@conference {
	title = {Opportunistic Communications for Networked Controlled Systems of Autonomous Vehicles},
	author = {Chen, Hua., Hovareshti, Pedram., Baras, John S.},
	year = {2010},
	month = {10/2010},
	abstract = {Situational awareness requires maintaining a reasonable level of communication connectivity in networks of autonomous vehicles. It is difficult to overcome deep fading from time-varying wireless channels in a dynamic and resource constrained environment. Moreover, other system constraints such as the energy consumption and total operation time make the design of communication protocols for such systems more challenging. In this paper, we consider the problem of efficient communications between a group of autonomous vehicles with energy consumption and total operation time constraints in an adversarial environment. We show that the policy of continuously attempting to communicate reliably over the course of the mission may lead to considerable system degradation. We propose an adaptive algorithm to make communication attempts opportunistically, based on the qualities of the wireless channels as the vehicles move throughout the terrain. We compare the proposed algorithm with a non-opportunistic algorithm in which the vehicles blindly attempt to communicate regularly throughout the course of the mission. We show that the proposed algorithm significantly improves the system performance, both in terms of operation time when the agents transmit only situational information and data throughput when additional data transmission is necessary.},
	address = {San Jose, CA},
	booktitle = {2010 Military Communications Conference (MILCOM 2010)},
	pages = {pp. 1306-1311}
}
@conference {
	title = {Efficient communication Infrastructures for Distributed Control and Decision Making in Networked Stochastic Systems},
	author = {Baras, John S., Hovareshti, Pedram.},
	year = {2010},
	month = {07/2010},
	abstract = {In networked systems, groups of agents achieve certain objectives via interaction at local levels in a distributed manner. the performance of such systems is determined by the communication infrastructure of the network as well as the system dynamics. In this paper we study the interdependence of the communication and collaboration graphs in a networked system, in the context of a coordination control and decision making problem. Each agent has to make a decision on whether to cooperate or not in a group effort. this is modelled by two-person coordination games between neighboring agents. the payoff of each agent is computed as the sum of the agent{\textquoteright}s payoffs from each of these games. Each agent{\textquoteright}s decision on whether to collaborate or not is based on its personal understanding of its own behavioral tendencies as well as its neighbors{\textquoteright}. to account for this fact we endow the agents with a behavioral variable which indicates how risk averse each agent is. The effect of the agents on each other is governed by an influence matrix which is partially derived from the communication graph{\textquoteright}s topology. This paper focuses on three major issues: The learning algorithm, the effect of communication network topology on the fast convergence of the scheme, the characterization of the effect of the number of like- minded agents and their well-connectedness as major decisive factors on which equilibrium is attained.},
	address = {Budapest, Hungary},
	booktitle = {The 19th International Symposium on Mathematical Theory of Networks and Systems (MTNS 2010)},
	pages = {pp. 1-6}
}
@conference {
	title = {Distributed Collaborative Controlled Autonomous Vehicle Systems over Wireless Networks},
	author = {Chen, Hua., Hovareshti, Pedram., Baras, John S.},
	year = {2010},
	month = {06/2010},
	abstract = {Inspired by military tactical, civil help-and-rescue applications, it is desirable yet challenging to develop networked systems of autonomous vehicles and sensors in dynamic, resource-constrained and adversarial environments. An essential aspect of designing such collaborative systems is to address the communication needs of the vehicles in order to perform a given mission. The vehicles{\textquoteright} communication network should maintain a connectivity pattern based on the requirements of the mission. In this paper, we consider both the control and communication aspects for coordinated path planning of a group of autonomous vehicles in an adversarial environment. We propose distributed algorithms to control the vehicles{\textquoteright} trajectories over a wireless vehicle-to-vehicle network. Distributed control algorithms both with and without collaboration between the vehicles are presented. We study the performance of the wireless network over the distributed controlled autonomous vehicles. Simulation results show that collaboration between vehicles results in better performance for path planning and wireless inter-vehicle communications. However, contention based communication protocols are likely to fail due to severe channel conditions.},
	address = {Marrakech, Morocco},
	booktitle = {18th Mediterranean Conference onControl and Automation (MED 2010)},
	pages = {pp. 1695-1700}
}
