2 resultados para resource management
em DRUM (Digital Repository at the University of Maryland)
Resumo:
The Archaeological Reconnaissance Survey of United States Naval Academy will provide the Navy with a rich understanding of the history of this property. A National Register of Historic Places District, such as the Academy, deserves a thorough analysis of its past, in order to preserve what exists and to plan for the future. The goal of this project is to investigate the history of the Academy through traditional historic research, innovative computer analysis of historic maps, oral history interviews, and tract histories. This information has been synthesized to provide the Navy with a planning tool for Public Works, a concise look at the cartographic history of the Academy, and reference manual of the vast amounts of information which have been gathered during the course of this project. This information can serve as a reference tool to help the Public Works department comply with Section 106 regulations of the Historic Sites Preservation Act, with regard to construction. It can also serve as a source of cartographic history for those interested in the Academy's physical development, and as a way of preserving the culture of residents in Annapolis. This program and archaeological survey will ultimately serve to add to the rich history of the United States Naval Academy while preserving an important part of our nation's heritage.
Resumo:
Deployment of low power basestations within cellular networks can potentially increase both capacity and coverage. However, such deployments require efficient resource allocation schemes for managing interference from the low power and macro basestations that are located within each other’s transmission range. In this dissertation, we propose novel and efficient dynamic resource allocation algorithms in the frequency, time and space domains. We show that the proposed algorithms perform better than the current state-of-art resource management algorithms. In the first part of the dissertation, we propose an interference management solution in the frequency domain. We introduce a distributed frequency allocation scheme that shares frequencies between macro and low power pico basestations, and guarantees a minimum average throughput to users. The scheme seeks to minimize the total number of frequencies needed to honor the minimum throughput requirements. We evaluate our scheme using detailed simulations and show that it performs on par with the centralized optimum allocation. Moreover, our proposed scheme outperforms a static frequency reuse scheme and the centralized optimal partitioning between the macro and picos. In the second part of the dissertation, we propose a time domain solution to the interference problem. We consider the problem of maximizing the alpha-fairness utility over heterogeneous wireless networks (HetNets) by jointly optimizing user association, wherein each user is associated to any one transmission point (TP) in the network, and activation fractions of all TPs. Activation fraction of a TP is the fraction of the frame duration for which it is active, and together these fractions influence the interference seen in the network. To address this joint optimization problem which we show is NP-hard, we propose an alternating optimization based approach wherein the activation fractions and the user association are optimized in an alternating manner. The subproblem of determining the optimal activation fractions is solved using a provably convergent auxiliary function method. On the other hand, the subproblem of determining the user association is solved via a simple combinatorial algorithm. Meaningful performance guarantees are derived in either case. Simulation results over a practical HetNet topology reveal the superior performance of the proposed algorithms and underscore the significant benefits of the joint optimization. In the final part of the dissertation, we propose a space domain solution to the interference problem. We consider the problem of maximizing system utility by optimizing over the set of user and TP pairs in each subframe, where each user can be served by multiple TPs. To address this optimization problem which is NP-hard, we propose a solution scheme based on difference of submodular function optimization approach. We evaluate our scheme using detailed simulations and show that it performs on par with a much more computationally demanding difference of convex function optimization scheme. Moreover, the proposed scheme performs within a reasonable percentage of the optimal solution. We further demonstrate the advantage of the proposed scheme by studying its performance with variation in different network topology parameters.