamente a escalabilidade do controlador. No entanto um controlador com coerência forte traduz-se num modelo de programação mais simples e transparente à distribuição do controlador. Neste trabalho nós argumentámos que é possível utilizar técnicas bem conhecidas de replicação baseadas na máquina de estados distribuída [5], para construir um controlador SDN, que não só garante tolerância a faltas e coerência forte, mas também o faz com uma performance aceitável. Neste sentido a principal contribuição desta dissertação é mostrar que uma base de dados construída com as técnicas mencionadas anteriormente (como as providenciadas pelo BFT-SMaRt [6]), e integrada com um controlador open-source existente (como o Floodlight1), consegue lidar com vários tipos de carga, provenientes de aplicações de controlo de rede, eficientemente. As contribuições principais do nosso trabalho, podem ser resumidas em: 1. A proposta de uma arquitectura de um controlador distribuído baseado nas propriedades de coerência forte e tolerância a faltas; 2. Como a arquitectura proposta é baseada numa base de dados replicada, nós realizamos um estudo da carga produzida por três aplicações na base dados. 3. Para avaliar a viabilidade da nossa arquitectura nós analisamos a capacidade do middleware de replicação para processar a carga mencionada no ponto anterior. Este estudo descobre as seguintes variáveis: (a) Quantos eventos por segundo consegue o middleware processar por segundo; (b) Qual o impacto de tempo (i.e., latência) necessário para processar tais eventos; para cada uma das aplicações mencionadas, e para cada um dos possíveis eventos de rede processados por essas aplicações. Estas duas variáveis são importantes para entender a escalabilidade e performance da arquitectura proposta. Do nosso trabalho, nomeadamente do nosso estudo da carga das aplicações (numa primeira versão da nossa integração com a base de dados) e da capacidade do middleware resultou uma publicação: Fábio Botelho, Fernando Ramos, Diego Kreutz and Alysson Bessani; On the feasibility of a consistent and fault-tolerant data store for SDNs, in Second European Workshop on Software Defined Networks, Berlin, October 2013. Entretanto, nós submetemos esta dissertação cerca de cinco meses depois desse artigo, e portanto, contém um estudo muito mais apurado e melhorado.Even if traditional data networks are very successful, they exhibit considerable complexity manifested in the configuration of network devices, and development of network protocols. Researchers argue that this complexity derives from the fact that network devices are responsible for both processing control functions such as distributed routing protocols and forwarding packets. This work is motivated by the emergent network architecture of Software Defined Networks where the control functionality is removed from the network devices and delegated to a server (usually called controller) that is responsible for dynamically configuring the network devices present in the infrastructure. The controller has the advantage of logically centralizing the network state in contrast to the previous model where state was distributed across the network devices. Despite of this logical centralization, the control plane (where the controller operates) must be distributed in order to avoid being a single point of failure. However, this distribution introduces several challenges due to the heterogeneous, asynchronous, and faulty environment where the controller operates. Current distributed controllers lack transparency due to the eventual consistency properties employed in the distribution of the controller. This results in a complex programming model for the development of network control applications. This work proposes a fault-tolerant distributed controller with strong consistency properties that allows a transparent distribution of the control plane. The drawback of this approach is the increase in overhead and delay, which limits responsiveness and scalability. However, despite being fault-tolerant and strongly consistent, we show that this controller is able to provide performance results (in some cases) superior to those available in the literature

Supporting Quality of Service in Scientific Workflows

While workflow management systems have been utilized in enterprises to support businesses for almost two decades, the use of workflows in scientific environments was fairly uncommon until recently. Nowadays, scientists use workflow systems to conduct scientific experiments, simulations, and distributed computations. However, most scientific workflow management systems have not been built using existing workflow technology; rather they have been designed and developed from scratch. Due to the lack of generality of early scientific workflow systems, many domain-specific workflow systems have been developed. Generally speaking, those domain-specific approaches lack common acceptance and tool support and offer lower robustness compared to business workflow systems. In this thesis, the use of the industry standard BPEL, a workflow language for modeling business processes, is proposed for the modeling and the execution of scientific workflows. Due to the widespread use of BPEL in enterprises, a number of stable and mature software products exist. The language is expressive (Turingcomplete) and not restricted to specific applications. BPEL is well suited for the modeling of scientific workflows, but existing implementations of the standard lack important features that are necessary for the execution of scientific workflows. This work presents components that extend an existing implementation of the BPEL standard and eliminate the identified weaknesses. The components thus provide the technical basis for use of BPEL in academia. The particular focus is on so-called non-functional (Quality of Service) requirements. These requirements include scalability, reliability (fault tolerance), data security, and cost (of executing a workflow). From a technical perspective, the workflow system must be able to interface with the middleware systems that are commonly used by the scientific workflow community to allow access to heterogeneous, distributed resources (especially Grid and Cloud resources). The major components cover exactly these requirements: Cloud Resource Provisioner Scalability of the workflow system is achieved by automatically adding additional (Cloud) resources to the workflow system’s resource pool when the workflow system is heavily loaded. Fault Tolerance Module High reliability is achieved via continuous monitoring of workflow execution and corrective interventions, such as re-execution of a failed workflow step or replacement of the faulty resource. Cost Aware Data Flow Aware Scheduler The majority of scientific workflow systems only take the performance and utilization of resources for the execution of workflow steps into account when making scheduling decisions. The presented workflow system goes beyond that. By defining preference values for the weighting of costs and the anticipated workflow execution time, workflow users may influence the resource selection process. The developed multiobjective scheduling algorithm respects the defined weighting and makes both efficient and advantageous decisions using a heuristic approach. Security Extensions Because it supports various encryption, signature and authentication mechanisms (e.g., Grid Security Infrastructure), the workflow system guarantees data security in the transfer of workflow data. Furthermore, this work identifies the need to equip workflow developers with workflow modeling tools that can be used intuitively. This dissertation presents two modeling tools that support users with different needs. The first tool, DAVO (domain-adaptable, Visual BPEL Orchestrator), operates at a low level of abstraction and allows users with knowledge of BPEL to use the full extent of the language. DAVO is a software that offers extensibility and customizability for different application domains. These features are used in the implementation of the second tool, SimpleBPEL Composer. SimpleBPEL is aimed at users with little or no background in computer science and allows for quick and intuitive development of BPEL workflows based on predefined components

Storage Solutions for Big Data Systems: A Qualitative Study and Comparison

Big data systems development is full of challenges in view of the variety of application areas and domains that this technology promises to serve. Typically, fundamental design decisions involved in big data systems design include choosing appropriate storage and computing infrastructures. In this age of heterogeneous systems that integrate different technologies for optimized solution to a specific real world problem, big data system are not an exception to any such rule. As far as the storage aspect of any big data system is concerned, the primary facet in this regard is a storage infrastructure and NoSQL seems to be the right technology that fulfills its requirements. However, every big data application has variable data characteristics and thus, the corresponding data fits into a different data model. This paper presents feature and use case analysis and comparison of the four main data models namely document oriented, key value, graph and wide column. Moreover, a feature analysis of 80 NoSQL solutions has been provided, elaborating on the criteria and points that a developer must consider while making a possible choice. Typically, big data storage needs to communicate with the execution engine and other processing and visualization technologies to create a comprehensive solution. This brings forth second facet of big data storage, big data file formats, into picture. The second half of the research paper compares the advantages, shortcomings and possible use cases of available big data file formats for Hadoop, which is the foundation for most big data computing technologies. Decentralized storage and blockchain are seen as the next generation of big data storage and its challenges and future prospects have also been discussed

A taxonomy of task-based parallel programming technologies for high-performance computing

Task-based programming models for shared memory -- such as Cilk Plus and OpenMP 3 -- are well established and documented. However, with the increase in parallel, many-core and heterogeneous systems, a number of research-driven projects have developed more diversified task-based support, employing various programming and runtime features. Unfortunately, despite the fact that dozens of different task-based systems exist today and are actively used for parallel and high-performance computing (HPC), no comprehensive overview or classification of task-based technologies for HPC exists. In this paper, we provide an initial task-focused taxonomy for HPC technologies, which covers both programming interfaces and runtime mechanisms. We demonstrate the usefulness of our taxonomy by classifying state-of-the-art task-based environments in use today