Communication networks are vulnerable to natural as well as man-made disasters. The geographical layout of the network influences the impact of these disasters. It is therefore, necessary to identify areas that could be most affected by a disaster and redesign those parts of the network so that the impact of a disaster has least effect on them. In this work, we assume that disasters which have a circular impact on the network. The work presents two new algorithms, namely the WHF-PG algorithm and the WHF-NPG algorithm, designed to solve the problem of finding the locations of disasters that would have the maximum disruptive effect on the communication infrastructure in terms of capacity.

We focus on the two overlapping areas of preference queries and dataset summarization. A (linear) preference query specifies the relative importance of the attributes in a dataset and asks for the tuples that best match those preferences. Dataset summarization is the task of representing an entire dataset by a small, representative subset. Within these areas, we focus on three important sub-problems, significantly advancing the state-of-the-art in each. We begin with an investigation into a new formulation of preference queries, identifying a neglected and important subclass that we call threshold projection queries. While literature typically constrains the attribute preferences (which are real-valued weights) such that their sum is one, we show that this introduces bias when querying by threshold rather than cardinality. Using projection, rather than inner product as in that literature, removes the bias. We then give algorithms for building and querying indices for this class of query, based, in the general case, on geometric duality and halfspace range searching, and, in an important special case, on stereographic projection. In the second part of the dissertation, we investigate the monochromatic reverse top-k (mRTOP) query in two dimensions. A mRTOP query asks for, given a tuple and a dataset, the linear preference queries on the dataset that will include the given tuple. Towards this goal, we consider the novel scenario of building an index to support mRTOP queries, using geometric duality and plane sweep. We show theoretically and empirically that the index is quick to build, small on disk, and very efficient at answering mRTOP queries. As a corollary to these efforts, we defined the top-k rank contour, which encodes the k-ranked tuple for every possible linear preference query. This is tremendously useful in answering mRTOP queries, but also, we posit, of significant independent interest for its relation to myriad related linear preference query problems. Intuitively, the top-k rank contour is the minimum possible representation of knowledge needed to identify the k-ranked tuple for any query, without apriori knowledge of that query. We also introduce k-regret minimizing sets, a very succinct approximation of a numeric dataset. The purpose of the approximation is to represent the entire dataset by just a small subset that nonetheless will contain a tuple within or near to the top-k for any linear preference query. We show that the problem of finding k-regret minimizing sets—and, indeed, the problem in literature that it generalizes—is NP-Hard. Still, for the special case of two dimensions, we provide a fast, exact algorithm based on the top-k rank contour. For arbitrary dimension, we introduce a novel greedy algorithm based on linear programming and randomization that does excellently in our empirical investigation. / Graduate / 0984

在無線網狀網路(Wireless Mesh Network)中，每個節點須幫助相鄰節點轉送資料及提供使用者網路存取，例如WLAN(IEEE 802.11s)、WMAN(IEEE 802.16)等，皆可利用多跳接方式將資料轉送至通訊閘道器(Gateway)。在無線網狀網路中，常利用密集佈建的方式來解決通訊死角的問題。當網路節點的密度增加時，無線訊號的干擾也會增強，並且各節點的效能會顯著下降。 在本研究中，將利用幾何學概念，解決網路干擾問題，並提出拓樸重建演算法來重建路徑，使網路干擾達到最小化。我們試著最小化節點與節點間的干擾，以提升整體無線網狀網路效能。我們將網路問題轉換成幾何問題，並定義在幾何圖形中線段交錯問題，之後驗證在幾何圖形中是否有線段交錯的現象發生。若發生線段交錯時，則將此線段從幾何圖形中移除，並且利用三角化演算法將此區域線段重新規劃，使相鄰節點間的干擾最小。當網路拓樸建立完成後，我們利用標準差公式將干擾較大的連線移除，使得網路效能提升。上述測試線段交錯及三角化多邊形演算法可在時間複雜度O(n log n)內找到干擾最小的解。最後，我們將利用網路模擬器(Network Simulator)驗證所提出的方法是否能達到預期的系統效能指標。 / In wireless mesh networks, such as WLAN (IEEE 802.11s), WMAN (IEEE 802.16), etc., each node should forward packets of neighboring nodes toward gateway using multi-hop routing mechanism. In wireless mesh network, as the density of network nodes increases, the RF interference will increase and the throughput of each node will drop rapidly. In our research, we use the geometry to resolve the RF interference problem by rebuilding network topology. We try to minimize the interference between neighboring nodes and improve the throughput in wireless mesh network. We transform the network topology problem into geometry problem and define the line intersection problem in geometric graph, then check path intersection in the geometric graph. If line intersection occurs in the graph, we remove the intersection line from the graph and re-plan the region by triangulation algorithm. When the network topology is built up, we use a standard deviation formula to improve network performance by removing longer links. The line intersection algorithm and triangulation algorithm, both of time complexity O(n log n), are used to find the minimal interference solution. At the end of our research, we use network simulator to verify if the proposed methods can help to meet all those performance expectations.