120,291 research outputs found
Embedding of global attractors and their dynamics
Using shape theory and the concept of cellularity, we show that if is the
global attractor associated with a dissipative partial differential equation in
a real Hilbert space and the set has finite Assouad dimension ,
then there is an ordinary differential equation in , with , that has unique solutions and reproduces the dynamics on . Moreover,
the dynamical system generated by this new ordinary differential equation has a
global attractor arbitrarily close to , where is a homeomorphism
from into
A Multi-perspective Analysis of Carrier-Grade NAT Deployment
As ISPs face IPv4 address scarcity they increasingly turn to network address
translation (NAT) to accommodate the address needs of their customers.
Recently, ISPs have moved beyond employing NATs only directly at individual
customers and instead begun deploying Carrier-Grade NATs (CGNs) to apply
address translation to many independent and disparate endpoints spanning
physical locations, a phenomenon that so far has received little in the way of
empirical assessment. In this work we present a broad and systematic study of
the deployment and behavior of these middleboxes. We develop a methodology to
detect the existence of hosts behind CGNs by extracting non-routable IP
addresses from peer lists we obtain by crawling the BitTorrent DHT. We
complement this approach with improvements to our Netalyzr troubleshooting
service, enabling us to determine a range of indicators of CGN presence as well
as detailed insights into key properties of CGNs. Combining the two data
sources we illustrate the scope of CGN deployment on today's Internet, and
report on characteristics of commonly deployed CGNs and their effect on end
users
Delay-Optimal User Scheduling and Inter-Cell Interference Management in Cellular Network via Distributive Stochastic Learning
In this paper, we propose a distributive queueaware intra-cell user
scheduling and inter-cell interference (ICI) management control design for a
delay-optimal celluar downlink system with M base stations (BSs), and K users
in each cell. Each BS has K downlink queues for K users respectively with
heterogeneous arrivals and delay requirements. The ICI management control is
adaptive to joint queue state information (QSI) over a slow time scale, while
the user scheduling control is adaptive to both the joint QSI and the joint
channel state information (CSI) over a faster time scale. We show that the
problem can be modeled as an infinite horizon average cost Partially Observed
Markov Decision Problem (POMDP), which is NP-hard in general. By exploiting the
special structure of the problem, we shall derive an equivalent Bellman
equation to solve the POMDP problem. To address the distributive requirement
and the issue of dimensionality and computation complexity, we derive a
distributive online stochastic learning algorithm, which only requires local
QSI and local CSI at each of the M BSs. We show that the proposed learning
algorithm converges almost surely (with probability 1) and has significant gain
compared with various baselines. The proposed solution only has linear
complexity order O(MK)
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