69 research outputs found
Chinese Internet AS-level Topology
We present the first complete measurement of the Chinese Internet topology at
the autonomous systems (AS) level based on traceroute data probed from servers
of major ISPs in mainland China. We show that both the Chinese Internet AS
graph and the global Internet AS graph can be accurately reproduced by the
Positive-Feedback Preference (PFP) model with the same parameters. This result
suggests that the Chinese Internet preserves well the topological
characteristics of the global Internet. This is the first demonstration of the
Internet's topological fractality, or self-similarity, performed at the level
of topology evolution modeling.Comment: This paper is a preprint of a paper submitted to IEE Proceedings on
Communications and is subject to Institution of Engineering and Technology
Copyright. If accepted, the copy of record will be available at IET Digital
Librar
Distances in random graphs with finite variance degrees
In this paper we study a random graph with nodes, where node has
degree and are i.i.d. with \prob(D_j\leq x)=F(x). We
assume that for some and some constant
. This graph model is a variant of the so-called configuration model, and
includes heavy tail degrees with finite variance.
The minimal number of edges between two arbitrary connected nodes, also known
as the graph distance or the hopcount, is investigated when . We
prove that the graph distance grows like , when the base of the
logarithm equals \nu=\expec[D_j(D_j -1)]/\expec[D_j]>1. This confirms the
heuristic argument of Newman, Strogatz and Watts \cite{NSW00}. In addition, the
random fluctuations around this asymptotic mean are
characterized and shown to be uniformly bounded. In particular, we show
convergence in distribution of the centered graph distance along exponentially
growing subsequences.Comment: 40 pages, 2 figure
Understanding edge-connectivity in the Internet through core-decomposition
Internet is a complex network composed by several networks: the Autonomous
Systems, each one designed to transport information efficiently. Routing
protocols aim to find paths between nodes whenever it is possible (i.e., the
network is not partitioned), or to find paths verifying specific constraints
(e.g., a certain QoS is required). As connectivity is a measure related to both
of them (partitions and selected paths) this work provides a formal lower bound
to it based on core-decomposition, under certain conditions, and low complexity
algorithms to find it. We apply them to analyze maps obtained from the
prominent Internet mapping projects, using the LaNet-vi open-source software
for its visualization
Router-level community structure of the Internet Autonomous Systems
The Internet is composed of routing devices connected between them and
organized into independent administrative entities: the Autonomous Systems. The
existence of different types of Autonomous Systems (like large connectivity
providers, Internet Service Providers or universities) together with
geographical and economical constraints, turns the Internet into a complex
modular and hierarchical network. This organization is reflected in many
properties of the Internet topology, like its high degree of clustering and its
robustness.
In this work, we study the modular structure of the Internet router-level
graph in order to assess to what extent the Autonomous Systems satisfy some of
the known notions of community structure. We show that the modular structure of
the Internet is much richer than what can be captured by the current community
detection methods, which are severely affected by resolution limits and by the
heterogeneity of the Autonomous Systems. Here we overcome this issue by using a
multiresolution detection algorithm combined with a small sample of nodes. We
also discuss recent work on community structure in the light of our results
IHMCIF: An Extension of the PDBx/mmCIF Data Standard for Integrative Structure Determination Methods
IHMCIF (github.com/ihmwg/IHMCIF) is a data information framework that supports archiving and disseminating macromolecular structures determined by integrative or hybrid modeling (IHM), and making them Findable, Accessible, Interoperable, and Reusable (FAIR). IHMCIF is an extension of the Protein Data Bank Exchange/macromolecular Crystallographic Information Framework (PDBx/mmCIF) that serves as the framework for the Protein Data Bank (PDB) to archive experimentally determined atomic structures of biological macromolecules and their complexes with one another and small molecule ligands (e.g., enzyme cofactors and drugs). IHMCIF serves as the foundational data standard for the PDB-Dev prototype system, developed for archiving and disseminating integrative structures. It utilizes a flexible data representation to describe integrative structures that span multiple spatiotemporal scales and structural states with definitions for restraints from a variety of experimental methods contributing to integrative structural biology. The IHMCIF extension was created with the benefit of considerable community input and recommendations gathered by the Worldwide Protein Data Bank (wwPDB) Task Force for Integrative or Hybrid Methods (wwpdb.org/task/hybrid). Herein, we describe the development of IHMCIF to support evolving methodologies and ongoing advancements in integrative structural biology. Ultimately, IHMCIF will facilitate the unification of PDB-Dev data and tools with the PDB archive so that integrative structures can be archived and disseminated through PDB
Network-aware Distributed Computing: A Case Study
. The development of network-aware applications, i.e. applications that dynamically adapt to network conditions, has had some success in the domain of multimedia applications, but progress has been very slow for distributed computing applications. The reason is that the relationship between application performance and network performance is typically more complex for that class of applications, making adaptation di#cult. In this paper we introduce two adaptation methods for distributed computing applications, one based on a performance model and another based on balancing computation and communication time. We illustrate the two methods using a simple distributed application (matrix multiply) and compare their performance. We show that both methods can correctly estimate the best number of nodes to use on our testbed. We also show that both methods have weaknesses. Model-based adaptation requires an accurate performance model and is sensitive to errors in measurements of ..
On Characterizing Network Hierarchy
Our previous work in topology characterization and hierarchy [1] introduced a hierarchy metric to explore the hierarchical structure in various networks. This metric is non-intuitive and complicated. In this paper, we propose a simpler and more natural metric for measuring network hierarchy. This simpler metric uses slightly different criteria in selecting backbone links than the more complicated one. Nevertheless, the network classifications according to both metrics agree with each other. Furthermore, we have extended the hierarchy analysis to examine path characteristics and found that the hierarchical nature of degree-based networks better resembles the hierarchy of the Internet at the AS level than at the routerlevel
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