A contrasting look at self-organization in the Internet and next-generation communication networks

This article examines contrasting notions of self-organization in the Internet and next-generation communication networks, by reviewing in some detail recent evidence regarding several of the more popular attempts to explain prominent features of Internet structure and behavior as "emergent phenomena." In these examples, what might appear to the nonexpert as "emergent self-organization" in the Internet actually results from well conceived (albeit perhaps ad hoc) design, with explanations that are mathematically rigorous, in agreement with engineering reality, and fully consistent with network measurements. These examples serve as concrete starting points from which networking researchers can assess whether or not explanations involving self-organization are relevant or appropriate in the context of next-generation communication networks, while also highlighting the main differences between approaches to self-organization that are rooted in engineering design vs. those inspired by statistical physics

Evolution-based modelling of complex airport networks

Copyright @ 2011 Society for Electronics, Telecommunications, Automation, and InformaticsThis paper presents a time-series model of the United States Airport Network as a directed, weighted network, with the weight representing the total number of passengers flying from an origin to a destination airport, in a two month time period. Six independent networks are built for a given year, in order to capture the seasonal variation of passengers. To explore the evolution of the network over the past two decades, three specific years are investigated: 1990, 2000, and 2010. The results highlight the growth of the network in terms of airports and connections, and suggest a scale-free, small-world topology. In addition, the ranked passenger distribution appears to follow a logarithmic trend, implying high heterogeneity in passengers on different connections.This project was funded by te Brunel Research Support and Development Office

Community structure detection in the evolution of the United States airport network

This is the post-print version of the Article. Copyright © 2013 World Scientific PublishingThis paper investigates community structure in the US Airport Network as it evolved from 1990 to 2010 by looking at six bi-monthly intervals in 1990, 2000 and 2010, using data obtained from the Bureau of Transportation Statistics of the US Department of Transport. The data contained monthly records of origin-destination pairs of domestic airports and the number of passengers carried. The topological properties and the volume of people traveling are both studied in detail, revealing high heterogeneity in space and time. A recently developed community structure detection method, accounting for the spatial nature of these networks, is applied and reveals a picture of the communities within. The patterns of communities plotted for each bi-monthly interval reveal some interesting seasonal variations of passenger flows and airport clusters that do not occupy a single US region. The long-term evolution of the network between those years is explored and found to have consistently improved its stability. The more recent structure of the network (2010) is compared with migration patterns among the four US macro-regions (West, Midwest, Northeast and South) in order to identify possible relationships and the results highlight a clear overlap between US domestic air travel and migration

The Dynamics of Internet Traffic: Self-Similarity, Self-Organization, and Complex Phenomena

The Internet is the most complex system ever created in human history. Therefore, its dynamics and traffic unsurprisingly take on a rich variety of complex dynamics, self-organization, and other phenomena that have been researched for years. This paper is a review of the complex dynamics of Internet traffic. Departing from normal treatises, we will take a view from both the network engineering and physics perspectives showing the strengths and weaknesses as well as insights of both. In addition, many less covered phenomena such as traffic oscillations, large-scale effects of worm traffic, and comparisons of the Internet and biological models will be covered.Comment: 63 pages, 7 figures, 7 tables, submitted to Advances in Complex System

Towards a Theory of Scale-Free Graphs: Definition, Properties, and Implications (Extended Version)

Although the ``scale-free'' literature is large and growing, it gives neither a precise definition of scale-free graphs nor rigorous proofs of many of their claimed properties. In fact, it is easily shown that the existing theory has many inherent contradictions and verifiably false claims. In this paper, we propose a new, mathematically precise, and structural definition of the extent to which a graph is scale-free, and prove a series of results that recover many of the claimed properties while suggesting the potential for a rich and interesting theory. With this definition, scale-free (or its opposite, scale-rich) is closely related to other structural graph properties such as various notions of self-similarity (or respectively, self-dissimilarity). Scale-free graphs are also shown to be the likely outcome of random construction processes, consistent with the heuristic definitions implicit in existing random graph approaches. Our approach clarifies much of the confusion surrounding the sensational qualitative claims in the scale-free literature, and offers rigorous and quantitative alternatives.Comment: 44 pages, 16 figures. The primary version is to appear in Internet Mathematics (2005

Cluster damage robustness analysis and space independent community detection in complex networks

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.This thesis investigates the evolution of two very different complex systems using network theory. This multi-disciplinary technique is widely used to model and analyse vastly diverse systems of multiple interacting components, and therefore, it is applied in this thesis to study the complexity of the systems. This complexity is rooted in the components’ interactions such that the whole system is more than the sum of all the individual parts. The first novelty in this research is the proposal of a new type of structural perturbation, cluster damage, for measuring another dimension of network robustness. The second novelty is the first application of a community detection method, which uncovers space-independent communities in spatial networks, to airport and linguistic networks. A critical property of complex systems – robustness – is explored within a partial model of the Internet, by demonstrating a novel perturbation strategy based on the iterative removal of clusters. The main contribution of this theoretical case study is the methodology for cluster damage, which has not been investigated by literature on the robustness of complex networks. The model, part of the Internet at the Autonomous System level, only serves as a domain where the novel methodology is demonstrated, and it is chosen because the Internet is known to be robust due to its distributed (non-centralised) nature, even though it is often subjected to large perturbations and failures. The first applied case study is in the field of air transportation. Specifically, it explores the topology and passenger flows of the United States Airport Network (USAN) over two decades. The network model consists of a time-series of six network snapshots for the years 1990, 2000 and 2010, which capture bi-monthly passenger flows among US airports. Since the network is embedded in space, the volume of these flows is naturally affected by spatial proximity, and therefore, a model (recently proposed in the literature) accounting for this phenomenon is used to identify the communities of airports that have particularly high flows among them, given their spatial separation. The second applied case study – in the field of language acquisition – investigates the word co-occurrence network of children, as they develop their linguistic abilities at an early age. Similarly to the previous case study, the network model consists of six children and three discrete developmental stages. These networks are not embedded in physical space, but they are mapped to an artificial semantic space that defines the semantic distance between pairs of words. This novel approach allows for an additional dimension of network information that results in a more complete dataset. Then, community detection identifies groups of words that have particularly high co-occurrence frequency, given their semantic distance. This research highlights the fact that some general techniques from network theory, such as network modelling and analysis, can be successfully applied for the study of diverse systems, while others, such as community detection, need to be tailored for the specific system. However, methods originally developed for one domain may be applied somewhere completely new, as illustrated by the application of spatial community detection to a non-spatial network. This underlines the importance of inter-disciplinary research

Networks, complexity and internet regulation: scale-free law

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Media handling for conferencing in MANETs

Mobile Ad hoc NETworks (MANETs) are formed by devices set up temporarily to communicate without using a pre-existing network infrastructure. Devices in these networks are disparate in terms of resource capabilities (e.g. processing power, battery energy). Multihop Cellular Networks (MCNs) incorporate multihop mobile ad-hoc paradigms into 3G conventional single-hop cellular networks. Conferencing, an essential category of applications in MANETs and MCNs, includes popular applications such as audio/video conferencing. It is defined as an interactive multimedia service comprising online exchange of multimedia content among several users. Conferencing requires two sessions: a call signaling session and a media handling session. Call signaling is used to set up, modify, and tear down conference sessions. Media handling deals with aspects such as media transportation, media mixing, and transcoding. In this thesis, we are concerned with media handling for conferencing in MANETs and MCNs. We propose an architecture based on two overlay networks: one for mixing and one for control. The first overlay is composed of nodes acting as mixers. Each node in the network has a media connection with one mixer in the first overlay. A novel distributed mixing architecture that minimizes the number of mixers in end-to-end paths is proposed as an architectural solution for this first overlay. A sub-network of nodes, called controllers, composes the second overlay. Each controller controls a set of mixers, and collectively, they manage and control the two-overlay network. The management and control tasks are assured by a media signaling architecture based on an extended version of Megaco/H.L248. The two-overlay network is self-organizing, and thus automatically assigns users to mixers, controls mixers and controllers, and recovers the network from failures. We propose a novel self-organizing scheme that has three components: self-growing, self-shrinking and self-healing. Self-growing and self-shrinking use novel workload balancing schemes that make decisions to enable and disable mixers and controllers. The workload balancing schemes use resources efficiently by balancing the load among the nodes according to their capabilities. Self-healing detects failed nodes and recovers the network when failures of nodes with responsibilities (mixers and controllers) occur. Detection of failed nodes is based on a novel application-level failure detection architecture. A novel architecture for media handling in MCNs is proposed. We use mediator concepts to connect the media handling entities of a MANET with the media entities of a 3G cellular network. A media mediator assures signaling and media connectivity between the two networks and acts as a translator of the different media handling protocols