11 research outputs found
Evolution of the Internet AS-Level Ecosystem
We present an analytically tractable model of Internet evolution at the level
of Autonomous Systems (ASs). We call our model the multiclass preferential
attachment (MPA) model. As its name suggests, it is based on preferential
attachment. All of its parameters are measurable from available Internet
topology data. Given the estimated values of these parameters, our analytic
results predict a definitive set of statistics characterizing the AS topology
structure. These statistics are not part of the model formulation. The MPA
model thus closes the "measure-model-validate-predict" loop, and provides
further evidence that preferential attachment is a driving force behind
Internet evolution
An integrated model of traffic, geography and economy in the Internet
Modeling Internet growth is important both for understanding the current
network and to predict and improve its future. To date, Internet models have
typically attempted to explain a subset of the following characteristics:
network structure, traffic flow, geography, and economy. In this paper we
present a discrete, agent-based model, that integrates all of them. We show
that the model generates networks with topologies, dynamics, and (more
speculatively) spatial distributions that are similar to the Internet
Paul Baran, Network Theory, and the Past, Present, and Future of Internet
Paul Baran’s seminal 1964 article “On Distributed Communications Networks” that first proposed packet switching also advanced an underappreciated vision of network architecture: a lattice-like, distributed network, in which each node of the Internet would be homogeneous and equal in status to all other nodes. Scholars who have subsequently embraced the concept of a lattice-like network approach have largely overlooked the extent to which it is both inconsistent with network theory (associated with the work of Duncan Watts and Albert-László Barabási), which emphasizes the importance of short cuts and hubs in enabling networks to scale, and the actual way, the Internet initially deployed, which relied on a three-tiered, hierarchical architecture that was actually what Baran called a decentralized network. However, empirical studies reveal that the Internet’s architecture is changing: it is in the process of becoming flatter and less hierarchical, as large content providers build extensive wide area networks and undersea cables to connect directly to last-mile networks. This change is making the network more centralized rather than becoming more distributed. As a result, this article suggests that the standard reference model that places backbones at the center of the architecture should be replaced with a radically different vision: a stack of centralized star networks, each centered on one of the leading content providers
Distributed Internet security and measurement
The Internet has developed into an important economic, military, academic, and social resource. It is a complex network, comprised of tens of thousands of independently operated networks, called Autonomous Systems (ASes). A significant strength of the Internet\u27s design, one which enabled its rapid growth in terms of users and bandwidth, is that its underlying protocols (such as IP, TCP, and BGP) are distributed. Users and networks alike can attach and detach from the Internet at will, without causing major disruptions to global Internet connectivity. This dissertation shows that the Internet\u27s distributed, and often redundant structure, can be exploited to increase the security of its protocols, particularly BGP (the Internet\u27s interdomain routing protocol). It introduces Pretty Good BGP, an anomaly detection protocol coupled with an automated response that can protect individual networks from BGP attacks. It also presents statistical measurements of the Internet\u27s structure and uses them to create a model of Internet growth. This work could be used, for instance, to test upcoming routing protocols on ensemble of large, Internet-like graphs. Finally, this dissertation shows that while the Internet is designed to be agnostic to political influence, it is actually quite centralized at the country level. With the recent rise in country-level Internet policies, such as nation-wide censorship and warrantless wiretaps, this centralized control could have significant impact on international reachability
Compact routing for the future internet
The Internet relies on its inter-domain routing system to allow data
transfer between any two endpoints regardless of where they are
located. This routing system currently uses a shortest path routing algorithm
(modified by local policy constraints) called the Border Gateway
Protocol. The massive growth of the Internet has led to large routing
tables that will continue to grow. This will present a serious
engineering challenge for router designers in the long-term,
rendering state (routing table) growth at this pace unsustainable.
There are various short-term engineering solutions that may slow the
growth of the inter-domain routing tables, at the expense of increasing
the complexity of the network. In addition, some of these require manual configuration, or
introduce additional points of failure within the network. These solutions may
give an incremental, constant factor, improvement. However,
we know from previous work that all shortest path routing algorithms
require forwarding state that grows linearly with the size of the
network in the worst case.
Rather than attempt to sustain inter-domain routing through a
shortest path routing algorithm, compact routing algorithms exist that
guarantee worst-case sub-linear state requirements at all nodes by
allowing an upper-bound on path length relative to the theoretical
shortest path, known as path stretch. Previous work has shown
the promise of these algorithms when applied to synthetic graphs
with similar properties to the known Internet
graph, but they haven't been studied in-depth on Internet topologies
derived from real data.
In this dissertation, I demonstrate the consistently strong
performance of these compact routing algorithms for inter-domain routing by performing
a longitudinal study of two compact routing algorithms on the Internet
Autonomous System (AS) graph over time.
I then show, using the k-cores graph decomposition algorithm, that
the structurally important nodes in the AS graph are highly stable
over time. This property makes these nodes suitable for use as the
"landmark" nodes used by the most stable of the compact routing
algorithms evaluated, and the use of these nodes shows similar strong
routing performance.
Finally, I present a decentralised compact routing algorithm for
dynamic graphs, and present state requirements and message overheads
on AS graphs using realistic simulation inputs.
To allow the continued long-term growth of Internet routing state, an
alternative routing architecture may be required. The use of the
compact routing algorithms presented in this dissertation offer
promise for a scalable future Internet routing system
Actas da 10ÂŞ ConferĂŞncia sobre Redes de Computadores
Universidade do MinhoCCTCCentro AlgoritmiCisco SystemsIEEE Portugal Sectio
The One with the Social Network Analysis: the extraction, analysis and modelling of temporal social networks from narratives
Narratives tell us about the people, cultures, and time periods in and about which they were written. Therefore, narrative analysis is a powerful tool for understanding culture. One way to analyse narratives is through their social networks, however extracting the network is a complex task. Manually recording characters and their interactions is an accurate, but time consuming method for narrative social network extraction, however efficient automatic extraction methods may introduce errors. In this thesis, we perform a detailed comparative study of narrative social network extraction techniques, and investigate the effect the techniques have on the analysis of the narrative. We use the 1994–2004 television series Friends as a case study to model and compare extraction techniques. By designing a simulated social network and observation processes resembling different network extraction techniques, we find that automated network extraction methods are reliable for computing many network metrics, but can distort the clustering coefficient. Our comparison of extraction techniques allows for many more narratives to be extracted and analysed efficiently. We also analyse and model the social networks of Friends, to gain new insights into the the series, and what made it successful. We show which are the most important characters and relationships, and through modelling social network features we find the most informative features to predict success. Our analysis of Friends provides an example and a building block for deeper understanding about particular narratives and narratives in general.Thesis (MPhil) -- University of Adelaide, School of Mathematical Sciences, 201