135,193 research outputs found

    Building global and scalable systems with atomic multicast

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    The rise of worldwide Internet-scale services demands large distributed systems. Indeed, when handling several millions of users, it is common to operate thousands of servers spread across the globe. Here, replication plays a central role, as it contributes to improve the user experience by hiding failures and by providing acceptable latency. In this thesis, we claim that atomic multicast, with strong and well-defined properties, is the appropriate abstraction to efficiently design and implement globally scalable distributed systems. Internet-scale services rely on data partitioning and replication to provide scalable performance and high availability. Moreover, to reduce user-perceived response times and tolerate disasters (i.e., the failure of a whole datacenter), services are increasingly becoming geographically distributed. Data partitioning and replication, combined with local and geographical distribution, introduce daunting challenges, including the need to carefully order requests among replicas and partitions. One way to tackle this problem is to use group communication primitives that encapsulate order requirements. While replication is a common technique used to design such reliable distributed systems, to cope with the requirements of modern cloud based ``always-on'' applications, replication protocols must additionally allow for throughput scalability and dynamic reconfiguration, that is, on-demand replacement or provisioning of system resources. We propose a dynamic atomic multicast protocol which fulfills these requirements. It allows to dynamically add and remove resources to an online replicated state machine and to recover crashed processes. Major efforts have been spent in recent years to improve the performance, scalability and reliability of distributed systems. In order to hide the complexity of designing distributed applications, many proposals provide efficient high-level communication abstractions. Since the implementation of a production-ready system based on this abstraction is still a major task, we further propose to expose our protocol to developers in the form of distributed data structures. B-trees for example, are commonly used in different kinds of applications, including database indexes or file systems. Providing a distributed, fault-tolerant and scalable data structure would help developers to integrate their applications in a distribution transparent manner. This work describes how to build reliable and scalable distributed systems based on atomic multicast and demonstrates their capabilities by an implementation of a distributed ordered map that supports dynamic re-partitioning and fast recovery. To substantiate our claim, we ported an existing SQL database atop of our distributed lock-free data structure. Here, replication plays a central role, as it contributes to improve the user experience by hiding failures and by providing acceptable latency. In this thesis, we claim that atomic multicast, with strong and well-defined properties, is the appropriate abstraction to efficiently design and implement globally scalable distributed systems. Internet-scale services rely on data partitioning and replication to provide scalable performance and high availability. Moreover, to reduce user-perceived response times and tolerate disasters (i.e., the failure of a whole datacenter), services are increasingly becoming geographically distributed. Data partitioning and replication, combined with local and geographical distribution, introduce daunting challenges, including the need to carefully order requests among replicas and partitions. One way to tackle this problem is to use group communication primitives that encapsulate order requirements. While replication is a common technique used to design such reliable distributed systems, to cope with the requirements of modern cloud based ``always-on'' applications, replication protocols must additionally allow for throughput scalability and dynamic reconfiguration, that is, on-demand replacement or provisioning of system resources. We propose a dynamic atomic multicast protocol which fulfills these requirements. It allows to dynamically add and remove resources to an online replicated state machine and to recover crashed processes. Major efforts have been spent in recent years to improve the performance, scalability and reliability of distributed systems. In order to hide the complexity of designing distributed applications, many proposals provide efficient high-level communication abstractions. Since the implementation of a production-ready system based on this abstraction is still a major task, we further propose to expose our protocol to developers in the form of distributed data structures. B- trees for example, are commonly used in different kinds of applications, including database indexes or file systems. Providing a distributed, fault-tolerant and scalable data structure would help developers to integrate their applications in a distribution transparent manner. This work describes how to build reliable and scalable distributed systems based on atomic multicast and demonstrates their capabilities by an implementation of a distributed ordered map that supports dynamic re-partitioning and fast recovery. To substantiate our claim, we ported an existing SQL database atop of our distributed lock-free data structure

    Learning from information crises: Exploring aggregated trustworthiness in big data production

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    In a crisis situation when traditional venues for information dissemination aren't reliable and information is needed immediately "aggregated trustworthiness", data verification through network evaluation and social validation, becomes an important alternative. However, the risk with evaluating credibility through trust and network reputation is that the perspective can get biased. In these socially distributed information systems there is therefore of particularly high importance to understand how data is socially produced by whom. The purpose with the research project presented in this position paper is to explore how patters of bias in information production online can become more transparent by including tools that analyze and visualize aggregated trustworthiness. the research project consists of two interconnected parts. We will first look into a recent crisis situation, the case Red Hook after Hurricane Sandy, to see how the dissemination of information took place in the recovery work, focusing on questions of credibility and trust. Thereafter, this case study will inform the design of two collaborative tools where we investigate how social validation processes can be made more transparent

    An approach to rollback recovery of collaborating mobile agents

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    Fault-tolerance is one of the main problems that must be resolved to improve the adoption of the agents' computing paradigm. In this paper, we analyse the execution model of agent platforms and the significance of the faults affecting their constituent components on the reliable execution of agent-based applications, in order to develop a pragmatic framework for agent systems fault-tolerance. The developed framework deploys a communication-pairs independent check pointing strategy to offer a low-cost, application-transparent model for reliable agent- based computing that covers all possible faults that might invalidate reliable agent execution, migration and communication and maintains the exactly-one execution property

    Checkpointing as a Service in Heterogeneous Cloud Environments

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    A non-invasive, cloud-agnostic approach is demonstrated for extending existing cloud platforms to include checkpoint-restart capability. Most cloud platforms currently rely on each application to provide its own fault tolerance. A uniform mechanism within the cloud itself serves two purposes: (a) direct support for long-running jobs, which would otherwise require a custom fault-tolerant mechanism for each application; and (b) the administrative capability to manage an over-subscribed cloud by temporarily swapping out jobs when higher priority jobs arrive. An advantage of this uniform approach is that it also supports parallel and distributed computations, over both TCP and InfiniBand, thus allowing traditional HPC applications to take advantage of an existing cloud infrastructure. Additionally, an integrated health-monitoring mechanism detects when long-running jobs either fail or incur exceptionally low performance, perhaps due to resource starvation, and proactively suspends the job. The cloud-agnostic feature is demonstrated by applying the implementation to two very different cloud platforms: Snooze and OpenStack. The use of a cloud-agnostic architecture also enables, for the first time, migration of applications from one cloud platform to another.Comment: 20 pages, 11 figures, appears in CCGrid, 201

    Restoring Trust Relationships within Collaborative Digital Preservation Federations

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    4th International Conference on Open RepositoriesThis presentation was part of the session : Conference PresentationsDate: 2009-05-19 01:00 PM – 02:30 PMThe authors extend their process for creating and establishing trust relationships to include steps for restoring trust relationships after catastrophic events. Part of this model will include best practices for business continuity relationships and will integrate trust models from Holland and Lockett (1998) and Ring and Van de Ven (1994) and how they can be applied to a process for trust restoration after periods of disaster or critical data loss. These models provide key frameworks for understanding how trust can be utilized for collaborative start points as well as for collaborative recovery points from physical natural disaster or critical data loss

    Implementing fault tolerant applications using reflective object-oriented programming

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    Abstract: Shows how reflection and object-oriented programming can be used to ease the implementation of classical fault tolerance mechanisms in distributed applications. When the underlying runtime system does not provide fault tolerance transparently, classical approaches to implementing fault tolerance mechanisms often imply mixing functional programming with non-functional programming (e.g. error processing mechanisms). The use of reflection improves the transparency of fault tolerance mechanisms to the programmer and more generally provides a clearer separation between functional and non-functional programming. The implementations of some classical replication techniques using a reflective approach are presented in detail and illustrated by several examples, which have been prototyped on a network of Unix workstations. Lessons learnt from our experiments are drawn and future work is discussed
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