2007 Convocation

Prelude Music: Joanna Messer, 1997 IMSA Graduate Pledge of Allegiance & Welcome: Jonathan Koch, Student Council President; Dr. Max McGee, President; Dr. Eric McLaren, Principal Featured Piece: Joanna Messer, 1997 IMSA Graduate Keynote Speaker: Jessica Droste Yagan, Sam D. Yagan; 1995 IMSA Graduate

Effects of temporal correlations in social multiplex networks

Multi-layered networks represent a major advance in the description of natural complex systems, and their study has shed light on new physical phenomena. Despite its importance, however, the role of the temporal dimension in their structure and function has not been investigated in much detail so far. Here we study the temporal correlations between layers exhibited by real social multiplex networks. At a basic level, the presence of such correlations implies a certain degree of predictability in the contact pattern, as we quantify by an extension of the entropy and mutual information analyses proposed for the single-layer case. At a different level, we demonstrate that temporal correlations are a signature of a ‘multitasking’ behavior of network agents, characterized by a higher level of switching between different social activities than expected in a uncorrelated pattern. Moreover, temporal correlations significantly affect the dynamics of coupled epidemic processes unfolding on the network. Our work opens the way for the systematic study of temporal multiplex networks and we anticipate it will be of interest to researchers in a broad array of fields

Self-optimizing architecture for QoS provisioning in differentiated services

10.1109/ICAC.2005.57Proceedings - Second International Conference on Autonomic Computing, ICAC 20052005346-34

Adaptive QoS provisioning in wireless ad hoc Networks: A semi-MDP approach

10.1109/WCNC.2005.1424864IEEE Wireless Communications and Networking Conference, WCNC42238-224

Distributed model-free stochastic optimization in wireless sensor networks

10.1007/11776178_6Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)4026 LNCS85-10

Coordinated reinforcement learning for decentralized optimal control

10.1109/ADPRL.2007.368202Proceedings of the 2007 IEEE Symposium on Approximate Dynamic Programming and Reinforcement Learning, ADPRL 2007296-30

Connectivity in Secure Wireless Sensor Networks under Transmission Constraints (CMU-CyLab-14-003)

In wireless sensor networks (WSNs), the Eschenauer–Gligor (EG) key pre-distribution scheme is a widely recognized way to secure communications. Although the connectivity properties of secure WSNs with the EG scheme have been extensively investigated, few results address physical transmission constraints. These constraints reflect real–world implementations of WSNs in which two sensors have to be within a certain distance from each other to communicate. In this paper, we present zero–one laws for connectivity in WSNs employing the EG scheme under transmission constraints. These laws improve recent results [1], [2] significantly and help specify the critical transmission ranges for connectivity. Our analytical findings, which are also confirmed via numerical experiments, provide precise guidelines for the design of secure WSNs in practice. In addition to secure WSNs, our theoretical results are also applied to frequency hopping of wireless networks, as discussed in detail.. References: [1] B. Krishnan, A. Ganesh, and D. Manjunath. On connectivity thresholds in superposition of random key graphs on random geometric graphs. In Proc. IEEE ISIT, pages 2389–2393, 2013. [2] K. Krzywdzinski and K. Rybarczyk. Geometric graphs with randomly deleted edges — connectivity and routing protocols. Mathematical Foundations of Computer Science, 6907:544–555, 2011.</p

Results on Vertex Degree and K-Connectivity in Uniform S-Intersection Graphs (CMU-CyLab-14-004)

<p>We present results related to the vertex degree in a uniform s-intersection graph which has received much interest recently. Specifically, we derive the probability distribution for the minimum vertex degree, and show that the number of vertices with an arbitrary degree converges to a Poisson distribution. A uniform s-intersection graph models the topology of a secure wireless sensor network employing the widely used s-composite key predistribution scheme. Our theoretical findings is also confirmed by numerical results.</p