@conference {
	title = {Observing a Linear Process over Analog Erasure Channels using Multiple Sensors: Necessary and Sufficient Conditions for Mean-square Stability},
	author = {Gupta, Vijay., Martins, Nuno C., Baras, John S.},
	year = {2007},
	month = {12/2007},
	abstract = {Consider a discrete-time linear time-invariant process being observed by two sensors, which are connected to an observer via links that can be modeled as erasure channels. If a link transmits successfully then a finite-dimensional vector of real numbers is conveyed from the sensor to the controller. If an erasure event occurs, then any information conveyed over the link is lost. This paper addresses the problem of designing the maps that specify the processing at the sensors and the observer to calculate the minimum mean square error estimate of the state of the process. We derive necessary and sufficient conditions for the existence of maps such that the estimate error is bounded in the second moment sense.},
	address = {New Orleans, Louisiana},
	booktitle = {46th IEEE Conference on Decision and Control},
	pages = {pp. 659-664}
}
@conference {
	title = {Sensor Scheduling using Smart Sensors},
	author = {Hovareshti, Pedram., Gupta, Vijay., Baras, John S.},
	year = {2007},
	month = {12/2007},
	abstract = {The sensor selection problem arises when multiple sensors are jointly trying to estimate a process but only a subset of them can take and/or use measurements at any time step. In a networked estimation situation, sensors are typically equipped with some memory and processing capabilities. We illustrate that utilization of these capabilities can lead to significant performance gains in the sensor selection problem for improved estimation performance. Further, it also leads to significant pruning of the search tree that yields the optimum sensor schedule. We also present a periodicity result for the case where the decision is whether the sensor should transmit or not.},
	address = {New Orleans, Louisiana},
	booktitle = {46th IEEE Conference on Decision and Control},
	pages = {pp. 494-499}
}
@conference {
	title = {Convergence Results for Ant Routing Algorithms via Stochastic Approximation and Optimization},
	author = {Purkayastha, Punyaslok., Baras, John S.},
	year = {2007},
	month = {12/2007},
	abstract = {"Ant algorithms" have been proposed to solve a variety of problems arising in optimization and distributed control. They form a subset of the larger class of {\textquotedblleft}Swarm Intelligence{\textquotedblright} algorithms. The central idea is that a {\textquoteleft}swarm{\textquoteright} of relatively simple agents can interact through simple mechanisms and collectively solve complex problems. Instances that exemplify the above idea abound in nature. The abilities of ant colonies to collectively accomplish complex tasks have served as sources of inspiration for the design of {\textquotedblleft}Ant algorithms{\textquotedblright}. Examples of {\textquotedblleft}Ant algorithms{\textquotedblright} are {\textquotedblleft}Ant Routing{\textquotedblright} algorithms that have been proposed for communication networks. We analyze in this paper an Ant-Based Routing Algorithm for packet-switched wireline networks. The algorithm is an attractive multiple path probabilistic routing scheme, that is fully adaptive and distributed. Using methods from adaptive algorithms and stochastic approximation, we show that the evolution of the link delay estimates can be closely tracked by a deterministic ODE system. A study of the equilibrium points of the ODE then gives us the equilibrium behavior of the routing algorithm, in particular, the equilibrium routing probabilities, and mean delays in the links under equilibrium. We also show that the fixed-point equations that the equilibrium probabilities satisfy are actually the necessary and sufficient conditions of an appropriate optimization problem. Simulations supporting the analytical results are provided.},
	address = {New Orleans, Louisiana},
	booktitle = {46th IEEE Conference on Decision and Control},
	pages = {pp. 340-345}
}
@conference {
	title = {Combined Single-Path Routing and Flow Control in Many-User Region: A Case for Nash Efficiency},
	author = {Chen, Huigang., Baras, John S.},
	year = {2007},
	month = {12/2007},
	abstract = {We consider the problem of combined single-path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the {\textquotedblleft}many-user{\textquotedblright} region, i.e. large networks that have far more number of users than that of bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing~while keeping the remaining majority to use single-path routing, the resulting solution achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the price of anarchy, that is the gap between the worst Nash equilibrium and the social optimal, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. However, we introduce the concept of approximate Nash equilibrium and we show its existence given a~sufficiently large number of users. Then we prove that the approximate Nash equilibrium will be arbitrary close to the social optimal when the number of users is sufficiently large.},
	address = {New Orleans, Louisiana},
	booktitle = {46th IEEE Conference on Decision and Control},
	pages = {pp. 26-31}
}
