@conference {
	title = {Path Optimization and Trusted Routing in MANET: An Interplay Between Ordered Semirings},
	author = {Somasundaram, Kiran K., Baras, John S.},
	year = {2010},
	month = {12/2010},
	abstract = {In this paper, we formulate the problem of trusted routing as a transaction of services over a complex networked environment. We present definitions from service-oriented environments that unambiguously capture the difference between trust and reputation relations. We show that the trustworthiness measures associated with these relations have a linear order embedded in them. Identifying this order structure permits us to treat the trusted routing problem as a bi-objective path optimization problem. We consider bottleneck trust and present polynomial time solutions to obtain the optimal routing paths in various bi-objective settings. In developing these algorithms, we identify an interesting decomposition principle for (min,+) and (min,max) semirings, which yields a distributed solution.},
	address = {Chennai, India},
	booktitle = {The Second International Conference on Networks \&amp; Communications (NetCoM - 2010)},
	pages = {pp. 1-11}
}
@conference {
	title = {Consensus-Based Linear Distributed Filtering},
	author = {Matei, Ion., Baras, John S.},
	year = {2010},
	month = {12/2010},
	abstract = {We address the consensus-based distributed linear filtering problem, where a discrete time, linear stochastic process is observed by a network of sensors. We assume that the consensus weights are known and we first provide sufficient conditions under which the stochastic process is detectable, i.e. for a specific choice of consensus weights there exists a set of filtering gains such that the dynamics of the estimation errors (without noise) is asymptotically stable. Next, we provide a distributed, sub-optimal filtering scheme based on minimizing an upper bound on a quadratic filtering cost. In the stationary case, we provide sufficient conditions under which this scheme converges; conditions expressed in terms of the convergence properties of a set of coupled Riccati equations. We continue with presenting a connection between the consensus based distributed linear filter and the optimal linear filter of a Markovian jump linear system, appropriately defined. More specifically, we show that if the Markovian jump linear system is (mean square) detectable, then the stochastic process is detectable under the consensus-based distributed linear filtering scheme. We also show that the optimal gains of a linear filter for estimating the state of a Markovian jump linear system appropriately defined can be used to approximate the optimal gains of the consensus-based linear filter.},
	address = {Atlanta, Georgia},
	booktitle = {49th IEEE Conference on Decision and Control (CDC 2010)},
	pages = {pp.  7009- 7014}
}
@conference {
	title = {Distributed Topology Control for Stable Path Routing in Multi-hop Wireless Networks},
	author = {Somasundaram, Kiran K., Baras, John S., Jain, Kaustubh., Tabatabaee, Vahid.},
	year = {2010},
	month = {12/2010},
	abstract = {In this paper, we introduce the stable path topology control problem for routing in mobile multi-hop networks. We formulate the topology control problem of selective linkstate broadcast as a graph pruning problem with restricted local neighborhood information. We develop a multi-agent optimization framework where the decision policies of each agent are restricted to local policies on incident edges and independent of the policies of the other agents. We show that under a condition called the positivity condition, these independent local policies preserve the stable routing paths globally. We then provide an efficient algorithm to compute an optimal local policy that yields a minimal pruned graph, which we call the Stable Path Topology Control (SPTC) algorithm. Using simulations, we demonstrate that this algorithm, when used with the popular ETX metric, outperforms topology control mechanisms commonly used for Mobile Ad Hoc Networks.},
	address = {Atlanta, Georgia},
	booktitle = {49th IEEE Conference on Decision and Control (CDC 2010)},
	pages = {pp.  2342-2347}
}
@conference {
	title = {Robust State Estimation Under False Data Injection in Distributed Sensor Networks},
	author = {Zheng, Shanshan., Jiang, Tao., Baras, John S.},
	year = {2010},
	month = {12/2010},
	abstract = {Distributed sensor networks have been widely employed to monitor and protect critical infrastructure assets. The network status can be estimated by centralized state estimation using coordinated data aggregation or by distributed state estimation, where nodes only exchange information locally to achieve enhanced scalability and adaptivity to network dynamics. One important property of state estimation is robustness against false data injection from sensors compromised by attackers. Different from most existing works in the literature that focus on centralized state estimation, we propose two novel robust distributed state estimation algorithms against false data injection. They are built upon an existing distributed Kalman filtering algorithm. In the first algorithm, we use variational Bayesian learning to estimate attack parameters and achieve performance similar to a centralized majority voting rule, without causing extra communication overhead. In the second algorithm, we introduce heterogeneity into the network by utilizing a subset of pre-trusted nodes to achieve performance better than majority voting. We show that as long as there is a path connecting each node to some of the pre-trusted nodes, the attackers can not subvert the network. Experimental results demonstrate the effectiveness of our proposed schemes.},
	address = {Miami, Florida},
	booktitle = {IEEE Globecom 2010},
	pages = {pp.1-5}
}
@conference {
	title = {A systems biology model studying the role of cholesterol in Alzheimer{\textquoteright}s disease pathogenesis},
	author = {Kyrtsos, C Rose., Lee, Hey-Kyoung., Baras, John S.},
	year = {2010},
	month = {11/2010},
	abstract = {Objective: To develop a systems-level, metabolic network model to study the effect that alterations in the brain cholesterol concentration levels have on downstream or interconnected sub-networks in an Alzheimer{\textquoteright}s disease (AD) model.Methods: A simplified network encompassing both basic metabolic networks such as glucose and amino acid metabolism, as well as APP processing, cholesterol metabolism, and cholesterol-related metabolic pathways was generated using pathways described by either the KEGG database or in the literature. A differential equations model describing the distribution of molecules within the network over time was developed and simulated using Matlab. The model was initialized using healthy concentrations of all pertinent and known quantities. Individual molecules were represented by nodes in the topological mapping, while reactions between different molecules were designated by weighted links. The weights of the links were determined stoichiometrically, where possible, or statistically, if data was not available.Results: Our results are one of the first attempts to study Alzheimer{\textquoteright}s disease using a systems biology approach. This approach is unique in that it allows us to merge the creation of a systems-level quantitative model for the brain metabolic network with data obtained from in vivo experiments to generate the most accurate mathematical model using current knowledge. The topology of the initially-generated network showed crucial overlap between the APP clearance pathway and cholesterol distribution pathway in adults, specifically with the shared usage of apolipoprotein E (apoE) as a carrier for both beta amyloid (Aβ) cholesterol, and with the LDL receptor-related protein (LRP-1) as a necessary transport protein for Aβ out of the brain and cholesterol into neurons. Short run simulations of networks with decreased brain cholesterol synthesis showed slight increases in the concentration levels of Aβ.Conclusion: We have developed a systems-level, pseudo-metabolic network for the basic metabolic pathways in the brain that are pertinent to the development of AD. Analysis of the network structure revealed several important topological homologies between APP and cholesterol processing. Given our results and the important role that cholesterol plays in maintaining normal neuronal function, it is likely that decreased cholesterol will negatively affect functioning of neurons. Our future work will use an in vivo mouse model to study the effects of decreased brain cholesterol on AD pathology.},
	address = {San Diego, CA},
	booktitle = {40th Annual Meeting Neuroscience 2010}
}
@conference {
	title = {Modeling TDMA-Based USAP in JTRS MDL for Multicast and Unicast Traffic},
	author = {Perumal, Senni., Tabatabaee, Vahid., Baras, John S., Graff, Charles J., Yee, David G.},
	year = {2010},
	month = {10/2010},
	abstract = {In this paper, we develop loss network models for the hard scheduling mode (virtual circuit mode) of the reservation based USAP scheduling protocol as used in the Mobile Data Link (MDL) of the Joint Tactical Radio System (JTRS). These models are used to find performance metric estimates for both multicast and unicast traffic. USAP (Unifying Slot Assignment Protocol) is a dynamic distributed resource allocation protocol for mobile multihop wireless networks where the channel is partitioned in time and frequency. MDL creates a backbone sub-network and routes all traffic through this sub-network. For the backbone sub-network, we consider algorithms that form Connected Dominating Sets. We use loss network models that couple the physical, MAC, and routing layers effects. The effect of the MAC layer is modeled by approximating available capacity at a node. The available capacity to transmit is computed based on the USAP reservation rules and the node{\textquoteright}s 2-hop neighborhood traffic. For a given time varying scenario, we compute the performance metrics of blocking probability and throughput for both multicast and unicast traffic as a function of time. We compare the results of our model against simulation.},
	address = {San Jose, CA},
	booktitle = {2010 Military Communications Conference (MILCOM 2010)},
	pages = {pp. 1464-1469}
}
@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 = {VSAT return Channel Optimizations for Broadband Internet Support in 2-Way Satellite Networks},
	author = {Roy-Chowdhury, Ayan., Baras, John S., Robinson, Mitch.},
	year = {2010},
	month = {10/2010},
	abstract = {In this paper we describe our work on a Very Small Aperture Terminal (VSAT) satellite Internet gateway with capacity and latency optimizations in the return channel so as to allow significantly higher number of users, and a better user experience. The gateway is based on the Cerona SkySPAN technology which uses the Digital Video Broadcast via Satellite 2nd standard (DVB-S2) in the forward channel, and single-channel slotted Aloha protocol in the return channel. In this paper we describe the Spread Aloha Multiple Access (SAMA) protocol which we implement in the return channel. The SAMA protocol promises to deliver high speeds at a third of the latency compared to competing technologies like DVB-RCS (multi-frequency TDMA), while allowing the same number of users in 3MHz bandwidth as is possible in TDMA using 36MHz. We also describe the implementation of the Fast Multi-channel Slotted Aloha (FMCSA) protocol that will co-exist with SAMA in the return channel. FMCSA combines slotted Aloha random access with packet level forward error correction (FEC) for new messages and scheduled retransmissions for partially received messages. Due to the parity packets sent in FMCSA, more load is offered to the channel than in SAMA to achieve the same throughput. The delay performance of FMCSA is also much more robust to load fluctuations than SAMA. The combination of SAMA and FMCSA improves the robustness and throughput of the SkySPAN return channel and reduces the channel latency, while supporting significantly higher number of users, in comparison to the competition.},
	address = {Milan, Italy},
	booktitle = {16th Ka and Broadband Communications Conference},
	pages = {pp. 479-486}
}
@conference {
	title = {The Role of Cholesterol in Alzheimer{\textquoteright}s disease Pathogenesis: Preliminary Report},
	author = {Kyrtsos, C Rose., Baras, John S.},
	year = {2010},
	month = {10/2010},
	abstract = {Alzheimer{\textquoteright}s disease (AD) is a devastating neurodegenerative disorder affecting 1 in 8 individual over the age of 65. A growing body of evidence is suggesting that cholesterol levels in both the brain and the plasma may play significant roles in AD pathogenesis; however, the exact nature of this role is currently not well understood. Building on previous experiments, we have approached this problem using two, complementary methods- a systems biology model for brain metabolic networks that is based on empirical data gathered from in vivo experiments. The main goal of this study was to determine the effect that decreased brain cholesterol had on the level of beta amyloid (the key protein implicated in AD pathogenesis) and the extent of neurodegeneration observed. To achieve this, APPSwe/PS1 double transgenic mice were treated twice daily with simvastatin (a cholesterol-lowering drug) for a period of 2 or 10 weeks. The effects of the decreased brain cholesterol levels on APP and beta amyloid processing, as well as apoE and LRP-1 expression levels was studied using Western blotting and immunohistochemistry techniques, respectively. The extent of neurodegeneration was determined via immunohistochemical staining of hippocampal slices for synaptic density and neuron viability. The weights between key nodes in the systems biology model were updated to account for the observed experimental results.},
	address = {Austin, Texas},
	booktitle = {Biomedical Engineering Society (BMES 2010)}
}
@conference {
	title = {Trust-aware State Estimation Under False Data Injection In Distributed Sensor Networks},
	author = {Zheng, Shanshan., Jiang, Tao., Baras, John S.},
	year = {2010},
	month = {09/2010},
	abstract = {Distributed sensor networks have been widely employed to monitor and protect critical infrastructure assets. The network status can be estimated by centralized state estimation using coordinated data aggregation or by distributed state estimation, where nodes only exchange information locally to achieve enhanced scalability and adaptivity to network dynamics. One important property of state estimation is robustness against false data injection from sensors compromised by attackers. Different from most existing works in the literature that focus on centralized state estimation, we propose two novel robust distributed state estimation algorithms against false data injection. They are built upon an existing distributed Kalman filtering algorithm. In the first algorithm, we use variational Bayesian learning to estimate attack parameters and achieve performance similar to a centralized majority voting rule, without causing extra communication overhead. In the second algorithm, we introduce heterogeneity into the network by utilizing a subset of pre-trusted nodes to achieve performance better than majority voting. We show that as long as there is a path connecting each node to some of the pre-trusted nodes, the attackers can not subvert the network. Experimental results demonstrate the effectiveness of our proposed schemes.},
	address = {Austin, Texas},
	booktitle = {TECHCON 2010},
	pages = {pp. 1-4}
}
@conference {
	title = {Stochastic Average Consensus Filter for Distributed HMM Filtering: Almost Sure Convergence},
	author = {Ghasemi, Nader., Dey, Subhrakanti., Baras, John S.},
	year = {2010},
	month = {09/2010},
	abstract = {This paper studies almost sure convergence of a dynamic average consensus algorithm which allows distributed computation of the product of n time-varying conditional probability density functions. These conditional probability density functions (often called as {\textquotedblleft}belief functions{\textquotedblright}) correspond to the conditional probability of observations given the state of an underlying Markov chain, which is observed by n different nodes within a sensor network. The network topology is modeled as an undirected graph. The average consensus algorithm is used to obtain a distributed state estimation scheme for a hidden Markov model (HMM), where each sensor node computes a conditional probability estimate of the state of the Markov chain based on its own observations and the messages received from its immediate neighbors. We use the ordinary differential equation (ODE) technique to analyze the convergence of a stochastic approximation type algorithm for achieving average consensus with a constant step size. This allows each node to track the time varying average of the logarithm of conditional observation probabilities available at the individual nodes in the network. It is shown that, for a connected graph, under mild assumptions on the first and second moments of the observation probability densities and a geometric ergodicity condition on an extended Markov chain, the consensus filter state of each individual sensor converges almost surely~to the true average of the logarithm of the conditional observation probability density functions of all the sensors. Convergence is proved by using a perturbed stochastic Lyapunov function technique. Numerical results suggest that the distributed Markov chain state estimates obtained at the individual sensor nodes based on this consensus algorithm track the centralized state estimate (computed on the basis of having access to observations of all the nodes) quite well, while more formal convergence results for the distributed HMM filter to the centralized one are currently under investigation.},
	address = {Annecy, France},
	booktitle = {2nd IFAC Workshop on Distributed Estimation and Control in Networked Systems (NecSys{\textquoteright}10)},
	pages = {pp. 335-340}
}
@conference {
	title = {The asymptotic consensus problem on convex metric spaces},
	author = {Matei, Ion., Baras, John S.},
	year = {2010},
	month = {09/2010},
	abstract = {We consider the consensus problem of a group of dynamic agents whose communication network is modeled by a directed time-varying graph. In this paper we generalize the asymptotic consensus problem to convex metric spaces. A convex metric space is a metric space endowed with a convex structure. Using this convex structure we define convex sets and in particular the convex hull of a (finite) set. Under minimal connectivity assumptions, we show that if at each iteration an agent updates its state by choosing a point from a particular subset of the convex hull generated by the agent{\textquoteright}s current state and the states of its neighbors, then asymptotic agreement is achieved. In addition, we give bounds on the distance between the consensus point and the initial values of the agents.},
	address = {Annecy, France},
	booktitle = {2nd IFAC Workshop on Distributed Estimation and Control in Networked Systems (NecSys{\textquoteright}10)},
	pages = {pp. 287- 292}
}
@conference {
	title = {A Network Model of Alzheimer{\textquoteright}s disease},
	author = {Kyrtsos, C Rose., Baras, John S.},
	year = {2010},
	month = {07/2010},
	abstract = {We have derived a multi-scale network model to study the relationship between cholesterol and Aβ in silico to integrate with future experimental work. A pseudo-metabolic network approach has been taken to model the interactions between various signaling molecules, carrier and transport proteins, as well as other proteins that are considered pertinent to AD pathogenesis. We have also monitored the number of neurons and related synapses using a modified McCulloch-Pitts neural network.},
	address = {Pittsburgh, Pennsylvania},
	booktitle = {2010 SIAM Life Sciences Conference}
}
@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 = {Local Pruning for Information Dissemination for the Idempotent Semiring Algebraic Path Problem},
	author = {Somasundaram, Kiran K., Baras, John S.},
	year = {2010},
	month = {07/2010},
	abstract = {The advent of pervasive mobile devices has created the need for new algorithm design mechanisms for mobile computing platforms. The limited capabilities of these mobile devices have created several interesting problems that do not exist in traditional networks. These limitations have made communication an expensive commodity for distributed algorithms. In this paper, we consider the communicationintensive information broadcast problem for distributed computation. In distributed computing, several different computations can be viewed from a common viewpoint as instances of the Semiring Algebraic Path Problem (SAPP) on graphs. We first show that many algorithms broadcast information to enable recomputation of the SAPP on a dynamic graph. We then develop a general theory of local pruning for the SAPP problem for idempotent semirings. We motivate the pruning problem as a multi-agent optimization problem, where the agents try to limit the amount of information they broadcast while ensuring that the broadcast is sufficient to recompute the SAPP. The main contribution of this paper is establishing that this local pruning scheme chooses sufficient information to compute the original SAPP. For the dynamic SAPP, the information broadcast required to recompute the SAPP is reduced by the pruning. We also show that our solution corresponds to a local Gauss elimination solution over an extended semiring.},
	address = {Budapest, Hungary},
	booktitle = {The 19th International Symposium on Mathematical Theory of Networks and Systems (MTNS 2010)},
	pages = {pp. 1-8}
}
@conference {
	title = {Performance Evaluation of Multi-Agent Distributed Collaborative Optimizationunder Random Communication Topologies},
	author = {Matei, Ion., Baras, John S.},
	year = {2010},
	month = {07/2010},
	abstract = {We investigate collaborative optimization in a multi-agent setting, when the agents execute in a distributed manner using local information, while the communication topology used to exchange messages and information is modeled by a graph-valued random process, independent of other time instances. Specifically, we study the performance of the consensus-based multi-agent subgradient method, for the case of a constant stepsize, as measured by two metrics: rate of convergence and guaranteed region of convergence, evaluated via their expected values. Under a strong convexity type of assumption, we provide upper bounds on the performance metrics, which explicitly depend on the probability distribution of the random graph and on the agents{\textquoteright} estimates of the optimal solution. This provides a guide for tuning the parameters of the communication protocol such that good performance of the multi-agent subgradient method is ensured.},
	address = {Budapest, Hungary},
	booktitle = {Proceedings of the19th International Symposium on Mathematical Theory of Networks and Systems (MTNS 2010)},
	pages = {pp.1-8}
}
@conference {
	title = {Tuning the TCP Timeout Mechanism in Wireless Networks to Maximize Throughput via Stochastic Stopping Time Methods},
	author = {Papageorgiou, George., Baras, John S.},
	year = {2010},
	month = {07/2010},
	abstract = {We present an optimization problem that aims to maximize the throughput of a Transmission Control Protocol (TCP) connection between two nodes in a wireless adhoc network. More specifically, we focus on a persistent TCP connection between two nodes that are one hop away in a wireless unslotted Aloha network. The optimization is over the TCP timeout period, i.e. the problem is to find the optimal waiting period before the TCP sender declares a timeout event in the absence of a received acknowledgement for a transmitted packet. The problem is formulated as an optimal stochastic stopping time problem. In the absence of a tractable analytical solution to the problem, a numerical method based on dynamic programming is used instead. We verify the performance increase by comparing our solution to the standard TCP timeout mechanism using simulations for a range of values of the involved parameters.},
	address = {Budapest, Hungary},
	booktitle = {The 19th International Symposium on Mathematical Theory of Networks and Systems (MTNS 2010)},
	pages = {pp. 1539-1545}
}
@conference {
	title = {Dynamic Magic Graphs in Cooperative Networked Systems},
	author = {Baras, John S.},
	year = {2010},
	month = {07/2010},
	address = {Budapest, Hungary},
	booktitle = {The 19th International Symposium on Mathematical Theory of Networks and Systems (MTNS 2010)}
}
@conference {
	title = {Architectures, Modularity and Robustness in Networked Control Systems},
	author = {Baras, John S.},
	year = {2010},
	month = {07/2010},
	address = {Leuven, Belgium},
	booktitle = {2010 IFAC International Symposium on Dynamics and Control of Process Systems}
}
@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}
}
@conference {
	title = {Security and Trust in Communication and Social Networks},
	author = {Baras, John S.},
	year = {2010},
	month = {06/2010},
	address = {Al Ain, UAE},
	organization = {United Arab Emirates University}
}
@conference {
	title = {Modeling Air Traffic Throughput and Delay with Network Cell Transmission Model},
	author = {Nguyen, Alex T., Baras, John S.},
	year = {2010},
	month = {05/2010},
	abstract = {In practice, the model is envisioned to initially run offline to determine a preliminary solution to the initial state of the system. Solutions for subsequent changes in actual state can be determined by running the model online for the incremental state change. Stochastic events such as convective weather clearing times or capacities can be included in the model to better see the benefits and impacts of pre-positioning traffic to take advantage of possible future clearing.},
	address = {Herndon, VA},
	booktitle = { Integrated Communications Navigation and Surveillance Conference (ICNS 2010)},
	pages = {pp. 1-14}
}
@conference {
	title = {A Systems Biology Approach to Understanding Alzheimer{\textquoteright}s Disease},
	author = {Kyrtsos, C Rose., Baras, John S.},
	year = {2010},
	month = {04/2010},
	abstract = {Alzheimer{\textquoteright}s disease (AD) is the most prevalent form of dementia affecting the elderly. AD has devastating effects on the individual, leading to neuronal and synaptic loss, neuroinflammation, dysfunction of the blood-brain barrier and deposition of amyloid beta plaques in the brain parenchyma and cerebral blood vessels. Due to the inherent difficulty studying the many possible initiating factors of AD with in vivo models, we have chosen to approach this problem from a quantitative perspective initially to determine what key factors may initiate AD pathogenesis. We have developed a multi-scale systems biology model that describes the interactions between different components of the brain{\textquoteright}s biological network at the tissue, cellular and transcriptional levels. Neurons have been modeled using a modified McCulloch-Pitts neural network that accounts for cell death and synapse loss due to varying amyloid beta and cholesterol levels. Microglia have been modeled in both the ramified and activated states using the Langevin equations of motion. The spatial-temporal distribution of beta amyloid has been modeled using the convection-reaction-diffusion equation with stochastic generation rates. Transport of beta amyloid by LRP-1 across the blood-brain barrier has also been modeled. Future generations of the model will take into account experimental results, as well as include models for plaque development in the basement membrane of cerebral blood vessels.},
	address = {College Park, Maryland},
	booktitle = {2010 Southern Biomedical Engineering Conference},
	organization = {University of Maryland}
}
@conference {
	title = {Convergence Results for Ant Routing Algorithms via Stochastic Approximation and Optimization},
	author = {Purkayastha, Punyaslok., Baras, John S.},
	year = {2010},
	month = {04/2010},
	abstract = {In this paper, we provide convergence results for an Ant Routing (ARA) Algorithm for wireline, packet switched communication networks, that are acyclic. Such algorithms are inspired by the foraging behavior of ants in nature. We consider an ARA algorithm proposed by Bean and Costa [2]. The algorithm has the virtues of being adaptive and distributed, and can provide a multipath routing solution. We consider a scenario where there are multiple incoming data traffic streams that are to be routed to their destinations via the network. Ant packets, which are nothing but probe packets, are used to estimate the path delays in the network. The node routing tables, which consist of routing probabilities for the outgoing links, are updated based on these delay estimates. In contrast to the available analytical studies in the literature, the link delays in our model are stochastic, time-varying, and dependent on the link traffic. The evolution of the delay estimates and the routing probabilities are described by a set of stochastic iterative equations. In doing so, we take into account the distributed and asynchronous nature of the algorithm operation. Using methods from the theory of stochastic approximations, we show that the evolution of the delay estimates can be closely tracked by a deterministic ODE (Ordinary Differential Equation) system, when the step-size of the delay estimation scheme is small. We study the equilibrium behavior of the ODE in order to obtain the equilibrium behavior of the algorithm. We also provide illustrative simulation results.},
	address = {Stockholm, Sweden},
	booktitle = {Proceddings of the 13th International Conference on Hybrid Systems: Computation and Control (HSCC {\textquoteright}10)},
	pages = {pp. 201-210}
}
@conference {
	title = {A Trust Based Distributed Kalman Filtering Approach for Mode Estimation in Power Systems},
	author = {Jiang, Tao., Matei, Ion., Baras, John S.},
	year = {2010},
	month = {04/2010},
	abstract = {We consider distributed mode estimation in power systems. The measurements are observed by PMUs (Power Management Units). We introduce a novel model of trust, using weights on the graph links and nodes that represent the networked PMUs. We describe two algorithms that intergarte distributed Kalman filtering with these trust weights. We consider two interpretations of these trust weights as information accuracy and reliability. We show that by appropriate use of these weights from the distributed estimation algorithm avoids using information from untrusted PMUs. Simulation experiments further demonstrate the behavior of these algorithms.},
	address = {Stockholm, Sweden},
	booktitle = {First Workshop on Secure Control Systems (SCS) as part of CPSWeek 2010},
	pages = {pp. 1-6}
}
@conference {
	title = {Compositional Framework for System Security with Multi-metric Optimization"},
	author = {Baras, John S., Jiang, Tao., Somasundaram, Kiran K., Ivanov, Vladimir I.},
	year = {2010},
	month = {03/2010},
	abstract = {The objective of the proposed research is to develop a compositional framework and methods for~performance vs security tradeoffs via multi-criteria optimization of system security, and therefore it aligns~with problem statement 2: {\textquotedblleft}Security Framework.{\textquotedblright} We propose to study a top-down approach ~for~optimizing (1) the security metric(s) of a composite system viewed as a bivariate function of its~subsystems{\textquoteright} security and performance metrics under given constraints and (2) the composition of~subsystems that provides higher system security than that of the composition of the same subsystems~driven solely by performance maximization. In this way, we reconcile the trade-off between security and~performance by introducing a holistic, multi-objective solution that satisfies both the performance and the~security requirements for the system, by overcoming the problem of compartmentalized security solutions~and thus achieving the {\textquotedblleft}best value{\textquotedblright} of the system. Our framework delineates methods for achieving~provably secure composition of secure subsystems and system components {\textendash} a critical problem area~where almost all current results demonstrate infeasibility of achieving compositional security.},
	address = {Washington DC},
	booktitle = {SERC Security Workshop}
}
@conference {
	title = {Systems Engineering Challenges for Design and Realtime Management of Component-Enabled Wireless Ad-hoc Networks},
	author = {Austin, Mark A., Tabatabaee, Vahid., Baras, John S.},
	year = {2010},
	month = {03/2010},
	abstract = {This paper describes systems engineering challenges for the systematic design and realtime management of component-enabled wireless ad-hoc networks. At the front end of development, emphasis is placed on the use of goals and scenarios, and visual modelling abstractions for elicitation of models for required functionality. We assume that network nodes will be implemented as hierarchies of interconnected sub-components. To maximise system reliability and simplify technology upgrades we advocate the use of formal approaches to component interface definition, and to validation of component and system-level functionalities.},
	address = {Hoboken, NJ},
	booktitle = {Proceedings of the 8th Conference on Systems Engineering Research (CSER 2010)},
	pages = {pp. 1-10}
}
@conference {
	title = {A Mathematical Model for Alzheimer{\textquoteright}s disease},
	author = {Kyrtsos, C Rose., Baras, John S.},
	year = {2010},
	month = {02/2010},
	abstract = {A mathematical model for Alzheimer{\textquoteright}s disease (AD) has been developed using a systems biology approach. A cellular network of neurons, microglia and astrocytes has been created to model the levels of Aβ in the brain. The production and spatial distribution of beta amyloid (Aβ), the key protein implicated in AD, has been modeled using the reaction-diffusion equation, where reaction rates have been modeled using stochastic functions. Neurons have been modeled using a previously developed McCulloch-Pitts neural network (Butz 2006) modified to account for neuronal cell death and loss of synaptic elements during high Aβ levels. Microglia are either in the ramified state (at rest) and modeled using a continuous random walk model, or in the activated state (actively moving towards a source of Aβ) and modeled using the Langevin equation of motion. Astrocytes are defined to set locations and contribute to removal of Aβ from the brain interstitial fluid. The roles that local cerebral blood flow, transport across the BBB, and local reactions play have also been modeled. Future work will look at the development of amyloid beta plaques in the cerebrovasculature and brain parenchyma, and their relationship to observed decreases in cerebral blood flow as the disease progresses.},
	address = {San Francisco, California},
	booktitle = {Proceddings of the 2010 Biophysical Society Annual Meeting}
}
@conference {
	title = {A Systems Biology Approach to Modelling Alzheimer{\textquoteright}s disease},
	author = {Kyrtsos, C Rose., Baras, John S.},
	year = {2010},
	month = {01/2010},
	abstract = {A mathematical model for Alzheimer{\textquoteright}s disease (AD) has been developed using a systems biology approach. A cellular network of neurons, microglia and astrocytes has been created to model the levels of Aβ in the brain. The production and spatial distribution of beta amyloid (Aβ), the key protein implicated in AD, has been modeled using the reaction-diffusion equation, where reaction rates have been modeled using stochastic functions. Neurons have been modeled using a previously developed McCulloch-Pitts neural network (Butz 2006) modified to account for neuronal cell death and loss of synaptic elements during high Aβ levels. Microglia are either in the ramified state (at rest) and modeled using a continuous random walk model, or in the activated state (actively moving towards a source of Aβ) and modeled using the Langevin equation of motion. Astrocytes are defined to set locations and contribute to removal of Aβ from the brain interstitial fluid. The roles that local cerebral blood flow, transport across the BBB, and local reactions play have also been modeled. Future work will look at the development of amyloid beta plaques in the cerebrovasculature and brain parenchyma, and their relationship to observed decreases in cerebral blood flow as the disease progresses.},
	address = {San Francisco, California},
	booktitle = {Proceedings of the Joint Math Meeting 2010}
}
