@conference {
	title = {Semiring Pruning for Information Dissemination in Mobile Ad Hoc Networks},
	author = {Somasundaram, Kiran K., Baras, John S.},
	year = {2009},
	month = {12/2009},
	abstract = {Link state routing mechanisms have shown good convergence behaviour with mobile hosts. Pruning methods such as those used in Optimized Link State Routing (OLSR) have showed good throughput behaviour when compared to traditional link-state approaches which suffered from broadcast storm problems. In this paper, we show that the pruning function is a fundamental component of link-state routing protocols for mobile networks. We also show that this component architecture aids in interpreting both distance vector and link-state approaches under a common framework. We develop a class of pruning methods for many of the most commonly used routing objectives and show that these pruning methods are a special case of the semiring distribution property.},
	address = {Chennai, India},
	booktitle = {Proceedings of the The First International Conference on Networks and Communications(NetCoM-2009)},
	pages = {pp. 319-325}
}
@conference {
	title = {Achieving Symmetric Pareto Nash Equilibria using Biased Replicator Dynamics},
	author = {Somasundaram, Kiran K., Baras, John S.},
	year = {2009},
	month = {12/2009},
	abstract = {Achieving the Nash equilibria for single objective games is known to be a computationally difficult problem. However, there is a special class of equilibria called evolutionary robust equilibria which can be obtained through a special type of evolutionary dynamics called the replicator dynamics. These dynamics has special properties over the simplex, which has been studied in optimization theory to solve several combinatorial problems. In this work, we consider the essentially hard combinatorial optimization problem of computing the equilibria in games with multiple objectives. We extend the notion of replicator dynamics to handle such games. We establish proofs of dynamic stability of this modified replicator dynamics and present their relation to the Pareto Nash equilibria in multiobjective games.},
	address = {Shanghai, China},
	booktitle = {48th IEEE Conference on Decision and Control},
	pages = {pp.7000 - 7005}
}
@conference {
	title = {Performance Improvements in Distributed Estimation and Fusion Induced by a Trusted Core},
	author = {Somasundaram, Kiran K., Baras, John S.},
	year = {2009},
	month = {07/2009},
	abstract = {We consider distributed state estimation and fusion in autonomic ad-hoc sensor networks when some nodes are untrusted, corrupted or malicious. We provide rigorous graph models to capture both trust and network functionality relations. We propose a novel hierarchical scheme, inspired from socio-cognitive dynamics in economics and sociology, that utilizes a trusted core. We provide a component-based architecture to show the interplay between the trust and estimation schemes. As an explanatory example we consider the problem of distributed Kalman filtering. We show that trust-based schemes, implemented by a trusted core, result in significant improvement in the state estimation procedure. We also find that the interplay between estimation and trust updates quickly isolates malicious nodes and helps the observation limited nodes (corrupted sensor nodes).},
	address = {Seattle, WA},
	booktitle = {12th International Conference on Information Fusion (Fusion 2009)},
	pages = {pp. 1942-1949}
}
@conference {
	title = {Evolutionary Dynamics of Collaborative Environments with Heterogenous Agents},
	author = {Somasundaram, Kiran K., Baras, John S.},
	year = {2009},
	month = {06/2009},
	abstract = {The seminal work of Maynard Prince and Price in 1973 laid the foundations in establishing the concepts of evolutionarily stable game strategies. It attempts to select strategies which are robust to evolutionary selection pressures. We observe that most of the literature as evolved is concentrated on single objective games. In this work, we extend the notion of evolutionary stability to games with vector payoff functions. We illustrate by examples that this notion of Multicriteria evolutionary stability models a much larger class of interactions in social, economic and biological problems. Particular applications of interest are in autonomic wireless sensor networks and autonomic networked control systems. We present a multi-population replicator dynamics, which models the evolution of agent actions in a network with varying levels of selfishness. We observe this model clearly demarks the regions of co-operation among these selfish agents. We provide analytical results on the dynamic stability of the replication. This clearly characterizes the aforementioned demarcations.},
	address = {Thessaloniki, Greece},
	booktitle = {17th Mediterranean Conference on Control \&amp; Automation (MED 09)},
	pages = {pp 121-125}
}
@conference {
	title = {Component Based Performance Modeling of Wireless Routing Protocols},
	author = {Baras, John S., Tabatabaee, Vahid., Purkayastha, Punyaslok., Somasundaram, Kiran K.},
	year = {2009},
	month = {06/2009},
	abstract = {We propose a component-based methodology for modelling and design of wireless routing protocols. Componentization is a standard methodology for analysis and synthesis of complex systems, or software. The feasibility of the component based design relies heavily on the compositionality property (i.e. system-level properties can be computed from properties of components). To provide a component based design methodology and to test compositionality for routing protocols, we have to develop a component-based model of the wireless network. We present the main components of the routing protocol that should be modelled and focus on three main components: neighborhood discovery, selector of topology information to disseminate, and the path selection components. For each component, we identify the inputs, outputs, and a generic methodology for modelling. Throughout the paper, we use the Optimized Link State Routing (OLSR) protocol as a case study to demonstrate the effectiveness of our approach. Using the neighborhood discovery component, we present our design methodology and design a modified enhanced version of this component, and compare its performance to the original OLSR design.},
	address = {Dresden, Germany},
	booktitle = {IEEE ICC 2009 Ad Hoc and Sensor Networking Symposium},
	pages = {pp.1-6}
}
