57,900 research outputs found
Evaluating Connection Resilience for the Overlay Network Kademlia
Kademlia is a decentralized overlay network, up to now mainly used for highly
scalable file sharing applications. Due to its distributed nature, it is free
from single points of failure. Communication can happen over redundant network
paths, which makes information distribution with Kademlia resilient against
failing nodes and attacks. This makes it applicable to more scenarios than
Internet file sharing. In this paper, we simulate Kademlia networks with
varying parameters and analyze the number of node-disjoint paths in the
network, and thereby the network connectivity. A high network connectivity is
required for communication and system-wide adaptation even when some nodes or
communication channels fail or get compromised by an attacker. With our
results, we show the influence of these parameters on the connectivity and,
therefore, the resilience against failing nodes and communication channels.Comment: 12 pages, 14 figures, accepted to ICDCS2017. arXiv admin note:
substantial text overlap with arXiv:1605.0800
Stochastic model for the 3D microstructure of pristine and cyclically aged cathodes in Li-ion batteries
It is well-known that the microstructure of electrodes in lithium-ion
batteries strongly affects their performance. Vice versa, the microstructure
can exhibit strong changes during the usage of the battery due to aging
effects. For a better understanding of these effects, mathematical analysis and
modeling has turned out to be of great help. In particular, stochastic 3D
microstructure models have proven to be a powerful and very flexible tool to
generate various kinds of particle-based structures. Recently, such models have
been proposed for the microstructure of anodes in lithium-ion energy and power
cells. In the present paper, we describe a stochastic modeling approach for the
3D microstructure of cathodes in a lithium-ion energy cell, which differs
significantly from the one observed in anodes. The model for the cathode data
enhances the ideas of the anode models, which have been developed so far. It is
calibrated using 3D tomographic image data from pristine as well as two aged
cathodes. A validation based on morphological image characteristics shows that
the model is able to realistically describe both, the microstructure of
pristine and aged cathodes. Thus, we conclude that the model is suitable to
generate virtual, but realistic microstructures of lithium-ion cathodes
Theoretically Efficient Parallel Graph Algorithms Can Be Fast and Scalable
There has been significant recent interest in parallel graph processing due
to the need to quickly analyze the large graphs available today. Many graph
codes have been designed for distributed memory or external memory. However,
today even the largest publicly-available real-world graph (the Hyperlink Web
graph with over 3.5 billion vertices and 128 billion edges) can fit in the
memory of a single commodity multicore server. Nevertheless, most experimental
work in the literature report results on much smaller graphs, and the ones for
the Hyperlink graph use distributed or external memory. Therefore, it is
natural to ask whether we can efficiently solve a broad class of graph problems
on this graph in memory.
This paper shows that theoretically-efficient parallel graph algorithms can
scale to the largest publicly-available graphs using a single machine with a
terabyte of RAM, processing them in minutes. We give implementations of
theoretically-efficient parallel algorithms for 20 important graph problems. We
also present the optimizations and techniques that we used in our
implementations, which were crucial in enabling us to process these large
graphs quickly. We show that the running times of our implementations
outperform existing state-of-the-art implementations on the largest real-world
graphs. For many of the problems that we consider, this is the first time they
have been solved on graphs at this scale. We have made the implementations
developed in this work publicly-available as the Graph-Based Benchmark Suite
(GBBS).Comment: This is the full version of the paper appearing in the ACM Symposium
on Parallelism in Algorithms and Architectures (SPAA), 201
Clustering and Community Detection with Imbalanced Clusters
Spectral clustering methods which are frequently used in clustering and
community detection applications are sensitive to the specific graph
constructions particularly when imbalanced clusters are present. We show that
ratio cut (RCut) or normalized cut (NCut) objectives are not tailored to
imbalanced cluster sizes since they tend to emphasize cut sizes over cut
values. We propose a graph partitioning problem that seeks minimum cut
partitions under minimum size constraints on partitions to deal with imbalanced
cluster sizes. Our approach parameterizes a family of graphs by adaptively
modulating node degrees on a fixed node set, yielding a set of parameter
dependent cuts reflecting varying levels of imbalance. The solution to our
problem is then obtained by optimizing over these parameters. We present
rigorous limit cut analysis results to justify our approach and demonstrate the
superiority of our method through experiments on synthetic and real datasets
for data clustering, semi-supervised learning and community detection.Comment: Extended version of arXiv:1309.2303 with new applications. Accepted
to IEEE TSIP
Power Aware Routing for Sensor Databases
Wireless sensor networks offer the potential to span and monitor large
geographical areas inexpensively. Sensor network databases like TinyDB are the
dominant architectures to extract and manage data in such networks. Since
sensors have significant power constraints (battery life), and high
communication costs, design of energy efficient communication algorithms is of
great importance. The data flow in a sensor database is very different from
data flow in an ordinary network and poses novel challenges in designing
efficient routing algorithms. In this work we explore the problem of energy
efficient routing for various different types of database queries and show that
in general, this problem is NP-complete. We give a constant factor
approximation algorithm for one class of query, and for other queries give
heuristic algorithms. We evaluate the efficiency of the proposed algorithms by
simulation and demonstrate their near optimal performance for various network
sizes
Connectivity measures for internet topologies.
The topology of the Internet has initially been modelled as an undirected graph, where vertices correspond to so-called Autonomous Systems (ASs),and edges correspond to physical links between pairs of ASs. However, in order to capture the impact of routing policies, it has recently become apparent that one needs to classify the edges according to the existing economic relationships (customer-provider, peer-to-peer or siblings) between the ASs. This leads to a directed graph model in which traffic can be sent only along so-called valley-free paths. Four different algorithms have been proposed in the literature for inferring AS relationships using publicly available data from routing tables. We investigate the differences in the graph models produced by these algorithms, focussing on connectivity measures. To this aim, we compute the maximum number of vertex-disjoint valley-free paths between ASs as well as the size of a minimum cut separating a pair of ASs. Although these problems are solvable in polynomial time for ordinary graphs, they are NP-hard in our setting. We formulate the two problems as integer programs, and we propose a number of exact algorithms for solving them. For the problem of finding the maximum number of vertex-disjoint paths, we discuss two algorithms; the first one is a branch-and-price algorithm based on the IP formulation, and the second algorithm is a non LP based branch-and-bound algorithm. For the problem of finding minimum cuts we use a branch-and-cut algo rithm, based on the IP formulation of this problem. Using these algorithms, we obtain exact solutions for both problems in reasonable time. It turns out that there is a large gap in terms of the connectivity measures between the undirected and directed models. This finding supports our conclusion that economic relationships need to be taken into account when building a topology of the Internet.Research; Internet;
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