6,380 research outputs found
Fundamentals of Inter-cell Overhead Signaling in Heterogeneous Cellular Networks
Heterogeneous base stations (e.g. picocells, microcells, femtocells and
distributed antennas) will become increasingly essential for cellular network
capacity and coverage. Up until now, little basic research has been done on the
fundamentals of managing so much infrastructure -- much of it unplanned --
together with the carefully planned macro-cellular network. Inter-cell
coordination is in principle an effective way of ensuring different
infrastructure components behave in a way that increases, rather than
decreases, the key quality of service (QoS) metrics. The success of such
coordination depends heavily on how the overhead is shared, and the rate and
delay of the overhead sharing. We develop a novel framework to quantify
overhead signaling for inter-cell coordination, which is usually ignored in
traditional 1-tier networks, and assumes even more importance in multi-tier
heterogeneous cellular networks (HCNs). We derive the overhead quality contour
for general K-tier HCNs -- the achievable set of overhead packet rate, size,
delay and outage probability -- in closed-form expressions or computable
integrals under general assumptions on overhead arrivals and different overhead
signaling methods (backhaul and/or wireless). The overhead quality contour is
further simplified for two widely used models of overhead arrivals: Poisson and
deterministic arrival process. This framework can be used in the design and
evaluation of any inter-cell coordination scheme. It also provides design
insights on backhaul and wireless overhead channels to handle specific overhead
signaling requirements.Comment: 21 pages, 9 figure
On the tailoring of CAST-32A certification guidance to real COTS multicore architectures
The use of Commercial Off-The-Shelf (COTS) multicores in real-time industry is on the rise due to multicores' potential performance increase and energy reduction. Yet, the unpredictable impact on timing of contention in shared hardware resources challenges certification. Furthermore, most safety certification standards target single-core architectures and do not provide explicit guidance for multicore processors. Recently, however, CAST-32A has been presented providing guidance for software planning, development and verification in multicores. In this paper, from a theoretical level, we provide a detailed review of CAST-32A objectives and the difficulty of reaching them under current COTS multicore design trends; at experimental level, we assess the difficulties of the application of CAST-32A to a real multicore processor, the NXP P4080.This work has been partially supported by the Spanish Ministry of Economy and Competitiveness (MINECO) under grant
TIN2015-65316-P and the HiPEAC Network of Excellence.
Jaume Abella has been partially supported by the MINECO under Ramon y Cajal grant RYC-2013-14717.Peer ReviewedPostprint (author's final draft
A mask-based approach for the geometric calibration of thermal-infrared cameras
Accurate and efficient thermal-infrared (IR) camera calibration is important for advancing computer vision research within the thermal modality. This paper presents an approach for geometrically calibrating individual and multiple cameras in both the thermal and visible modalities. The proposed technique can be used to correct for lens distortion and to simultaneously reference both visible and thermal-IR cameras to a single coordinate frame. The most popular existing approach for the geometric calibration of thermal cameras uses a printed chessboard heated by a flood lamp and is comparatively inaccurate and difficult to execute. Additionally, software toolkits provided for calibration either are unsuitable for this task or require substantial manual intervention. A new geometric mask with high thermal contrast and not requiring a flood lamp is presented as an alternative calibration pattern. Calibration points on the pattern are then accurately located using a clustering-based algorithm which utilizes the maximally stable extremal region detector. This algorithm is integrated into an automatic end-to-end system for calibrating single or multiple cameras. The evaluation shows that using the proposed mask achieves a mean reprojection error up to 78% lower than that using a heated chessboard. The effectiveness of the approach is further demonstrated by using it to calibrate two multiple-camera multiple-modality setups. Source code and binaries for the developed software are provided on the project Web site
Modular System for Shelves and Coasts (MOSSCO v1.0) - a flexible and multi-component framework for coupled coastal ocean ecosystem modelling
Shelf and coastal sea processes extend from the atmosphere through the water
column and into the sea bed. These processes are driven by physical, chemical,
and biological interactions at local scales, and they are influenced by
transport and cross strong spatial gradients. The linkages between domains and
many different processes are not adequately described in current model systems.
Their limited integration level in part reflects lacking modularity and
flexibility; this shortcoming hinders the exchange of data and model components
and has historically imposed supremacy of specific physical driver models. We
here present the Modular System for Shelves and Coasts (MOSSCO,
http://www.mossco.de), a novel domain and process coupling system
tailored---but not limited--- to the coupling challenges of and applications in
the coastal ocean. MOSSCO builds on the existing coupling technology Earth
System Modeling Framework and on the Framework for Aquatic Biogeochemical
Models, thereby creating a unique level of modularity in both domain and
process coupling; the new framework adds rich metadata, flexible scheduling,
configurations that allow several tens of models to be coupled, and tested
setups for coastal coupled applications. That way, MOSSCO addresses the
technology needs of a growing marine coastal Earth System community that
encompasses very different disciplines, numerical tools, and research
questions.Comment: 30 pages, 6 figures, submitted to Geoscientific Model Development
Discussion
Flatness-based Deformation Control of an Euler-Bernoulli Beam with In-domain Actuation
This paper addresses the problem of deformation control of an Euler-Bernoulli
beam with in-domain actuation. The proposed control scheme consists in first
relating the system model described by an inhomogeneous partial differential
equation to a target system under a standard boundary control form. Then, a
combination of closed-loop feedback control and flatness-based motion planning
is used for stabilizing the closed-loop system around reference trajectories.
The validity of the proposed method is assessed through well-posedness and
stability analysis of the considered systems. The performance of the developed
control scheme is demonstrated through numerical simulations of a
representative micro-beam.Comment: Preprint of an original research wor
Allocation of Heterogeneous Resources of an IoT Device to Flexible Services
Internet of Things (IoT) devices can be equipped with multiple heterogeneous
network interfaces. An overwhelmingly large amount of services may demand some
or all of these interfaces' available resources. Herein, we present a precise
mathematical formulation of assigning services to interfaces with heterogeneous
resources in one or more rounds. For reasonable instance sizes, the presented
formulation produces optimal solutions for this computationally hard problem.
We prove the NP-Completeness of the problem and develop two algorithms to
approximate the optimal solution for big instance sizes. The first algorithm
allocates the most demanding service requirements first, considering the
average cost of interfaces resources. The second one calculates the demanding
resource shares and allocates the most demanding of them first by choosing
randomly among equally demanding shares. Finally, we provide simulation results
giving insight into services splitting over different interfaces for both
cases.Comment: IEEE Internet of Things Journa
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