47,945 research outputs found
Crux: Locality-Preserving Distributed Services
Distributed systems achieve scalability by distributing load across many
machines, but wide-area deployments can introduce worst-case response latencies
proportional to the network's diameter. Crux is a general framework to build
locality-preserving distributed systems, by transforming an existing scalable
distributed algorithm A into a new locality-preserving algorithm ALP, which
guarantees for any two clients u and v interacting via ALP that their
interactions exhibit worst-case response latencies proportional to the network
latency between u and v. Crux builds on compact-routing theory, but generalizes
these techniques beyond routing applications. Crux provides weak and strong
consistency flavors, and shows latency improvements for localized interactions
in both cases, specifically up to several orders of magnitude for
weakly-consistent Crux (from roughly 900ms to 1ms). We deployed on PlanetLab
locality-preserving versions of a Memcached distributed cache, a Bamboo
distributed hash table, and a Redis publish/subscribe. Our results indicate
that Crux is effective and applicable to a variety of existing distributed
algorithms.Comment: 11 figure
Implementing a distributed mobile calculus using the IMC framework
In the last decade, many calculi for modelling distributed mobile code have been proposed. To assess their merits and encourage use, implementations of the calculi have often been proposed. These implementations usually consist of a limited part dealing with mechanisms that are specific of the proposed calculus and of a significantly larger part handling recurrent mechanisms that are common to many calculi. Nevertheless, also the "classic" parts are often re-implemented from scratch. In this paper we show how to implement a well established representative of the family of mobile calculi, the distributed [pi]-calculus, by using a Java middleware (called IMC - Implementing Mobile Calculi) where recurrent mechanisms of distributed and mobile systems are already implemented. By means of the case study, we illustrate a methodology to accelerate the development of prototype implementations while concentrating only on the features that are specific of the calculus under consideration and relying on the common framework for all the recurrent mechanisms like network connections, code mobility, name handling, etc
Transit Node Routing Reconsidered
Transit Node Routing (TNR) is a fast and exact distance oracle for road
networks. We show several new results for TNR. First, we give a surprisingly
simple implementation fully based on Contraction Hierarchies that speeds up
preprocessing by an order of magnitude approaching the time for just finding a
CH (which alone has two orders of magnitude larger query time). We also develop
a very effective purely graph theoretical locality filter without any
compromise in query times. Finally, we show that a specialization to the online
many-to-one (or one-to-many) shortest path further speeds up query time by an
order of magnitude. This variant even has better query time than the fastest
known previous methods which need much more space.Comment: 19 pages, submitted to SEA'201
Why and When Can Deep -- but Not Shallow -- Networks Avoid the Curse of Dimensionality: a Review
The paper characterizes classes of functions for which deep learning can be
exponentially better than shallow learning. Deep convolutional networks are a
special case of these conditions, though weight sharing is not the main reason
for their exponential advantage
Towards a Formal Framework for Mobile, Service-Oriented Sensor-Actuator Networks
Service-oriented sensor-actuator networks (SOSANETs) are deployed in
health-critical applications like patient monitoring and have to fulfill strong
safety requirements. However, a framework for the rigorous formal modeling and
analysis of SOSANETs does not exist. In particular, there is currently no
support for the verification of correct network behavior after node failure or
loss/addition of communication links. To overcome this problem, we propose a
formal framework for SOSANETs. The main idea is to base our framework on the
\pi-calculus, a formally defined, compositional and well-established formalism.
We choose KLAIM, an existing formal language based on the \pi-calculus as the
foundation for our framework. With that, we are able to formally model SOSANETs
with possible topology changes and network failures. This provides the basis
for our future work on prediction, analysis and verification of the network
behavior of these systems. Furthermore, we illustrate the real-life
applicability of this approach by modeling and extending a use case scenario
from the medical domain.Comment: In Proceedings FESCA 2013, arXiv:1302.478
H-word: Supporting job scheduling in Hadoop with workload-driven data redistribution
The final publication is available at http://link.springer.com/chapter/10.1007/978-3-319-44039-2_21Today’s distributed data processing systems typically follow a query shipping approach and exploit data locality for reducing network traffic. In such systems the distribution of data over the cluster resources plays a significant role, and when skewed, it can harm the performance of executing applications. In this paper, we addressthe challenges of automatically adapting the distribution of data in a cluster to the workload imposed by the input applications. We propose a generic algorithm, named H-WorD, which, based on the estimated workload over resources, suggests alternative execution scenarios of tasks, and hence identifies required transfers of input data a priori, for timely bringing data close to the execution. We exemplify our algorithm in the context of MapReduce jobs in a Hadoop ecosystem. Finally, we evaluate our approach and demonstrate the performance gains of automatic data redistribution.Peer ReviewedPostprint (author's final draft
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