@conference {
	title = {Selfish response to Epidemic Propagation},
	author = {Theodorakopoulos, George., Le Boudec, Jean-Yves., Baras, John S.},
	year = {2011},
	month = {06/2011},
	abstract = {An epidemic spreading in a network calls for a decision on the part of the network members: They should decide whether to protect themselves or not. Their decision depends on the trade-off between their perceived risk of being infected and the cost of being protected. The network members can make decisions repeatedly, based on information that they receive about the changing infection level in the network. We study the equilibrium states reached by a network whose members increase (resp. decrease) their security deployment when learning that the network infection is higher (resp. lower). Our main result is that as the learning rate of the members increases, the equilibrium level of infection increases. We demonstrate this result both when members are strictly rational and when they are not. We characterize the domains of attraction of the equilibrium points.We validate our conclusions with simulations on human mobility traces.},
	address = {San Francisco, CA},
	booktitle = {2011 American Control Conference},
	pages = {pp. 4069-4074}
}
@conference {
	title = {The Geometry of a Probabilistic Consensus of Opinion Algorithm},
	author = {Matei, Ion., Baras, John S.},
	year = {2011},
	month = {06/2011},
	abstract = {We consider the problem of a group of agents whose objective is to asymptotically reach agreement of opinion. The agents exchange information subject to a communication topology modeled by a time-varying graph. The agents use a probabilistic algorithm under which at each time instant an agent updates its state by probabilistically choosing from its current state/opinion and the ones of its neighbors. We show that under some minimal assumptions on the communication topology (infinitely often connectivity and bounded intercommunication time between agents), the agents reach agreement with probability one. We show that this algorithm has the same geometric properties as the linear consensus algorithm in Rn. More specifically, we show that the probabilistic update scheme of an agent is equivalent to choosing a point from the (generalized) convex hull of its current state and the states of its neighbors; convex hull defined on a particular convex metric space where the states of the agents live and for which a detailed description is given.},
	address = {San Francisco, CA},
	booktitle = {2011 American Control Conference},
	pages = {pp.  2198-2205}
}
@conference {
	title = {Trust-Assisted Anomaly Detection and Localization in Wireless Sensor Networks},
	author = {Zheng, Shanshan., Baras, John S.},
	year = {2011},
	month = {06/2011},
	abstract = {Fast anomaly detection and localization is critical to ensure effective functioning of wireless sensor networks. The low bandwidth and power constraints in wireless sensor networks are the main challenges for achieving this task, especially for large scale networks. In this paper, we propose a trust-assisted framework for detecting and localizing network anomalies in a hierarchical sensor network. The proposed method makes inference based on end-to-end measurements collected by a set of measurement nodes. Network heterogeneity is exploited for better bandwidth and energy efficiency. The trustworthiness of network links is utilized to design an efficient two-phase probing strategy that can achieve a flexible tradeoff between inference accuracy and probing overhead. We performed experiments with different network settings and demonstrated the effectiveness of our proposed algorithms.},
	address = {Salt Lake City, Utah},
	booktitle = {8th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON) 2011},
	pages = {pp.  386-394}
}
@conference {
	title = {On the complexity of a social behavior model},
	author = {Somarakis, Christoforos., Baras, John S.},
	year = {2011},
	month = {06/2011},
	abstract = {In this paper, we discuss a social behavior model in cellular automata. This model came as a result of research in dynamical structures of networks as these were constructed out of game theory and statistical physics. We define it a dynamical system on the planar grid and study its behavior by varying its parameters under different initial configurations.},
	address = {Quincy, MA},
	booktitle = {Eighth International Conference on Complex Systems (ICCS 2011)},
	pages = {pp.  1330-1344},
	organization = {Boston Marriott}
}
@conference {
	title = {Motif-based Topology Design for Effective Performance by Networks of Mobile Autonomous Vehicles},
	author = {Hovareshti, Pedram., Chen, Hua., Baras, John S.},
	year = {2011},
	month = {06/2011},
	abstract = {To design efficient local connectivity patterns, we have used the idea of network motifs, which was first proposed in the context of biological networks. Network motifs are task specific local connectivity patterns, which exist with much higher frequency in real biological networks compared to those in random networks. These are sub-networks of a low number of nodes (usually 3-4) whose persistence in networks performing similar tasks in different contexts, imply their efficiency in the sense that they optimize certain performance metric in a local scale. We use a simulation test bed to find network motifs for local level communication structures in a collaborative vehicles framework. Here, the group mission consists of several tasks that the agents participate in. The tasks include search operation, data gathering/processing, target finding and leader-follower explorations. Each task gives rise to certain motifs that are specific to that task and the partial knowledge of the environment specifications that the agents operate in. In this way, given the subtasks that are necessary for the mission accomplishment, the most efficient task-specific local topologies are extracted. Switching suitable graphs when the mode of operation is changing can be handled by solving the resulting reachability problem using methods for symbolic planning such as graph grammars. Based on such switching, we also address the effects of split/merge operations on the spectral characteristics of the resulting connectivity graphs.},
	address = {Quincy, MA},
	booktitle = {Eighth International Conference on Complex Systems (ICCS 2011),},
	pages = {pp.  571-573}
}
@conference {
	title = {Cooperative networked systems: Multiple graphs, coalitional games, new probabilistics models},
	author = {Baras, John S.},
	year = {2011},
	month = {06/2011},
	abstract = {The consideration of cooperative networked systems has raised fundamental new questions and challenges. We consider networked systems from various domains including control, communications, sensing, sociology, economics, and biology. We first describe a general model for modeling such systems that involve several interacting dynamic multigraphs. These multigraphs evolve in at least three planes. At the higher plane (layer) we have the network of cognitive agents, where decisions are made and executed. At the intermediate plane (layer) we have the information network, where data, models, observations and signaling are represented. At the lower plane (layer) we have the communication network that supports the information and agent networks. There are several ways to capture these ideas and principles, and the one presented here is one of the simpler possible representations. The lower layer is more connected to the physical layer, while the middle and higher layer is more logical. The networks involve have links and nodes that are annotated by weights that can be scalar, vector or even policies and rules. Furthermore, the networks are dynamic. The resulting dynamic models are very complex and require a combination of methods from analysis, algebra, logic and optimization. The simplest possible model involves two interacting multigraphs: (a) the collaboration multigraph, which describes the time varying relation of collaboration between the agents; and (b) the communication multigraph, which describes the time-varying communications that occur between the agents. We link these concepts to ideas from distributed computing, distributed programs, and distributed computer hardware. We also link this representation to the behavior and structure models used in modern model-based-systems engineering. We describe a novel path-oriented characterization of these activities in networked dynamic systems. Next, we introduce three fundamental problems and challenges emerging from this framework. The first addresses the joint analysis of the collaboration and communication multigraphs and their impact on the performance of the networked system. The second fundamental problem addresses the development of a taxonomy of collaboration and communication multigraphs, from the perspective of system performance. The third fundamental problem addresses the need for different probability models for such cooperative networked systems. We relate the new framework, emerging from the results of the first and second problems, and its basic constructs, to information and control patterns, generalized information theory and entropy, and to distributed computing with local states. This new framework indicates the need for a new kind of probability over dynamical logical structures that is reminiscent of the axiomatic framework of quantum physics.},
	address = {Corfu Island, Greece},
	booktitle = {Control \&amp; Automation (MED), 2011 19th Mediterranean Conference},
	pages = {pp. no. 798-800}
}
@conference {
	title = {Sequential Anomaly Detection in Wireless Networks and Effects of Long Range Dependent Data},
	author = {Baras, John S., Zheng, Shanshan.},
	year = {2011},
	month = {06/2011},
	abstract = {Anomaly detection is an important but difficult task for wireless networks such as mobile ad hoc networks (MANET) and wireless sensor networks (WSN). We present various sequential detection schemes for anomaly detection in such networks including protocol violation, wormhole attacks, fraudulent data injection or algorithm modification. We present both parametric and non parametric algorithms, as well as centralized and distributed schemes. Recent studies have shown that node mobility along with spatial correlations of the monitored traffic in such wireless networks can lead to long range dependent (LRD) traffic, which could significantly increase the difficulty of anomaly detection. We next analyze the effects of LRD traffic on these sequential anomaly detection schemes. Various models of LRD traffic are considered. In the proposed schemes, wavelet transforms are used to approximately de-correlate the traffic data and capture data characteristics at different time scales. The remaining dependencies are then captured by a multilevel hidden Markov model in the wavelet domain. To estimate the model parameters, we proposed an online discounting Expectation Maximization (EM) algorithm, which also tracks variations of the estimated models over time. Network anomalies are then detected as abrupt changes in the tracked model variation scores. We develop statistical properties of these detection schemes as well as performance results, especially stemming from using incorrect short range dependent traffic models.},
	address = {Palo Alto, CA},
	booktitle = {International Workshop on Sequential Methodologies (IWSM 2011)},
	organization = {Stanford University}
}
@conference {
	title = {Challenges and Opportunities for Future Broadband Networks: From Physical to Services to Social},
	author = {Baras, John S.},
	year = {2011},
	month = {06/2011},
	booktitle = {Kick-off meeting of the new center of excellence Labex Comin Labs}
}
@conference {
	title = {Performance Analysis of Time-Critical Peer-to-Peer Communications in IEEE 802.15.4 Networks},
	author = {Wang, Baobing., Baras, John S.},
	year = {2011},
	month = {06/2011},
	abstract = {Existing works on the performance analysis of IEEE 802.15.4 networks with peer-to-peer (P2P) topologies assume the non-beacon unslotted mode in the MAC layer, which is not suitable for time-critical communications required by many applications, such as control, actuation and monitoring applications. In this paper, we introduce an enhanced guaranteed timeslot (GTS) mechanism which can support time-critical P2P communications in wireless sensor networks (WSNs). A Markov chain that takes into account retransmission limits, acknowledgements, unsaturated traffic and packet delivery ratios of links is proposed to model P2P communications using this enhanced GTS mechanism. Based on this model, we analyze the expected reliability and energy consumptions under various traffic conditions. In addition, the impacts of MAC parameters on these performance indexes are analyzed. Monte Carlo simulations show that our theoretical analysis is quite accurate, and thus can be used as guidance for networks configuration in WSNs.},
	address = {Kyoto, Japan},
	booktitle = {IEEE International Conference on Communications (ICC 2011)},
	pages = {pp. 1-6}
}
@conference {
	title = {Exploiting Trust Relations for Nash Equilibrium Efficiency in Ad Hoc Networks},
	author = {Zheng, Shanshan., Jiang, Tao., Baras, John S.},
	year = {2011},
	month = {06/2011},
	abstract = {Ad hoc networks rely on the mutual cooperation among individual nodes to achieve network-wide objectives. However, individual nodes may behave selfishly in order to maximize their own benefits without considering the global benefits of the network. One approach to incentivize nodes cooperation for better global benefits is to establish trust relations among nodes to guide their decision making. In this paper, we present a game theoretic analysis for the efficiency of establishing trust for improving node cooperation. The trust relations among nodes are modeled as a trust-weighted network, and we study a graphical game in this network where the nodes{\textquoteright} payoffs are affected by their trust relations. We characterize the Nash equilibrium and the social optimum of this game and show that the game efficiency has a close relationship to the Bonacich centralities of nodes in the trust-weighted network. Furthermore, we propose to improve game efficiency by introducing heterogeneous resources to nodes according to their centralities. We provide both experimental and theoretical analysis on the improvement of the game efficiency.},
	address = {Kyoto, Japan},
	booktitle = {IEEE International Conference on Communications (ICC 2011)},
	pages = {pp.1-5}
}
@conference {
	title = {A Robust Collaborative Filtering Algorithm Using Ordered Logistic Regression},
	author = {Zheng, Shanshan., Jiang, Tao., Baras, John S.},
	year = {2011},
	month = {06/2011},
	abstract = {The Internet offers tremendous opportunities for information sharing and content distribution. However, without proper filtering and selection, the large amount of information may likely swarm the users rather than benefit them. Collaborative filtering is a technique for extracting useful information from the large information pool generated by interconnected online communities. In this paper, we develop a probabilistic collaborative filtering algorithm, which is based on ordered logistic regression and takes into account both similarities among the users and similarities among the items. We make inference with maximum likelihood and Bayesian frameworks, and propose a Markov Chain Monte Carlo based Expectation Maximization algorithm to optimize model parameters. The power of our proposed algorithm is its extensibility. We show that it can incorporate content and contextual information. More importantly, it can be easily extended to include the trustworthiness of users, thus being more robust to malicious data manipulation. The experimental results on a real world data set show that our proposed algorithm with the trust extension is robust under different types of attacks in recommendation systems.},
	address = {Kyoto, Japan},
	booktitle = {IEEE International Conference on Communications (ICC 2011)},
	pages = {pp. 1-6}
}
