On the Geographic Location of Internet Resources

One relatively unexplored question about the Internet's physical structure concerns the geographical location of its components: routers, links and autonomous systems (ASes). We study this question using two large inventories of Internet routers and links, collected by different methods and about two years apart. We first map each router to its geographical location using two different state-of-the-art tools. We then study the relationship between router location and population density; between geographic distance and link density; and between the size and geographic extent of ASes. Our findings are consistent across the two datasets and both mapping methods. First, as expected, router density per person varies widely over different economic regions; however, in economically homogeneous regions, router density shows a strong superlinear relationship to population density. Second, the probability that two routers are directly connected is strongly dependent on distance; our data is consistent with a model in which a majority (up to 75-95%) of link formation is based on geographical distance (as in the Waxman topology generation method). Finally, we find that ASes show high variability in geographic size, which is correlated with other measures of AS size (degree and number of interfaces). Among small to medium ASes, ASes show wide variability in their geographic dispersal; however, all ASes exceeding a certain threshold in size are maximally dispersed geographically. These findings have many implications for the next generation of topology generators, which we envisage as producing router-level graphs annotated with attributes such as link latencies, AS identifiers and geographical locations.National Science Foundation (CCR-9706685, ANI-9986397, ANI-0095988, CAREER ANI-0093296); DARPA; CAID

Effect of hole doping on the London penetration depth in Bi2.15Sr1.85CaCu2O8+δ and Bi2.1Sr1.9Ca0.85Y0.15Cu2O8+δ

We report measurements of ac susceptibility and hence the in-plane London penetration depth on the same samples of Bi2.15Sr1.85CaCu2O8+δ and Bi2.1Sr1.9Ca0.85Y0.15Cu2O8+δ for many values of the hole concentration (p). These support the scenario in which the pseudogap weakens the superconducting response only for p≲0.19.We acknowledge funding from the EPSRC (U.K.), for the experimental facilities in Cambridge, and further financial support from The Royal Society, EURYI, and MEXT-CT-2006-039047. W.A. was supported by the Development and Promotion of Science and Technology Talents Project (D.P.S.T.), Thailand

Electronic structure in underdoped cuprates due to the emergence of a pseudogap

The phenomenological Green's function developed in the works of Yang, Rice and Zhang has been very successful in understanding many of the anomalous superconducting properties of the deeply underdoped cuprates. It is based on considerations of the resonating valence bond spin liquid approximation and is designed to describe the underdoped regime of the cuprates. Here we emphasize the region of doping, $x$, just below the quantum critical point at which the pseudogap develops. In addition to Luttinger hole pockets centered around the nodal direction, there are electron pockets near the antinodes which are connected to the hole pockets by gapped bridging contours. We determine the contours of nearest approach as would be measured in angular resolved photoemission experiments and emphasize signatures of the Fermi surface reconstruction from the large Fermi contour of Fermi liquid theory (which contains $1+x$ hole states) to the Luttinger pocket (which contains $x$ hole states). We find that the quasiparticle effective mass renormalization increases strongly towards the edge of the Luttinger pockets beyond which it diverges.Comment: 11 pages, 9 figure

Sampling Biases in IP Topology Measurements

Considerable attention has been focused on the properties of graphs derived from Internet measurements. Router-level topologies collected via traceroute-like methods have led some to conclude that the router graph of the Internet is well modeled as a power-law random graph. In such a graph, the degree distribution of nodes follows a distribution with a power-law tail

On the geographic location of internet resources

One relatively unexplored question about the Internet's physical structure concerns the geographical location of its components: routers, links and autonomous systems (ASes). We study this question using two large inventories of Internet routers and links, collected by different methods and about two years apart. We first map each router to its geographical location using two different state-of-the-art tools. We then study the relationship between router location and population density; between geographic distance and link density; and between the size and geographic extent of ASes. Our findings are consistent across..

On the Geographic Location of Internet Resources

Anukool Lakhina John W. Byers Mark Crovella Ibrahim Matta Department of Computer Science Boston University fanukool, byers, crovella, [email protected] I