79 research outputs found
Distributed Game Theoretic Optimization and Management of Multichannel ALOHA Networks
The problem of distributed rate maximization in multi-channel ALOHA networks
is considered. First, we study the problem of constrained distributed rate
maximization, where user rates are subject to total transmission probability
constraints. We propose a best-response algorithm, where each user updates its
strategy to increase its rate according to the channel state information and
the current channel utilization. We prove the convergence of the algorithm to a
Nash equilibrium in both homogeneous and heterogeneous networks using the
theory of potential games. The performance of the best-response dynamic is
analyzed and compared to a simple transmission scheme, where users transmit
over the channel with the highest collision-free utility. Then, we consider the
case where users are not restricted by transmission probability constraints.
Distributed rate maximization under uncertainty is considered to achieve both
efficiency and fairness among users. We propose a distributed scheme where
users adjust their transmission probability to maximize their rates according
to the current network state, while maintaining the desired load on the
channels. We show that our approach plays an important role in achieving the
Nash bargaining solution among users. Sequential and parallel algorithms are
proposed to achieve the target solution in a distributed manner. The
efficiencies of the algorithms are demonstrated through both theoretical and
simulation results.Comment: 34 pages, 6 figures, accepted for publication in the IEEE/ACM
Transactions on Networking, part of this work was presented at IEEE CAMSAP
201
Active Anomaly Detection in Heterogeneous Processes
An active inference problem of detecting anomalies among heterogeneous
processes is considered. At each time, a subset of processes can be probed. The
objective is to design a sequential probing strategy that dynamically
determines which processes to observe at each time and when to terminate the
search so that the expected detection time is minimized under a constraint on
the probability of misclassifying any process. This problem falls into the
general setting of sequential design of experiments pioneered by Chernoff in
1959, in which a randomized strategy, referred to as the Chernoff test, was
proposed and shown to be asymptotically optimal as the error probability
approaches zero. For the problem considered in this paper, a low-complexity
deterministic test is shown to enjoy the same asymptotic optimality while
offering significantly better performance in the finite regime and faster
convergence to the optimal rate function, especially when the number of
processes is large. The computational complexity of the proposed test is also
of a significantly lower order.Comment: This work has been accepted for publication on IEEE Transactions on
Information Theor
Remote Dipolar Interactions for Objective Density Calibration and Flow Control of Excitonic Fluids
In this paper we suggest a method to observe remote interactions of spatially
separated dipolar quantum fluids, and in particular of dipolar excitons in GaAs
bilayer based devices. The method utilizes the static electric dipole moment of
trapped dipolar fluids to induce a local potential change on spatially
separated test dipoles. We show that such an interaction can be used for a
model- independent, objective fluid density measurements, an outstanding
problem in this field of research, as well as for inter-fluid exciton flow
control and trapping. For a demonstration of the effects on realistic devices,
we use a full two-dimensional hydrodynamical model
- …