62,978 research outputs found
A Tutorial of 802.11 Implementation in NS-2
By analyzing the source codes of ns-2, we discuss the simulated
implementations of wireless channels, network interfaces and mostly the 802.11
MAC protocol in ns-2. We also notice the "bugs" of the 802.11 simulation
compared with the reality, and present an extension to fading channels as well
Applying Stochastic Network Calculus to 802.11 Backlog and Delay Analysis
Stochastic network calculus provides an elegant way to characterize traffic
and service processes. However, little effort has been made on applying it to
multi-access communication systems such as 802.11. In this paper, we take the
first step to apply it to the backlog and delay analysis of an 802.11 wireless
local network. In particular, we address the following questions: In applying
stochastic network calculus, under what situations can we derive stable backlog
and delay bounds? How to derive the backlog and delay bounds of an 802.11
wireless node? And how tight are these bounds when compared with simulations?
To answer these questions, we first derive the general stability condition of a
wireless node (not restricted to 802.11). From this, we give the specific
stability condition of an 802.11 wireless node. Then we derive the backlog and
delay bounds of an 802.11 node based on an existing model of 802.11. We observe
that the derived bounds are loose when compared with ns-2 simulations,
indicating that improvements are needed in the current version of stochastic
network calculus
On Effectiveness of Backlog Bounds Using Stochastic Network Calculus in 802.11
Network calculus is a powerful methodology of characterizing queueing
processes and has wide applications, but few works on applying it to 802.11 by
far. In this paper, we take one of the first steps to analyze the backlog
bounds of an 802.11 wireless LAN using stochastic network calculus. In
particular, we want to address its effectiveness on bounding backlogs. We model
a wireless node as a single server with impairment service based on two
best-known models in stochastic network calculus: Jiang's and Ciucu's.
Interestingly, we find that the two models can derive equivalent stochastic
service curves and backlog bounds in our studied case. We prove that the
network-calculus bounds imply stable backlogs as long as the average rate of
traffic arrival is less than that of service, indicating the theoretical
effectiveness of stochastic network calculus in bounding backlogs. From A.
Kumar's 802.11 model, we derive the concrete stochastic service curve of an
802.11 node and its backlog bounds. We compare the derived bounds with ns-2
simulations and find that the former are very loose and we discuss the reasons.
And we show that the martingale and independent case analysis techniques can
improve the bounds significantly. Our work offers a good reference to applying
stochastic network calculus to practical scenarios
Causal inference in degenerate systems: An impossibility result
Causal relationships among variables are commonly represented via directed
acyclic graphs. There are many methods in the literature to quantify the
strength of arrows in a causal acyclic graph. These methods, however, have
undesirable properties when the causal system represented by a directed acyclic
graph is degenerate. In this paper, we characterize a degenerate causal system
using multiplicity of Markov boundaries. We show that in this case, it is
impossible to find an identifiable quantitative measure of causal effects that
satisfy a set of natural criteria. To supplement the impossibility result, we
also develop algorithms to identify degenerate causal systems from observed
data. Performance of our algorithms is investigated through synthetic data
analysis
A Revised Incremental Conductance MPPT Algorithm for Solar PV Generation Systems
A revised Incremental Conductance (IncCond) maximum power point tracking
(MPPT) algorithm for PV generation systems is proposed in this paper. The
commonly adopted traditional IncCond method uses a constant step size for
voltage adjustment and is difficult to achieve both a good tracking performance
and quick elimination of the oscillations, especially under the dramatic
changes of the environment conditions. For the revised algorithm, the
incremental voltage change step size is adaptively adjusted based on the slope
of the power-voltage (P-V) curve. An accelerating factor and a decelerating
factor are further applied to adjust the voltage step change considering
whether the sign of the P-V curve slope remains the same or not in a subsequent
tracking step. In addition, the upper bound of the maximum voltage step change
is also updated considering the information of sign changes. The revised MPPT
algorithm can quickly track the maximum power points (MPPs) and remove the
oscillation of the actual operation points around the real MPPs. The
effectiveness of the revised algorithm is demonstrated using a simulation
The current density and transport coefficients in the fully ionized plasma with q-distributions in nonextensive statistics
We study the current density and transport coefficients in the fully ionized
plasma with the q-distributions in nonextensive statistics and in strong
magnetic field. By using the generalized Boltzmann transport equation in
nonextensive statistics, we derive the current density and the expressions of
the transport coefficients, including the conductivity, the thermoelectric
coefficient, the Hall coefficient, and the Nernst coefficient. It is shown that
these new transport coefficients has been generalized to the nonequilibrium
complex plasmas with q-distributions in nonextensive statistics, which depend
strongly on the q-parameters and when we take the limit q to 1, they perfectly
return to those for the plasma based on a Maxwellian distribution.Comment: 10 pages,30 references. arXiv admin note: text overlap with
arXiv:1807.0361
Finite-sample Analysis of Greedy-GQ with Linear Function Approximation under Markovian Noise
Greedy-GQ is an off-policy two timescale algorithm for optimal control in
reinforcement learning. This paper develops the first finite-sample analysis
for the Greedy-GQ algorithm with linear function approximation under Markovian
noise. Our finite-sample analysis provides theoretical justification for
choosing stepsizes for this two timescale algorithm for faster convergence in
practice, and suggests a trade-off between the convergence rate and the quality
of the obtained policy. Our paper extends the finite-sample analyses of two
timescale reinforcement learning algorithms from policy evaluation to optimal
control, which is of more practical interest. Specifically, in contrast to
existing finite-sample analyses for two timescale methods, e.g., GTD, GTD2 and
TDC, where their objective functions are convex, the objective function of the
Greedy-GQ algorithm is non-convex. Moreover, the Greedy-GQ algorithm is also
not a linear two-timescale stochastic approximation algorithm. Our techniques
in this paper provide a general framework for finite-sample analysis of
non-convex value-based reinforcement learning algorithms for optimal control.Comment: UAI 202
Spectrally enhancing near-field radiative transfer between gold gratings by exciting magnetic polariton in nanometric vacuum gaps
In the present work, we theoretically demonstrate that near field radiative
transport between one dimensional periodic grating microstructures separated by
nanometer vacuum gaps can be spectrally enhanced by exciting magnetic
polariton. Fluctuational electrodynamics that incorporates scattering matrix
theory with rigorous coupled wave analysis is employed to exactly calculate the
near field radiative flux between two gold gratings. Besides the well known
coupled surface plasmon polaritons, the radiative flux can be also spectrally
enhanced due to magnetic polariton, which is excited in the gap between gold
ridges. The mechanisms of magnetic polariton in the near field radiative
transport are elucidated in detail, while the unusual enhancement cannot be
predicted by either the Derjaguin or effective medium approximations. The
effects of vacuum gap distance and grating geometry parameters between the two
gratings are investigated. The findings will open up a new way to control near
field radiative transfer by magnetic polariton with micro or nanostructured
metamaterials
Revisiting the electronic phase diagram of YBa2Cu3Oy via temperature derivative of in-plane resistivity
We have re-examined the temperature-doping (T-p) phase diagram of YBa2Cu3Oy
(YBCO) to address several issues therein by using the temperature derivative of
in-plane resistivity, d\{rho}ab/dT. For p less than about 0.15, a temperature
Tf has been defined to mark the onset of an upturn in d\{rho}ab/dT at T>Tc,
which, in light of prior studies on another cuprate La2-xSrxCuO4, is attributed
to the onset of superconducting fluctuations in normal state. The Tf exhibits a
doping dependence similar to Tc, and the interval between Tf and Tc is about
5-30 K across the underdoped regime, showing agreement with a variety of other
measurements to probe a restricted temperature range of superconducting
fluctuations. Above Tf, the d\{rho}ab/dT increases linearly as T increases up
to a value denoted as T2, which is about half the T* and falls roughly in
parallel with T* as p rises up to about 0.13, indicating a prominent
T^2-dependent \{rho}ab in this T-p region. The d\{rho}ab/dT helps reveal that,
at Tf<T<T2, the \{rho}ab also involves an insulating-like component for p<0.08,
or a T-linear component for p>0.10-0.11, thereby leaving a narrow window of
doping for \{rho}ab to show a pure T^2 dependence. As T increases further, the
d\{rho}ab/dT reaches a local maximum at a temperature T_R, signifying the known
curvature change (inflection point) in \{rho}ab. With the derivatives, it is
illustrated that, in the vicinity of T_R, the in-plane Hall coefficient R_H and
thermopower Sab of YBCO display curvature changes as well, suggesting a
correlation of the three transport properties. It is also found that the
dSab/dT shows the onset of an upturn at a temperature coinciding with the Tf,
which, backing the identification of Tf with the onset of superconducting
fluctuations, demonstrates further the virtue of using the temperature
derivative to unveil information helpful for the study of high-Tc cuprates.Comment: 22 pages, 13 figure
A Medical Literature Search System for Identifying Effective Treatments in Precision Medicine
The Precision Medicine Initiative states that treatments for a patient should
take into account not only the patient's disease, but his/her specific genetic
variation as well. The vast biomedical literature holds the potential for
physicians to identify effective treatment options for a cancer patient.
However, the complexity and ambiguity of medical terms can result in vocabulary
mismatch between the physician's query and the literature. The physician's
search intent (finding treatments instead of other types of studies) is
difficult to explicitly formulate in a query. Therefore, simple ad hot
retrieval approach will suffer from low recall and precision. In this paper, we
propose a new retrieval system that helps physicians identify effective
treatments in precision medicine. Given a cancer patient with a specific
disease, genetic variation, and demographic information, the system aims to
identify biomedical publications that report effective treatments. We approach
this goal from two directions. First, we expand the original disease and gene
terms using biomedical knowledge bases to improve recall of the initial
retrieval. We then improve precision by promoting treatment-related
publications to the top using a machine learning reranker trained on 2017 Text
Retrieval Conference Precision Medicine (PM) track corpus. Batch evaluation
results on 2018 PM track corpus show that the proposed approach effectively
improves both recall and precision, achieving performance comparable to the top
entries on the leaderboard of 2018 PM track.Comment: 32 page
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