10,638 research outputs found
Connectivity aware routing - a method for finding bandwidth constrained paths over a variety of network topologies
Multimedia traffic and real-time e-commerce applications can experience quality degradation in traditional networks such as the Internet. These difficulties can be overcome in networks which feature dynamically set up paths with bandwidth and delay guarantees. The problem of selecting such constrained paths is the task of quality of service (QoS) routing. Researchers have proposed several ways of implementing QoS routing, preferring either mechanisms which distribute network load or algorithms which conserve resources. Our previous studies have shown that network connectivity is an important factor when deciding which of these two approaches gives the best performance. In this paper we propose an algorithm, which features both load distribution and resource conservation. It takes a hybrid approach which balances between these two extreme approaches, according to the level of network connectivity. Our simulations indicate that this algorithm offers excellent performance over a than existing algorithms
Sustaining the Internet with Hyperbolic Mapping
The Internet infrastructure is severely stressed. Rapidly growing overheads
associated with the primary function of the Internet---routing information
packets between any two computers in the world---cause concerns among Internet
experts that the existing Internet routing architecture may not sustain even
another decade. Here we present a method to map the Internet to a hyperbolic
space. Guided with the constructed map, which we release with this paper,
Internet routing exhibits scaling properties close to theoretically best
possible, thus resolving serious scaling limitations that the Internet faces
today. Besides this immediate practical viability, our network mapping method
can provide a different perspective on the community structure in complex
networks
Energy-efficient traffic engineering
The energy consumption in telecommunication networks is expected to grow considerably, especially in core networks. In this chapter, optimization of energy consumption is approached from two directions. In a first study, multilayer traffic engineering (MLTE) is used to assign energy-efficient paths and logical topology to IP traffic. The relation with traditional capacity optimization is explained, and the MLTE strategy is applied for daily traffic variations. A second study considers the core network below the IP layer, giving a detailed power consumption model. Optical bypass is evaluated as a technique to achieve considerable power savings over per-hop opticalelectronicoptical regeneration.
Document type: Part of book or chapter of boo
Robust geometric forest routing with tunable load balancing
Although geometric routing is proposed as a memory-efficient alternative to traditional lookup-based routing and forwarding algorithms, it still lacks: i) adequate mechanisms to trade stretch against load balancing, and ii) robustness to cope with network topology change.
The main contribution of this paper involves the proposal of a family of routing schemes, called Forest Routing. These are based on the principles of geometric routing, adding flexibility in its load balancing characteristics. This is achieved by using an aggregation of greedy embeddings along with a configurable distance function. Incorporating link load information in the forwarding layer enables load balancing behavior while still attaining low path stretch. In addition, the proposed schemes are validated regarding their resilience towards network failures
The Large Scale Curvature of Networks
Understanding key structural properties of large scale networks are crucial
for analyzing and optimizing their performance, and improving their reliability
and security. Here we show that these networks possess a previously unnoticed
feature, global curvature, which we argue has a major impact on core
congestion: the load at the core of a network with N nodes scales as N^2 as
compared to N^1.5 for a flat network. We substantiate this claim through
analysis of a collection of real data networks across the globe as measured and
documented by previous researchers.Comment: 4 pages, 5 figure
The Internet AS-Level Topology: Three Data Sources and One Definitive Metric
We calculate an extensive set of characteristics for Internet AS topologies
extracted from the three data sources most frequently used by the research
community: traceroutes, BGP, and WHOIS. We discover that traceroute and BGP
topologies are similar to one another but differ substantially from the WHOIS
topology. Among the widely considered metrics, we find that the joint degree
distribution appears to fundamentally characterize Internet AS topologies as
well as narrowly define values for other important metrics. We discuss the
interplay between the specifics of the three data collection mechanisms and the
resulting topology views. In particular, we show how the data collection
peculiarities explain differences in the resulting joint degree distributions
of the respective topologies. Finally, we release to the community the input
topology datasets, along with the scripts and output of our calculations. This
supplement should enable researchers to validate their models against real data
and to make more informed selection of topology data sources for their specific
needs.Comment: This paper is a revised journal version of cs.NI/050803
Graph Annotations in Modeling Complex Network Topologies
The coarsest approximation of the structure of a complex network, such as the
Internet, is a simple undirected unweighted graph. This approximation, however,
loses too much detail. In reality, objects represented by vertices and edges in
such a graph possess some non-trivial internal structure that varies across and
differentiates among distinct types of links or nodes. In this work, we
abstract such additional information as network annotations. We introduce a
network topology modeling framework that treats annotations as an extended
correlation profile of a network. Assuming we have this profile measured for a
given network, we present an algorithm to rescale it in order to construct
networks of varying size that still reproduce the original measured annotation
profile.
Using this methodology, we accurately capture the network properties
essential for realistic simulations of network applications and protocols, or
any other simulations involving complex network topologies, including modeling
and simulation of network evolution. We apply our approach to the Autonomous
System (AS) topology of the Internet annotated with business relationships
between ASs. This topology captures the large-scale structure of the Internet.
In depth understanding of this structure and tools to model it are cornerstones
of research on future Internet architectures and designs. We find that our
techniques are able to accurately capture the structure of annotation
correlations within this topology, thus reproducing a number of its important
properties in synthetically-generated random graphs
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