This thesis presents CraneTracker, a multi-modal sensing and communication system for monitoring migratory species at the continental level. By exploiting the robust and extensive cellular infrastructure across the continent, traditional mobile wireless sensor networks can be extended to enable

First and foremost, I would like to thank my advisor, Prof. Jennifer E. Michaels. I am most appreciative of your guidance over the last four years, from the basics of elastic waves to both short- and long-term career advice. I have grown a tremendous amount, both profes-sionally and personally, and am deeply grateful for your mentorship, patience, and support. I would also like to thank my Ph.D. committee for their valuable insight and sugges-

splitting, a factor of 10 longer than the phase diffusion time expected for a coherent state for our experimental con-ditions. The enhanced coherence time is attributed to number squeezing of the initial

It is interesting to note that as practical limita-tions were removed, several fundamental or principal limitations were established. For instance, Carnot showed that there was a fun-damental limit to how much energy could be extracted from a heat engine. Later this result was generalized to the second law of thermo-dynamics. As a result of Einstein’s special rela-tivity theory, the existence of an upper velocity limit was found. Other examples include Kelvin’s absolute zero, Heissenberg’s uncer-tainty principle and Gödel’s incompleteness theorem in mathematics. Shannon’s Channel coding theorem, which was published in 1948, seems to be the last one of such fundamental

in partial ful2llment of the requirements for the degree of

Copyright © 2012 Muhammad Hamad Alizai et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. We address the challenge of link estimation and routing over highly dynamic links, thats is, bursty links that rapidly shift between reliable and unreliable periods of transmissions. Based on significant empirical evidence of over 100,000 transmissions over each link in 802.15.4 and 802.11 testbeds, we propose two metrics, expected future transmissions (EFT) and MAC3, for runtime estimation of bursty wireless links.We introduce a bursty link estimator (BLE) that based on these twometrics, accurately estimates bursty links in the network rendering them available for data transmissions. Finally, we present bursty routing extensions (BRE): an adaptive routing strategy that uses BLE for forwarding packets over bursty links if they offer better routing progress than long-term stable links. Our evaluation, comprising experimental data from widely used IEEE 802.15.4-based testbeds, reveals an average of 19 % and a maximum of 42 % reduction in the number of transmissions when routing over long-range bursty links typically ignored by routing protocols. Additionally, we show that both BLE and BRE are not tied to any specific routing protocol and integrate seamlessly with existing routing protocols and link estimators. 1.

Abstract. We review theoretical models of individual motility as well as collective dynamics and pattern formation of active particles. We focus on simple models of active dynamics with a particular emphasis on nonlinear and stochastic dynamics of such self-propelled entities in the framework of statistical mechanics. Examples of such active units in complex physico-chemical and biological systems are chemically pow-ered nano-rods, localized patterns in reaction-diffusion system, motile cells or macroscopic animals. Based on the description of individual motion of point-like active particles by stochastic differential equations, we discuss different velocity-dependent friction functions, the impact of various types of fluctuations and calculate characteristic observ-ables such as stationary velocity distributions or diffusion coefficients. Finally, we consider not only the free and confined individual active dynamics but also different types of interaction between active par-ticles. The resulting collective dynamical behavior of large assemblies and aggregates of active units is discussed and an overview over some recent results on spatiotemporal pattern formation in such systems is given. 1

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