29 research outputs found
Panda: Neighbor Discovery on a Power Harvesting Budget
Object tracking applications are gaining popularity and will soon utilize
Energy Harvesting (EH) low-power nodes that will consume power mostly for
Neighbor Discovery (ND) (i.e., identifying nodes within communication range).
Although ND protocols were developed for sensor networks, the challenges posed
by emerging EH low-power transceivers were not addressed. Therefore, we design
an ND protocol tailored for the characteristics of a representative EH
prototype: the TI eZ430-RF2500-SEH. We present a generalized model of ND
accounting for unique prototype characteristics (i.e., energy costs for
transmission/reception, and transceiver state switching times/costs). Then, we
present the Power Aware Neighbor Discovery Asynchronously (Panda) protocol in
which nodes transition between the sleep, receive, and transmit states. We
analyze \name and select its parameters to maximize the ND rate subject to a
homogeneous power budget. We also present Panda-D, designed for non-homogeneous
EH nodes. We perform extensive testbed evaluations using the prototypes and
study various design tradeoffs. We demonstrate a small difference (less then
2%) between experimental and analytical results, thereby confirming the
modeling assumptions. Moreover, we show that Panda improves the ND rate by up
to 3x compared to related protocols. Finally, we show that Panda-D operates
well under non-homogeneous power harvesting
WiLiTV: A Low-Cost Wireless Framework for Live TV Services
With the evolution of HDTV and Ultra HDTV, the bandwidth requirement for
IP-based TV content is rapidly increasing. Consumers demand uninterrupted
service with a high Quality of Experience (QoE). Service providers are
constantly trying to differentiate themselves by innovating new ways of
distributing content more efficiently with lower cost and higher penetration.
In this work, we propose a cost-efficient wireless framework (WiLiTV) for
delivering live TV services, consisting of a mix of wireless access
technologies (e.g. Satellite, WiFi and LTE overlay links). In the proposed
architecture, live TV content is injected into the network at a few residential
locations using satellite dishes. The content is then further distributed to
other homes using a house-to-house WiFi network or via an overlay LTE network.
Our problem is to construct an optimal TV distribution network with the minimum
number of satellite injection points, while preserving the highest QoE, for
different neighborhood densities. We evaluate the framework using realistic
time-varying demand patterns and a diverse set of home location data. Our study
demonstrates that the architecture requires 75 - 90% fewer satellite injection
points, compared to traditional architectures. Furthermore, we show that most
cost savings can be obtained using simple and practical relay routing
solutions
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Resource Allocation for the Internet of Everything: From Energy Harvesting Tags to Cellular Networks
In the near future, objects equipped with heterogeneous devices such as sensors, actuators, and tags, will be able to interact with each other and cooperate to achieve common goals. These networks are termed the Internet of Things (IoT) and have applications in healthcare, smart buildings, assisted living, manufacturing, supply chain management, and intelligent transportation. The IoT vision is enabled by ubiquitous wireless communications and there are numerous resource allocation challenges to efficiently connect each device to the network. In this thesis, we study wireless resource allocation problems that arise in the IoT, namely in the areas of the energy harvesting tags, termed the Internet of Tags (IoTags), and in cellular networks (mobile and cognitive).
First, we present our experience designing and developing Energy Harvesting Active Networked Tags (EnHANTs). The prototypes harvest indoor light energy using custom organic solar cells, communicate and form multihop networks using ultra-low-power Ultra- Wideband Impulse Radio (UWB-IR) transceivers, and dynamically adapt their communications and networking patterns to the energy harvesting and battery states. Using our custom designed small scale testbed, we evaluate energy-adaptive networking algorithms spanning the protocol stack (link, network, and flow control). Throughout the evaluation of experiments, we highlight numerous phenomena which are typically difficult to capture in simulations and nearly impossible to model in analytical work. We believe that these lessons would be useful for the designers of many different types of energy harvesters and energy harvesting adaptive networks.
Based on the lessons learned from EnHANTs, we present Power Aware Neighbor Discovery Asynchronously (Panda), a Neighbor Discovery (ND) protocol optimized for networks of energy harvesting nodes. To enable object tracking and monitoring applications for IoTags, Panda is designed to efficiently identify nodes which are within wireless communication range of one another. By accounting for numerous hardware constraints which are typically ignored (i.e., energy costs for transmission/reception, and transceiver state switching times/costs), we formulate a power budget to guarantee perpetual ND. Finally, via testbed evaluation utilizing Commercial Off-The-Shelf (COTS) energy harvesting nodes, we demonstrate experimentally that Panda outperforms existing protocols by a factor of 2-3x.
We then consider Proportional Fair (PF) cellular scheduling algorithms for mobile users, These users experience slow-fading wireless channels while traversing roads, train tracks, bus routes, etc. We leverage the predicable mobility on these routes and present the Predictive Finite-horizon PF Scheduling ((PF)2S) Framework. We collect extensive channel measurement results from a 3G network and characterize mobility-induced channel state trends. We show that a user’s channel state is highly reproducible and leverage that to develop a data rate prediction mechanism. Our trace-based simulations of the (PF)2S Framework indicate that the framework can increase the throughput by 15%–55% compared to traditional PF schedulers, while improving fairness.
Finally, we study fragmentation within a probability model of combinatorial structures. Our model does not refer to any particular application. Yet, it is applicable to dynamic spectrum access networks which can be used as the wireless access technology for numerous IoT applications. In dynamic spectrum access networks, users share the wireless resource and compete to transmit and receive data, and accordingly have specific bandwidth and residence-time requirements. We prove that the spectrum tends towards states of complete fragmentation. That is, for every request for j > 1 sub-channels, nearly all size-j requests are allocated j mutually disjoint sub-channels. In a suite of four theorems, we show how this result specializes for certain classes of request-size distributions. We also show that the delays in reaching the inefficient states of complete fragmentation can be surprisingly long. The results of this chapter provide insights into the fragmentation process and, in turn, into those circumstances where defragmentation is worth the cost it incurs
Project-based Learning within a Large-Scale Interdisciplinary Research Effort
The modern engineering landscape increasingly requires a range of skills to
successfully integrate complex systems. Project-based learning is used to help
students build professional skills. However, it is typically applied to small
teams and small efforts. This paper describes an experience in engaging a large
number of students in research projects within a multi-year interdisciplinary
research effort. The projects expose the students to various disciplines in
Computer Science (embedded systems, algorithm design, networking), Electrical
Engineering (circuit design, wireless communications, hardware prototyping),
and Applied Physics (thin-film battery design, solar cell fabrication). While a
student project is usually focused on one discipline area, it requires
interaction with at least two other areas. Over 5 years, 180 semester-long
projects have been completed. The students were a diverse group of high school,
undergraduate, and M.S. Computer Science, Computer Engineering, and Electrical
Engineering students. Some of the approaches that were taken to facilitate
student learning are real-world system development constraints, regular
cross-group meetings, and extensive involvement of Ph.D. students in student
mentorship and knowledge transfer. To assess the approaches, a survey was
conducted among the participating students. The results demonstrate the
effectiveness of the approaches. For example, 70% of the students surveyed
indicated that working on their research project improved their ability to
function on multidisciplinary teams more than coursework, internships, or any
other activity
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The Formation of Collective Silk Balls in the Spider Mite Tetranychus urticae Koch
Tetranychus urticae is a phytophagous mite that forms colonies of several thousand individuals. These mites construct a common web to protect the colony. When plants become overcrowded and food resources become scarce, individuals gather at the plant apex to form a ball composed of mites and their silk threads. This ball is a structure facilitating group dispersal by wind or animal transport. Until now, no quantitative study had been done on this collective form of migration. This is the first attempt to understand the mechanisms that underlie the emergence and growth of the ball. We studied this collective behaviour under laboratory conditions on standardized infested plants. Our results show that the collective displacement and the formation of balls result from a recruitment process: by depositing silk threads on their way up to the plant apex, mites favour and amplify the recruitment toward the balls. A critical threshold (quorum response) in the cumulative flow of mites must be reached to observe the emergence of a ball. At the beginning of the balls formation, mites form an aggregate. After 24 hours, the aggregated mites are trapped inside the silk balls by the complex network of silk threads and finally die, except for recently arrived individuals. The balls are mainly composed of immature stages. Our study reconstructs the key events that lead to the formation of silk balls. They suggest that the interplay between mites' density, plant morphology and plant density lead to different modes of dispersions (individual or collective) and under what conditions populations might adopt a collective strategy rather than one that is individually oriented. Moreover, our results lead to discuss two aspects of the cooperation and altruism: the importance of Allee effects during colonization of new plants and the importance of the size of a founding group
Aetiology and treatment of nightmare disorder: State of the art and future perspectives
This consensus paper provides an overview of the state of the art in research on the aetiology and treatment of nightmare disorder and outlines further perspectives on these issues. It presents a definition of nightmares and nightmare disorder followed by epidemiological findings, and then explains existing models of nightmare aetiology in traumatized and non-traumatized individuals. Chronic nightmares develop through the interaction of elevated hyperarousal and impaired fear extinction. This interplay is assumed to be facilitated by trait affect distress elicited by traumatic experiences, early childhood adversity and trait susceptibility, as well as by elevated thought suppression and potentially sleep-disordered breathing. Accordingly, different treatment options for nightmares focus on their meaning, on the chronic repetition of the nightmare or on maladaptive beliefs. Clinically, knowledge of healthcare providers about nightmare disorder and the delivery of evidence-based interventions in the healthcare system is discussed. Based on these findings, we highlight some future perspectives and potential further developments of nightmare treatments and research into nightmare aetiology
FAMILY CONCEPT FACTORS MEDIATING DYSFUNCTION IN FAMILIES WITH AN ENCOPRETIC CHILD (TYPOLOGY)
The purpose of the present study was to explore family concepts (perceptions) in families with an encopretic child. Clinical observations of parents of encopretic children were used as a base to generate hypotheses concerning individual and shared family perceptions. Thirty parental dyads from families with an encopretic child and thirty control group families with a non-encopretic child participated in the study. Extraneous inter-group variability was controlled by selecting families pariwise to be similar in family size, age, and sex of the main child. Additional limiting characteristics were also imposed on sample selection. Parents were administered a battery of tests including the Family Concept Q-Sort, the Moos Family Environment Scale, a set of Semantic Differential scales, and a questionnaire on child rearing practices. Encopretic group families were found to perceive themselves as less effective and less adaptive in general family life and social activities, and to have a more negative cognitive model of an ideal well-functioning family than control group families. Encopretic group mothers were found to be less satisfied with family integration, and more negative in their evaluation of other family members (especially the encopretic child) than control group mothers. Neither group nor inter-parental differences were found on measures of family congruence, general satisfaction with family life, and major theoretical systems dimensions of family cohesion and communications. Toilet training techniques were found to be largely comparable across groups, except for the tendency of encopretic group parents to utilize physical punishment for soiling accidents. These and other findings were discussed in relation to clinical hypotheses outlined in the literature review. Finally, an obverse factor analysis of encopretic group family Q-Sorts was undertaken and is discussed in terms of its methodological implications for furthering the understanding of the relation between individual conceptualizations of the family and general systems functioning
Three-dimensional structure of murine anti-p-azophenylarsonate Fab 36-71. 1. X-ray crystallography, site-directed mutagenesis, and modeling of the complex with hapten
The structure of the antigen-binding fragment (Fab) of an anti-p-azophenylarsonate monoclonal antibody, 36-71, bearing a major cross-reactive idiotype of A/J mice has been refined to an R factor of 24.8% at a resolution of 1.85 Ă…. The previously solved partial structure of this Fab a resolution of 2.9 Ă…. (Rose et al., 1990) was used as an initial model for refinement against the high-resolution data. The complex with hapten has been modeled by docking the small-molecule crystal structure of phenylarsonic
acid into the structure of the native Fab on the basis of a low-resolution electron density map of the complex. In this model, residue Arg-96 in the light chain and residues Asn-35, Trp-47, and Ser-99 in the heavy chain contact the arsonate moiety of the hapten; an additional bond is found between the arsonate group and a tightly bound water molecule. The phenyl moiety of the hapten packs against two tyrosine side chains at positions 50 and 106 in the heavy chain. Residue Arg-96 in the light chain had been implicated as involved in hapten binding on the basis of previous experiments, and indeed, this residue appears to play a crucial role in this model. Experiments employing site-directed mutagenesis directly support this conclusion. The heavy-chain complementarity-determining regions have novel conformations not previously observed in immunoglobulins except for the recently solved anti-p-azophenylarsonate Fab R19.9 (Lascombe et al., 1989)