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

Statistical Analysis of Bus Networks in India

Through the past decade the field of network science has established itself as a common ground for the cross-fertilization of exciting inter-disciplinary studies which has motivated researchers to model almost every physical system as an interacting network consisting of nodes and links. Although public transport networks such as airline and railway networks have been extensively studied, the status of bus networks still remains in obscurity. In developing countries like India, where bus networks play an important role in day-to-day commutation, it is of significant interest to analyze its topological structure and answer some of the basic questions on its evolution, growth, robustness and resiliency. In this paper, we model the bus networks of major Indian cities as graphs in \textit{L}-space, and evaluate their various statistical properties using concepts from network science. Our analysis reveals a wide spectrum of network topology with the common underlying feature of small-world property. We observe that the networks although, robust and resilient to random attacks are particularly degree-sensitive. Unlike real-world networks, like Internet, WWW and airline, which are virtual, bus networks are physically constrained. The presence of various geographical and economic constraints allow these networks to evolve over time. Our findings therefore, throw light on the evolution of such geographically and socio-economically constrained networks which will help us in designing more efficient networks in the future.Comment: Submitted to PLOS ON

Whole-genome sequencing for national surveillance of Shiga toxin–producing Escherichia coli O157

Background. National surveillance of gastrointestinal pathogens, such as Shiga toxin–producing Escherichia coli O157 (STEC O157), is key to rapidly identifying linked cases in the distributed food network to facilitate public health interventions. In this study, we used whole-genome sequencing (WGS) as a tool to inform national surveillance of STEC O157 in terms of identifying linked cases and clusters and guiding epidemiological investigation. Methods. We retrospectively analyzed 334 isolates randomly sampled from 1002 strains of STEC O157 received by the Gastrointestinal Bacteria Reference Unit at Public Health England, Colindale, in 2012. The genetic distance between each isolate, as estimated by WGS, was calculated and phylogenetic methods were used to place strains in an evolutionary context. Results. Estimates of linked clusters representing STEC O157 outbreaks in England and Wales increased by 2-fold when WGS was used instead of traditional typing techniques. The previously unidentified clusters were often widely geographically distributed and small in size. Phylogenetic analysis facilitated identification of temporally distinct cases sharing common exposures and delineating those that shared epidemiological and temporal links. Comparison with multi locus variable number tandem repeat analysis (MLVA) showed that although MLVA is as sensitive as WGS, WGS provides a more timely resolution to outbreak clustering. Conclusions. WGS has come of age as a molecular typing tool to inform national surveillance of STEC O157; it can be used in real time to provide the highest strain-level resolution for outbreak investigation. WGS allows linked cases to be identified with unprecedented specificity and sensitivity that will facilitate targeted and appropriate public health investigations

Employing geographical principles for sampling in state of the art dialectological projects

The aims of this paper are twofold: First, we locate the most effective human geographical methods for sampling across space in large-scale dialectological projects. We propose two geographical concepts as a basis for sampling decisions: Geo-demographic classification, which is a multidimensional method used for the socio-economic grouping of areas. We also develop an updated version of functional regions that can be used in sociolinguistic research. We then report on the results of a pilot project that applies these models to collect data regarding the acceptability of vernacular morpho-syntactic forms in the North-East of England. Following the method of natural breaks advocated for dialectology by Horvath and Horvath (2002), we interpret breaks in the probabilistic patterns as areas of dialect transitions. This study contributes to the debate about the role and limitations of spatiality in linguistic analysis. It intends to broaden our knowledge about the interfaces between human geography and dialectology

Performance evaluation of MPLS-enabled communications infrastructure for wide area monitoring systems

In order to obtain the transient power system measurement information, Wide Area Monitoring Systems (WAMS) should be able to collect Phasor Measurement Unit (PMU) data in a timely manner. Therefore along with the continual deployment of PMUs in Great Britain (GB) transmission system substations, a high performance communications infrastructure is becoming essential with regard to the establishment of reliable WAMS. This paper focuses mainly on evaluating the performance of the real-time WAMS communication infrastructure when Multi-Protocol Label Switching (MPLS) capability is added to a conventional IP network. Furthermore, PMU communications from geographically distributed substations to a Phasor Data Concentrator (PDC) are investigated over different transport protocols. Using OPNET Modeler, simulations are performed based on the existing WAMS infrastructure as installed on the GB transmission system. The simulation results are analyzed in detail in order to fully determine the different characteristics of communication delays between PMUs and PDC

Population genetic data for 17 Y STR markers from Benghazi (East Libya)

The seventeen Y-STR loci included in the AmpF‘STR1 YfilerTM PCR Amplification kit (DYS19, DYS389I,DYS389II, DYS390, DYS391, DYS392, DYS393, DYS385a/b, DYS438, DYS439, DYS437, DYS448, DYS458,DYS456, DYS635, and Y-GATA-H4) were used to type a sample population of 238 males from eastern Libya (Benghazi region). Of 238 observed haplotypes, 214 were unique (90%) and 24 (10%) were found more than once. The 17 loci gave a discriminating power of 0.999. DYS458 showed the highest diversity as a single-locus marker (0.73). Allelic frequencies and gene diversities for each Y-STR locus were determined. The high haplotype diversity and discrimination capacity (0.996) demonstrate the utility of these loci for human identification in forensic applications. Comparative analysis with Y-STR datasets of relevant populations and submission of the haplotypes to the Y-STR Haplotype Reference Database (YHRD) was undertaken

HypTrails: A Bayesian Approach for Comparing Hypotheses About Human Trails on the Web

When users interact with the Web today, they leave sequential digital trails on a massive scale. Examples of such human trails include Web navigation, sequences of online restaurant reviews, or online music play lists. Understanding the factors that drive the production of these trails can be useful for e.g., improving underlying network structures, predicting user clicks or enhancing recommendations. In this work, we present a general approach called HypTrails for comparing a set of hypotheses about human trails on the Web, where hypotheses represent beliefs about transitions between states. Our approach utilizes Markov chain models with Bayesian inference. The main idea is to incorporate hypotheses as informative Dirichlet priors and to leverage the sensitivity of Bayes factors on the prior for comparing hypotheses with each other. For eliciting Dirichlet priors from hypotheses, we present an adaption of the so-called (trial) roulette method. We demonstrate the general mechanics and applicability of HypTrails by performing experiments with (i) synthetic trails for which we control the mechanisms that have produced them and (ii) empirical trails stemming from different domains including website navigation, business reviews and online music played. Our work expands the repertoire of methods available for studying human trails on the Web.Comment: Published in the proceedings of WWW'1

On the complexity of routing in wireless multihop network

Wireless backbone networks represent an attractive alternative to wired networks in situations where cost, speed of deployment, and flexibility in network design are important. In typical configurations, users connect to wireless routers of the backbone network, which then redirect the traffic to one of the existing network gateways. To improve the network performance, wireless backbone routers redirect their traffic to the network gateways so as to maximize amount of traffic that can be sup- ported by the network. In this paper, we prove that this problem is NP-hard as a result of the wireless interference that is created between geographically close transmission links. We consequently design and investigate the performance of interference-aware algorithms suitable for multi-channel environments against more traditional routing approaches. We evaluate their performance in simulated environments based on data taken from existing networks, and show that interference-based heuristics exhibit advantageous performance in non-uniform deployment

The complex relationship between weather and dengue virus transmission in Thailand.

Using a novel analytical approach, weather dynamics and seasonal dengue virus transmission cycles were profiled for each Thailand province, 1983-2001, using monthly assessments of cases, temperature, humidity, and rainfall. We observed systematic differences in the structure of seasonal transmission cycles of different magnitude, the role of weather in regulating seasonal cycles, necessary versus optimal transmission "weather-space," basis of large epidemics, and predictive indicators that estimate risk. Larger epidemics begin earlier, develop faster, and are predicted at Onset change-point when case counts are low. Temperature defines a viable range for transmission; humidity amplifies the potential within that range. This duality is central to transmission. Eighty percent of 1.2 million severe dengue cases occurred when mean temperature was 27-29.5°C and mean humidity was > 75%. Interventions are most effective when applied early. Most cases occur near Peak, yet small reductions at Onset can substantially reduce epidemic magnitude. Monitoring the Quiet-Phase is fundamental in effectively targeting interventions pre-emptively