2,368,624 research outputs found
Delay Comparison of Delivery and Coding Policies in Data Clusters
A key function of cloud infrastructure is to store and deliver diverse files,
e.g., scientific datasets, social network information, videos, etc. In such
systems, for the purpose of fast and reliable delivery, files are divided into
chunks, replicated or erasure-coded, and disseminated across servers. It is
neither known in general how delays scale with the size of a request nor how
delays compare under different policies for coding, data dissemination, and
delivery.
Motivated by these questions, we develop and explore a set of evolution
equations as a unified model which captures the above features. These equations
allow for both efficient simulation and mathematical analysis of several
delivery policies under general statistical assumptions. In particular, we
quantify in what sense a workload aware delivery policy performs better than a
workload agnostic policy. Under a dynamic or stochastic setting, the sample
path comparison of these policies does not hold in general. The comparison is
shown to hold under the weaker increasing convex stochastic ordering, still
stronger than the comparison of averages.
This result further allows us to obtain insightful computable performance
bounds. For example, we show that in a system where files are divided into
chunks of equal size, replicated or erasure-coded, and disseminated across
servers at random, the job delays increase sub-logarithmically in the request
size for small and medium-sized files but linearly for large files.Comment: 13 pages, 4 figure
Computational Intelligence Inspired Data Delivery for Vehicle-to-Roadside Communications
We propose a vehicle-to-roadside communication protocol based on distributed clustering where a coalitional game approach is used to stimulate the vehicles to join a cluster, and a fuzzy logic algorithm is employed to generate stable clusters by considering multiple metrics of vehicle velocity, moving pattern, and signal qualities between vehicles. A reinforcement learning algorithm with game theory based reward allocation is employed to guide each vehicle to select the route that can maximize the whole network performance. The protocol is integrated with a multi-hop data delivery virtualization scheme that works on the top of the transport layer and provides high performance for multi-hop end-to-end data transmissions. We conduct realistic computer simulations to show the performance advantage of the protocol over other approaches
Why do women deliver where they had not planned to go? A qualitative study from peri-urban Nairobi Kenya.
BACKGROUND: In urban Kenya, couples face a wide variety of choices for delivery options; however, many women end up delivering in different facilities from those they had intended while pregnant. One potential consequence of this is delivering in facilities that do not meet minimum quality standards and lack the capacity to provide treatment for obstetric and neonatal complications.
METHODS: This study investigated why women in peri-urban Nairobi, Kenya deliver in facilities they had not intended to use. We used 60 in-depth audio-recorded interviews in which mothers shared their experiences 2-6 months after delivery. Descriptive statistics were used to summarize socio-demographic characteristics of participants. Qualitative data were analyzed in three steps i) exploration and generation of initial codes; ii) searching for themes by gathering coded data that addressed specific themes; and iii) defining and naming identified themes. Verbatim excerpts from participants were provided to illustrate study findings. The Health Belief Model was used to shed light on individual-level drivers of delivery location choice.
RESULTS: Findings show a confluence of factors that predispose mothers to delivering in unintended facilities. At the individual level, precipitate labor, financial limitations, onset of pain, complications, changes in birth plans, undisclosed birth plans, travel during pregnancy, fear of health facility providers, misconception of onset of labor, wrong estimate of delivery date, and onset of labor at night, contributed to delivery at unplanned locations. On the supply side, the sudden referral to other facilities, poor services, wrong projection of delivery date, and long distance to chosen delivery facility, were factors in changes in delivery location. Lack of transport discouraged delivery at a chosen health facility. Social influences included others\u27 perspectives on delivery location and lack of aides/escorts.
CONCLUSIONS: Results from this study suggest that manifold factors contribute to the occurrence of women delivering in facilities that they had not intended during pregnancy. Future studies should consider whether these changes in delivery location late in pregnancy contribute to late facility arrival and the use of lower quality facilities. Deliberate counseling during antenatal care regarding birth plans is likely to encourage timely arrival at facilities consistent with women\u27s preferences
D2D Data Offloading in Vehicular Environments with Optimal Delivery Time Selection
Within the framework of a Device-to-Device (D2D) data offloading system for
cellular networks, we propose a Content Delivery Management System (CDMS) in
which the instant for transmitting a content to a requesting node, through a
D2D communication, is selected to minimize the energy consumption required for
transmission. The proposed system is particularly fit to highly dynamic
scenarios, such as vehicular networks, where the network topology changes at a
rate which is comparable with the order of magnitude of the delay tolerance. We
present an analytical framework able to predict the system performance, in
terms of energy consumption, using tools from the theory of point processes,
validating it through simulations, and provide a thorough performance
evaluation of the proposed CDMS, in terms of energy consumption and spectrum
use. Our performance analysis compares the energy consumption and spectrum use
obtained with the proposed scheme with the performance of two benchmark
systems. The first one is a plain classic cellular scheme, the second is a D2D
data offloading scheme (that we proposed in previous works) in which the D2D
transmissions are performed as soon as there is a device with the required
content within the maximum D2D transmission range..
Creating information delivery specifications using linked data
The use of Building Information Management (BIM) has become mainstream in many countries. Exchanging data in open standards like the Industry Foundation Classes (IFC) is seen as the only workable solution for collaboration. To define information needs for collaboration, many organizations are now documenting what kind of data they need for their purposes. Currently practitioners define their requirements often a) in a format that cannot be read by a computer; b) by creating their own definitions that are not shared. This paper proposes a bottom up solution for the definition of new building concepts a property. The authors have created a prototype implementation and will elaborate on the capturing of information specifications in the future
Robust streaming in delay tolerant networks
Delay Tolerant Networks (DTN) do not provide any end to end connectivity guarantee. Thus, transporting data over such networks is a tough challenge as most of Internet applications assume a form of persistent end to end connection. While research in DTN has mainly addressed the problem of routing in various mobility contexts with the aim to improve bundle delay delivery and data delivery ratio, little attention has been paid to applications. This paper investigates the support of streaming-like applications over DTN. We identify how DTN characteristics impact on the overall performances of these applications and present Tetrys, a transport layer mechanism, which enables robust streaming over DTN. Tetrys is based on an
on the fly coding mechanism able to ensure full reliability without retransmission and fast in-order bundle delivery in comparison to classical erasure coding schemes. We evaluate our Tetrys prototype on real DTN connectivity traces captured from the Rollerblading tour in Paris. Simulations show that on average, Tetrys clearly outperforms all other reliability schemes in terms of bundles delivery service
Optimization and synchronization of programmable quantum communication channels
Quantum applications transmit and receive data through quantum and classical
communication channels. Channel capacity, the distance and the photon path
between transmitting and receiving parties and the speed of the computation
links play an essential role in timely synchronization and delivery of
information using classical and quantum channels. In this study, we analyze and
optimize the parameters of the communication channels needed for the quantum
application to successfully operate. We also develop algorithms for
synchronizing data delivery on classical and quantum channels.Comment: 7 pages, 2 figure
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