StationRank: Aggregate dynamics of the Swiss railway

Increasing availability and quality of actual, as opposed to scheduled, open transport data offers new possibilities for capturing the spatiotemporal dynamics of the railway and other networks of social infrastructure. One way to describe such complex phenomena is in terms of stochastic processes. At its core, a stochastic model is domain-agnostic and algorithms discussed here have been successfully used in other applications, including Google's PageRank citation ranking. Our key assumption is that train routes constitute meaningful sequences analogous to sentences of literary text. A corpus of routes is thus susceptible to the same analytic tool-set as a corpus of sentences. With our experiment in Switzerland, we introduce a method for building Markov Chains from aggregated daily streams of railway traffic data. The stationary distributions under normal and perturbed conditions are used to define systemic risk measures with non-evident,valuable information about railway infrastructure

Street Smart in 5G : Vehicular Applications, Communication, and Computing

Recent advances in information technology have revolutionized the automotive industry, paving the way for next-generation smart vehicular mobility. Specifically, vehicles, roadside units, and other road users can collaborate to deliver novel services and applications that leverage, for example, big vehicular data and machine learning. Relatedly, fifth-generation cellular networks (5G) are being developed and deployed for low-latency, high-reliability, and high bandwidth communications. While 5G adjacent technologies such as edge computing allow for data offloading and computation at the edge of the network thus ensuring even lower latency and context-awareness. Overall, these developments provide a rich ecosystem for the evolution of vehicular applications, communications, and computing. Therefore in this work, we aim at providing a comprehensive overview of the state of research on vehicular computing in the emerging age of 5G and big data. In particular, this paper highlights several vehicular applications, investigates their requirements, details the enabling communication technologies and computing paradigms, and studies data analytics pipelines and the integration of these enabling technologies in response to application requirements.Peer reviewe

Interference charecterisation, location and bandwidth estimation in emerging WiFi networks

Wireless LAN technology based on the IEEE 802.11 standard, commonly referred to as WiFi, has been hugely successful not only for the last hop access to the Internet in home, office and hotspot scenarios but also for realising wireless backhaul in mesh networks and for point -to -point long- distance wireless communication. This success can be mainly attributed to two reasons: low cost of 802.11 hardware from reaching economies of scale, and operation in the unlicensed bands of wireless spectrum.The popularity of WiFi, in particular for indoor wireless access at homes and offices, has led to significant amount of research effort looking at the performance issues arising from various factors, including interference, CSMA/CA based MAC protocol used by 802.11 devices, the impact of link and physical layer overheads on application performance, and spatio-temporal channel variations. These factors affect the performance of applications and services that run over WiFi networks. In this thesis, we experimentally investigate the effects of some of the above mentioned factors in the context of emerging WiFi network scenarios such as multi- interface indoor mesh networks, 802.11n -based WiFi networks and WiFi networks with virtual access points (VAPs). More specifically, this thesis comprises of four experimental characterisation studies: (i) measure prevalence and severity of co- channel interference in urban WiFi deployments; (ii) characterise interference in multi- interface indoor mesh networks; (iii) study the effect of spatio-temporal channel variations, VAPs and multi -band operation on WiFi fingerprinting based location estimation; and (iv) study the effects of newly introduced features in 802.11n like frame aggregation (FA) on available bandwidth estimation.With growing density of WiFi deployments especially in urban areas, co- channel interference becomes a major factor that adversely affects network performance. To characterise the nature of this phenomena at a city scale, we propose using a new measurement methodology called mobile crowdsensing. The idea is to leverage commodity smartphones and the natural mobility of people to characterise urban WiFi co- channel interference. Specifically, we report measurement results obtained for Edinburgh, a representative European city, on detecting the presence of deployed WiFi APs via the mobile crowdsensing approach. These show that few channels in 2.4GHz are heavily used and there is hardly any activity in the 5GHz band even though relatively it has a greater number of available channels. Spatial analysis of spectrum usage reveals that co- channel interference among nearby APs operating in the same channel can be a serious problem with around 10 APs contending with each other in many locations. We find that the characteristics of WiFi deployments at city -scale are similar to those of WiFi deployments in public spaces of different indoor environments. We validate our approach in comparison with wardriving, and also show that our findings generally match with previous studies based on other measurement approaches. As an application of the mobile crowdsensing based urban WiFi monitoring, we outline a cloud based WiFi router configuration service for better interference management with global awareness in urban areas.For mesh networks, the use of multiple radio interfaces is widely seen as a practical way to achieve high end -to -end network performance and better utilisation of available spectrum. However this gives rise to another type of interference (referred to as coexistence interference) due to co- location of multiple radio interfaces. We show that such interference can be so severe that it prevents concurrent successful operation of collocated interfaces even when they use channels from widely different frequency bands. We propose the use of antenna polarisation to mitigate such interference and experimentally study its benefits in both multi -band and single -band configurations. In particular, we show that using differently polarised antennas on a multi -radio platform can be a helpful counteracting mechanism for alleviating receiver blocking and adjacent channel interference phenomena that underlie multi -radio coexistence interference. We also validate observations about adjacent channel interference from previous studies via direct and microscopic observation of MAC behaviour.Location is an indispensable information for navigation and sensing applications. The rapidly growing adoption of smartphones has resulted in a plethora of mobile applications that rely on position information (e.g., shopping apps that use user position information to recommend products to users and help them to find what they want in the store). WiFi fingerprinting is a popular and well studied approach for indoor location estimation that leverages the existing WiFi infrastructure and works based on the difference in strengths of the received AP signals at different locations. However, understanding the impact of WiFi network deployment aspects such as multi -band APs and VAPs has not received much attention in the literature. We first examine the impact of various aspects underlying a WiFi fingerprinting system. Specifically, we investigate different definitions for fingerprinting and location estimation algorithms across different indoor environments ranging from a multi- storey office building to shopping centres of different sizes. Our results show that the fingerprint definition is as important as the choice of location estimation algorithm and there is no single combination of these two that works across all environments or even all floors of a given environment. We then consider the effect of WiFi frequency bands (e.g., 2.4GHz and 5GHz) and the presence of virtual access points (VAPs) on location accuracy with WiFi fingerprinting. Our results demonstrate that lower co- channel interference in the 5GHz band yields more accurate location estimation. We show that the inclusion of VAPs has a significant impact on the location accuracy of WiFi fingerprinting systems; we analyse the potential reasons to explain the findings.End -to -end available bandwidth estimation (ABE) has a wide range of uses, from adaptive application content delivery, transport-level transmission rate adaptation and admission control to traffic engineering and peer node selection in peer -to- peer /overlay networks [ 1, 2]. Given its importance, it has been received much research attention in both wired data networks and legacy WiFi networks (based on 802.11 a/b /g standards), resulting in different ABE techniques and tools proposed to optimise different criteria and suit different scenarios. However, effects of new MAC/PHY layer enhancements in new and next generation WiFi networks (based on 802.11n and 802.11ac standards) have not been studied yet. We experimentally find that among different new features like frame aggregation, channel bonding and MIMO modes (spacial division multiplexing), frame aggregation has the most harmful effect as it has direct effect on ABE by distorting the measurement probing traffic pattern commonly used to estimate available bandwidth. Frame aggregation is also specified in both 802.11n and 802.1 lac standards as a mandatory feature to be supported. We study the effect of enabling frame aggregation, for the first time, on the performance of the ABE using an indoor 802.11n wireless testbed. The analysis of results obtained using three tools - representing two main Probe Rate Model (PRM) and Probe Gap Model (PGM) based approaches for ABE - led us to come up with the two key principles of jumbo probes and having longer measurement probe train sizes to counter the effects of aggregating frames on the performance of ABE tools. Then, we develop a new tool, WBest+ that is aware of the underlying frame aggregation by incorporating these principles. The experimental evaluation of WBest+ shows more accurate ABE in the presence of frame aggregation.Overall, the contributions of this thesis fall in three categories - experimental characterisation, measurement techniques and mitigation/solution approaches for performance problems in emerging WiFi network scenarios. The influence of various factors mentioned above are all studied via experimental evaluation in a testbed or real - world setting. Specifically, co- existence interference characterisation and evaluation of available bandwidth techniques are done using indoor testbeds, whereas characterisation of urban WiFi networks and WiFi fingerprinting based location estimation are carried out in real environments. New measurement approaches are also introduced to aid better experimental evaluation or proposed as new measurement tools. These include mobile crowdsensing based WiFi monitoring; MAC/PHY layer monitoring of co- existence interference; and WBest+ tool for available bandwidth estimation. Finally, new mitigation approaches are proposed to address challenges and problems identified throughout the characterisation studies. These include: a proposal for crowd - based interference management in large scale uncoordinated WiFi networks; exploiting antenna polarisation diversity to remedy the effects of co- existence interference in multi -interface platforms; taking advantage of VAPs and multi -band operation for better location estimation; and introducing the jumbo frame concept and longer probe train sizes to improve performance of ABE tools in next generation WiFi networks

Spatial and Temporal Structure of a Mesocarnivore Guild in Midwestern North America

Carnivore guilds play a vital role in ecological communities by cascading trophic effects, energy and nutrient transfer, and stabilizing or destabilizing food webs. Consequently, the structure of carnivore guilds can be critical to ecosystem patterns. Body size is a crucial influence on intraguild interactions, because it affects access to prey resources, effectiveness in scramble competition, and vulnerability to intraguild predation. Coyotes (Canis latrans), bobcats (Lynx rufus), gray foxes (Urocyon cinereoargenteus), raccoons (Procyon lotor), red foxes (Vulpes vulpes), and striped skunks (Mephitis mephitis) occur sympatrically throughout much of North America and overlap in resource use, indicating potential for interspecific interactions. Although much is known about the autecology of the individual species separately, little is known about factors that facilitate coexistence and how interactions within this guild influence distribution, habitat use, and temporal activity of the smaller carnivores. To assess how habitat autecology and interspecific interactions affect the structure of this widespread carnivore guild, we conducted a large-scale, non-invasive carnivore survey using an occupancy modeling framework. We deployed remote cameras during 3-week surveys to detect carnivores at 1,118 camera locations in 357 2.6-km2 sections (3–4 cameras/section composing a cluster) in the 16 southernmost counties of Illinois (16,058 km2) during January–April, 2008–2010. We characterized microhabitat at each camera location and landscape-level habitat features for each camera-cluster. In a multi-stage approach, we used information-theoretic methods to evaluate competing models for detection, species-specific habitat occupancy, multi-species co-occupancy, and multi-season (colonization and extinction) occupancy dynamics. We developed occupancy models for each species to represent hypothesized effects of anthropogenic features, prey availability, landscape complexity, and vegetative land cover. We quantified temporal activity patterns of each carnivore species based on their frequency of appearance in photographs. Further, we assessed whether smaller carnivores shifted their diel activity patterns in response to the presence of potential competitors. Of the 102,711 photographs of endothermic animals, we recorded photographs of bobcats (n = 412 photographs), coyotes (n = 1,397), gray foxes (n = 546), raccoons (n = 40,029), red foxes (n = 149), and striped skunks (n = 2,467). Bobcats were active primarily during crepuscular periods, and their activity was reduced with precipitation and higher temperatures. The probability of detecting bobcats decreased after a bobcat photograph was recorded, suggesting avoidance of remote cameras after the first encounter. Across southern Illinois, bobcat occupancy at the camera-location and camera-cluster scale (local = 0.24 ± 0.04, camera-cluster cluster = 0.75 ± 0.06) was negatively influenced by anthropogenic features and infrastructure. Bobcats had high rates of colonization (= 0.86) and low rates of extinction (= 0.07), suggesting an expanding population, but agricultural land was less likely to be colonized. Nearly all camera clusters were occupied by coyotes (cluster = 0.95 ± 0.03). At the local scale, coyote occupancy (local = 0.58 ± 0.03) was higher in hardwood forest stands with open understories than in other areas. Compared to coyotes, gray foxes occupied a smaller portion of the study area (local = 0.13 ± 0.01, cluster = 0.29 ± 0.03) at all scales. At the scale of the camera-cluster, gray fox occupancy was highest in fragmented areas with high proportions of forest, and positively related to anthropogenic features within 100% home-range buffers. Red foxes occupied a similar proportion of the study area as gray foxes (local = 0.12 ± 0.02, cluster = 0.26 ± 0.04) but were more closely associated with anthropogenic features. Only anthropogenic feature models made up the 90% confidence set at all scales of analysis for red foxes. Extinction probabilities at the scale of the camera-cluster were higher for both gray foxes (= 0.57) and red foxes (= 0.35) than their colonization rates (gray fox = 0.16, red fox = 0.06), suggesting both species may be declining in southern Illinois. Striped skunks occupied a large portion of the study area (local = 0.47 ± 0.01, cluster = 0.79 ± 0.03) and were associated primarily with anthropogenic features. Raccoons were essentially ubiquitous within the study area, being photographed in 99% of camera clusters. We observed little evidence for spatial partitioning based on interspecific interactions, with the exception of the gray fox-coyote pairs, and found that habitat preferences were more important in structuring the carnivore community. Habitat had a stronger influence on the occupancy of foxes than did the presence of bobcats. However, the level of red fox activity was negatively correlated with bobcat activity at a camera cluster. Gray fox occupancy and the number of detections within occupied sites were reduced in camera-clusters occupied by coyotes but not bobcat occupancy. Overall, gray fox occupancy was highest at camera locations with fewer hardwood and more conifer trees. However, gray foxes were more likely to occupy camera locations in hardwood stands than conifer stands if coyotes were also present indicating that hardwood stands may enhance gray fox-coyote coexistence. The 2 fox species appeared to co-occur with each other at the local scale more frequently than expected based on their individual selection of habitat. Similarly, occupancy of camera-location by red foxes was higher when coyotes were present. These positive spatial associations among canids may be a response to locally high prey abundance or unmeasured habitat variables. Activity levels of raccoons, bobcats, and coyotes were all positively correlated. Overall, our co-occurrence and activity models indicate competitor-driven adjustments in space use among members of a carnivore community might be the exception rather than the norm. Nevertheless, although our results indicate that gray foxes and red foxes currently coexist with bobcats and coyotes, their distribution appears to be contracting on our study area. Coexistence of foxes with larger carnivores may be enhanced by temporal partitioning of activity and by habitat features that reduce vulnerability of intraguild predation. For instance, hardwood stands may contain trees with structure that enhances tree-climbing by gray foxes, a behavior that probably facilitates coexistence with coyotes. Efforts to enhance gray fox populations in this region would likely benefit from increasing the amount of mature oak-hickory forest. Additionally, the varying results from different scales of analyses underscore the importance of considering multiple spatial scales in carnivore community studies