Surging data demand driven by the proliferation of smartphones is revolutionizing the wire- less scene. By 2020, the number of smartphone subscribers will grow to 9 billion and the demand in mobile data traffic will grow 10 folds. Capacity (bandwidth) and Latency are the key contributing factors to a positive user experience. For example, streaming a video from Netflix or Youtube is bandwidth limited while loading or browsing the Youtube or Net- flix website is latency limited. One can argue that by using more spectrum(wider wireless channels) can solve the capacity problem however according to Federal Communications Commission(FCC) we are already facing a spectrum deficit. Newer network technologies like 4G and LTE have improved the network performance(both capacity and latency) but 60world’s mobile subscribers will still be using the slower 3G or 2G connections for at least a decade. Another challenge that mobile devices are posing is that the networks previously dominated by the static users (or static channel conditions) with devices like laptops are increasingly becoming more heterogeneous( mix of static and mobile users with varying channel conditions).

In this dissertation, I address the issue of managing wireless resources to support various multimedia applications, in wireless networks with a high degree of user mobility. Driven by necessity for flexible wireless resource management, I design, build and eval- uate three wireless resource management schemes. First, I present JPRA, a joint power and rate adaptation scheme which adaptively distributes uneven power levels of OFDMA sub-carriers to cope with frequency selectivity in fading. Thus, improves the total network capacity. Second, I present TRINITY, a practical transmitter cooperation scheme to handle heterogeneous user profiles in wireless networks. Sophisticated MIMO-based transmission strategies, based on transmitter cooperation, have emerged recently. However, different types of users profiles (e.g., static vs mobile, stable vs dynamic channels) that make up todays enterprises, require different MIMO transmission strategies(CMSA, Network MIMO and DAS). With the wrong strategy, a user could even see a degradation in performance. TRINITY can simultaneously cater to a heterogeneous mix of users, by intelligently com- bining a plurality of MIMO transmission strategies wherein the transmitters at different nodes can cooperate to deliver significant performance gains.

Next, I present FluidNet, a scalable, light-weight framework for realizing the full potential of Cloud-based radio access networks(C-RAN). Cloud-based radio access networks (C-RAN) have been proposed as a cost-efficient way of deploying small cells. In this work, we argue that the intelligent configuration of the front-haul network between the baseband processing units(BBUs) and remote radio heads, is essential in delivering the performance and energy benefits to the RAN and the BBU pool, respectively. FluidNet deploys a logically re-configurable front-haul to apply appropriate transmission strategies in different parts of the network and hence cater effectively to both heterogeneous user profiles and dynamic traffic load patterns.

Finally, I present FlexiWeb, a network aware compaction scheme for accelerat- ing mobile web transfers. Latency is often cited as the main reason for poor mobile web performance and to reduce the page load times, middleboxes that compress page content are commonly used today. Unfortunately, this can hurt performance in many cases. Our measurements reveal that the middlebox should be used only when network conditions are bad; otherwise, most objects in the web page should be directly fetched from the source web server. Based on this observation we build FlexiWeb, a framework that supports network- aware middlebox usage and performs dynamic network-aware compression to provide further performance gains.

We experimentally demonstrate the presence of negative refraction on acoustic passbands of two-dimensional phononic crystals for the in-plane and the anti-plane shear waves. We investigate the phenomenon on two geometrically identical two-phase crystals of different material properties, i.e., one stiff crystal (Aluminum matrix with PMMA inclusions), and another a soft crystal (PMMA matrix with Aluminum inclusions). We demonstrate that in the case of in-plane shear wave, the soft crystal does not show negative refraction in the first passband, however, the stiff crystal does show negative refraction for the first mode. In the case of the anti-plane shear wave tests, both crystals show only positive refraction in the first passband. However, in the soft crystal, negative refraction is present in the second passband. We also investigate and show that for the longitudinal mode (second acoustic passband), both stiff and soft crystals, exhibit negative refraction. The experimental results confirm the prediction of our theoretical model, which allows us to predict the behaviors of phononic crystals as we change the properties of their constituents.

In the second part of this dissertation, by the application of Noether’s theorem, conservation laws in linear elastodynamics are derived by invariance of the Lagrangean functional under a class of infinitesimal transformations. The work of Gupta and Markesncoff (2012), which provides a physical meaning to the dynamic J-integral as the variation of the Hamiltonian of the system due to an infinitesimal translation of the inhomogeneity if linear momentum is conserved in the domain, is extended here to the dynamic M- and L- integrals in terms of the ‘if’ conditions. We show that the variation of the Lagrangean is equal to the negative of the variation of the Hamiltonian under the above transformations for inhomogeneities, and hence provide a physical meaning to the dynamic J-, L- and M-integrals as dissipative mechanisms in elastodynamics. We prove that if linear momentum is conserved in the domain, the total energy loss of the system per unit scaling under the infinitesimal scaling transformation of the inhomogeneity is equal to the dynamic M-integral. Moreover, if linear and angular momenta are conserved, the total energy loss of the system per unit rotation under the infinitesimal rotational transformation is equal to the dynamic L-integral.

The central goal of this research is to develop a systematic framework and the support tools to ease, streamline and speed up the calibration of micro simulation projects. Part III of the final report documents the accomplishments achieved in the second phase of the research project. They include the following.

First, to overcome the lengthy time it takes for GA to obtain local and global driving behavior modeling parameters, we implemented a faster heuristic optimization technique, the simultaneous perturbation stochastic approximation (SPSA) and compared its performance with other heuristic optimization methods. Results indicate that SPSA can achieve comparable calibration accuracy with much less computational time than the often used Genetic Algorithm (GA) method.

Second, we developed a much faster O-D estimation tool to obtain an initial time-dependent O-D trip table. This O-D trip table can be used as a seed table in Paramics’ own O-D estimator for further refinement, or directly used in a micro simulation. In either case, the estimation time of O-D trip tables can be considerably shortened. Since our O-D estimation tool makes use of a macroscopic traffic model (logit path flow estimator, or LPFE), a network conversion tool is therefore developed to convert Paramics’s detailed network settings to those of LPFE and vice versa.

Third, we enhanced the vehicle actuated signal control APIs in Paramics, making it more versatile to implement and simulate various types of actuated traffic control strategies found in practice. We also developed a set of guidelines to help micro simulation users to set up and check signal settings in a micro simulation project.

Finally, we developed a summary statistics tools to track, diagnose and report on the calibration as it progresses or after it terminates, and carried out a case study using the SR-41 network in Fresno to demonstrate the use of the developed tools, identify potential problems and summarizing our calibration experiences with large scale networks.

Our case study indicates that the developed calibration tools can indeed ease, streamline and speed up the calibration of micro simulation, particularly when the network concerned is large. It also reveals that the calibration of a micro simulation is a complex task that involves numerous engineering judgments and cannot be fully automated. In a micro simulation, every modeling detail matters and each must be treated properly to ensure a good simulation outcome.