1,552 research outputs found
A Configurable Transport Layer for CAF
The message-driven nature of actors lays a foundation for developing scalable
and distributed software. While the actor itself has been thoroughly modeled,
the message passing layer lacks a common definition. Properties and guarantees
of message exchange often shift with implementations and contexts. This adds
complexity to the development process, limits portability, and removes
transparency from distributed actor systems.
In this work, we examine actor communication, focusing on the implementation
and runtime costs of reliable and ordered delivery. Both guarantees are often
based on TCP for remote messaging, which mixes network transport with the
semantics of messaging. However, the choice of transport may follow different
constraints and is often governed by deployment. As a first step towards
re-architecting actor-to-actor communication, we decouple the messaging
guarantees from the transport protocol. We validate our approach by redesigning
the network stack of the C++ Actor Framework (CAF) so that it allows to combine
an arbitrary transport protocol with additional functions for remote messaging.
An evaluation quantifies the cost of composability and the impact of individual
layers on the entire stack
Actor-based Concurrency in Newspeak 4
Actors are a model of computation invented by Carl Hewitt in the 1970s. It has seen a resurrection of mainstream use recently as a potential solution to the latency and concurrency that are quickly rising as the dominant challenges facing the software industry. In this project I explored the history of the actor model and a practical implementation of actor-based concurrency tightly integrated with non-blocking futures in the E programming language developed by Mark Miller. I implemented an actor-based concurrency framework for Newspeak that closely follows the E implementation and includes E-style futures and deep integration into the programming language via new syntax for asynchronous message passing
Lightweight Asynchronous Snapshots for Distributed Dataflows
Distributed stateful stream processing enables the deployment and execution
of large scale continuous computations in the cloud, targeting both low latency
and high throughput. One of the most fundamental challenges of this paradigm is
providing processing guarantees under potential failures. Existing approaches
rely on periodic global state snapshots that can be used for failure recovery.
Those approaches suffer from two main drawbacks. First, they often stall the
overall computation which impacts ingestion. Second, they eagerly persist all
records in transit along with the operation states which results in larger
snapshots than required. In this work we propose Asynchronous Barrier
Snapshotting (ABS), a lightweight algorithm suited for modern dataflow
execution engines that minimises space requirements. ABS persists only operator
states on acyclic execution topologies while keeping a minimal record log on
cyclic dataflows. We implemented ABS on Apache Flink, a distributed analytics
engine that supports stateful stream processing. Our evaluation shows that our
algorithm does not have a heavy impact on the execution, maintaining linear
scalability and performing well with frequent snapshots.Comment: 8 pages, 7 figure
Fisheye Consistency: Keeping Data in Synch in a Georeplicated World
Over the last thirty years, numerous consistency conditions for replicated
data have been proposed and implemented. Popular examples of such conditions
include linearizability (or atomicity), sequential consistency, causal
consistency, and eventual consistency. These consistency conditions are usually
defined independently from the computing entities (nodes) that manipulate the
replicated data; i.e., they do not take into account how computing entities
might be linked to one another, or geographically distributed. To address this
lack, as a first contribution, this paper introduces the notion of proximity
graph between computing nodes. If two nodes are connected in this graph, their
operations must satisfy a strong consistency condition, while the operations
invoked by other nodes are allowed to satisfy a weaker condition. The second
contribution is the use of such a graph to provide a generic approach to the
hybridization of data consistency conditions into the same system. We
illustrate this approach on sequential consistency and causal consistency, and
present a model in which all data operations are causally consistent, while
operations by neighboring processes in the proximity graph are sequentially
consistent. The third contribution of the paper is the design and the proof of
a distributed algorithm based on this proximity graph, which combines
sequential consistency and causal consistency (the resulting condition is
called fisheye consistency). In doing so the paper not only extends the domain
of consistency conditions, but provides a generic provably correct solution of
direct relevance to modern georeplicated systems
Strong Consistency for Shared Objects in Pervasive Grids
International audienceRecent advances in communication technology en- able the emergence of a new generation of applications that integrates mobile devices with classical high performance systems as part of a common computing environment. In such environ- ments, keeping the coherence of shared data (distributed objects, for example) represents a real challenge as communications are strongly influenced by the performance and the reliability of mobile devices (laptops, PDAs and cellular telephones) and wireless networks (WiFi, Bluetooth). Indeed, data incoherence may arise due to message losses or node volatility, which blocks the algorithms used to synchronize these data. In this paper, we analyze the main challenges concerning the manipulation of shared distributed objects in a pervasive environment. We demonstrate how a membership service can be enhanced to tolerate temporary disconnections and message losses without blocking, while reducing the number of exchanged message
Scalability approaches for causal multicast: a survey
The final publication is available at Springer via http://dx.doi.org/10.1007/s00607-015-0479-0Many distributed services need to be scalable: internet search,
electronic commerce, e-government... In order to
achieve scalability, high availability and fault tolerance, such
applications rely on replicated components. Because of the dynamics
of growth and volatility of customer markets, applications need to be
hosted by adaptive, highly scalable systems. In particular, the
scalability of the reliable multicast mechanisms used for supporting
the consistency of replicas is of crucial importance. Reliable
multicast might propagate updates in a pre-determined order (e.g.,
FIFO, total or causal). Since total order needs more communication
rounds than causal order, the latter appears to be the preferable
candidate for achieving multicast scalability, although the
consistency guarantees based on causal order are weaker than those of
total order. This paper provides a historical survey of different
scalability approaches for reliable causal multicast protocols.This work was supported by European Regional Development Fund (FEDER) and Ministerio de Economia y Competitividad (MINECO) under research Grant TIN2012-37719-C03-01.Juan MarĂn, RD.; Decker, H.; ArmendĂĄriz Ăñigo, JE.; Bernabeu AubĂĄn, JM.; Muñoz EscoĂ, FD. (2016). Scalability approaches for causal multicast: a survey. Computing. 98(9):923-947. https://doi.org/10.1007/s00607-015-0479-0S923947989Adly N, Nagi M (1995) Maintaining causal order in large scale distributed systems using a logical hierarchy. In: IASTED Intnl Conf on Appl Inform, pp 214â219Aguilera MK, Chen W, Toueg S (1997) Heartbeat: a timeout-free failure detector for quiescent reliable communication. In: 11th Intnl Wshop on Distrib Alg (WDAG), SaarbrĂŒcken, pp 126â140Almeida JB, Almeida PS, Baquero C (2004) Bounded version vectors. In: 18th Intnl Conf Distrib Comput (DISC), Amsterdam, pp 102â116Almeida PS, Baquero C, Fonte V (2008) Interval tree clocks. 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Assessing load-sharing within optimistic simulation platforms
The advent of multi-core machines has lead to the need for revising the architecture of modern simulation platforms. One recent proposal we made attempted to explore the viability of load-sharing for optimistic simulators run on top of these types of machines. In this article, we provide an extensive experimental study for an assessment of the effects on run-time dynamics by a load-sharing architecture that has been implemented within the ROOT-Sim package, namely an open source simulation platform adhering to the optimistic synchronization paradigm. This experimental study is essentially aimed at evaluating possible sources of overheads when supporting load-sharing. It has been based on differentiated workloads allowing us to generate different execution profiles in terms of, e.g., granularity/locality of the simulation events. © 2012 IEEE
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