8,630 research outputs found
Information Super-Diffusion on Structured Networks
We study diffusion of information packets on several classes of structured
networks. Packets diffuse from a randomly chosen node to a specified
destination in the network. As local transport rules we consider random
diffusion and an improved local search method. Numerical simulations are
performed in the regime of stationary workloads away from the jamming
transition. We find that graph topology determines the properties of diffusion
in a universal way, which is reflected by power-laws in the transit-time and
velocity distributions of packets. With the use of multifractal scaling
analysis and arguments of non-extensive statistics we find that these
power-laws are compatible with super-diffusive traffic for random diffusion and
for improved local search. We are able to quantify the role of network topology
on overall transport efficiency. Further, we demonstrate the implications of
improved transport rules and discuss the importance of matching (global)
topology with (local) transport rules for the optimal function of networks. The
presented model should be applicable to a wide range of phenomena ranging from
Internet traffic to protein transport along the cytoskeleton in biological
cells.Comment: 27 pages 7 figure
On the Tomography of Networks and Multicast Trees
In this paper we model the tomography of scale free networks by studying the
structure of layers around an arbitrary network node. We find, both
analytically and empirically, that the distance distribution of all nodes from
a specific network node consists of two regimes. The first is characterized by
rapid growth, and the second decays exponentially. We also show that the nodes
degree distribution at each layer is a power law with an exponential cut-off.
We obtain similar results for the layers surrounding the root of multicast
trees cut from such networks, as well as the Internet. All of our results were
obtained both analytically and on empirical Interenet data
Generating Representative ISP Technologies From First-Principles
Understanding and modeling the factors that underlie the growth and evolution of network topologies are basic questions that impact capacity planning, forecasting, and protocol research. Early topology generation work focused on generating network-wide connectivity maps, either at the AS-level or the router-level, typically with an eye towards reproducing abstract properties of observed topologies. But recently, advocates of an alternative "first-principles" approach question the feasibility of realizing representative topologies with simple generative models that do not explicitly incorporate real-world constraints, such as the relative costs of router configurations, into the model. Our work synthesizes these two lines by designing a topology generation mechanism that incorporates first-principles constraints. Our goal is more modest than that of constructing an Internet-wide topology: we aim to generate representative topologies for single ISPs. However, our methods also go well beyond previous work, as we annotate these topologies with representative capacity and latency information. Taking only demand for network services over a given region as input, we propose a natural cost model for building and interconnecting PoPs and formulate the resulting optimization problem faced by an ISP. We devise hill-climbing heuristics for this problem and demonstrate that the solutions we obtain are quantitatively similar to those in measured router-level ISP topologies, with respect to both topological properties and fault-tolerance
- …