> TITLE: Perspectives on Secure Wireless Networks and Efficient Energy  
> Replenishing Sensor Networks

> ABSTRACT: This talk is composed of two separate parts. In the first  
> part of the talk, we will focus on a random extended network, where  
> the legitimate and eavesdropper nodes are assumed to be placed  
> according to Poisson point processes in a square region of area n.  
> We show that, when the legitimate nodes have a unit intensity and  
> the eavesdroppers have an intensity of O((log n)^-2), almost all of  
> the nodes achieve a perfectly secure rate of O(1/sqrt(n)). The  
> achievability argument is based on a novel multi-hop forwarding  
> scheme where randomization is added in every hop to ensure maximal  
> ambiguity at the eavesdropper(s). Remarkably, under these  
> assumptions, securing the transmissions of nodes does not entail a  
> loss in the per-node throughput in terms of scaling.

> In the second part of the talk, we study sensor networks with nodes,  
> which have rechargable energy sources. In order to achieve a  
> perpetual network operation, the energy consumption rate at each  
> node cannot be higher than the energy harvesting rate. Otherwise,  
> the node will frequently deplete its battery and block critical  
> network functions. In this talk, we consider the problem of optimal  
> alloction of sampling rates, routing and congestion control in such  
> networks. In contrast to traditional network resource allocation  
> problems where the resources are static, the time-varying recharging  
> rate presents new challenges. Fluctuations in recharging can happen  
> at a faster time-scale than the convergence time of classical dual  
> decomposition and subgradient based algorithms. To address this  
> issue, we propose two algorithms, QuickFix and SnapIt, which run in  
> parallel to achieve a performance, close to the optimal and at the  
> same time keep the batteries at at a target level. Our evaluations  
> show that, QuickFix and SnapIt working in tandem achieves a sampling  
> rate, 42% higher compared to IFRC, a standard back-pressure based  
> algorithm.

> BIO: C. Emre Koksal received the B.S. degree in electrical  
> engineering from the Middle East Technical University, Ankara,  
> Turkey, in 1996, and the S.M. and Ph.D. degrees from the  
> Massachusetts Institute of Technology (MIT), Cambridge, in 1998 and  
> 2002, respectively, in electrical engineering and computer science.  
> He was a Postdoctoral Fellow in the Networks and Mobile Systems  
> Group in the Computer Science and Artificial Intelligence  
> Laboratory, MIT, until 2003 and a Senior Researcher jointly in the  
> Laboratory for Computer Communications and the Laboratory for  
> Information Theory at EPFL, Lausanne, Switzerland, until 2006. Since  
> then, he has been an Assistant Professor in the Electrical and  
> Computer Engineering Department, Ohio State University, Columbus,  
> Ohio. His general areas of interest are wireless communication,  
> communication networks, information theory, stochastic processes,  
> and financial economics.