New Algorithmic Approaches for Computing Optimal Network Paths with Several Types of QoS Constraints

Network Resilience Assessment via QoS Degradation Metrics: An Algorithmic Approach

This paper focuses on network resilience to perturbation of edge weight. Other than connectivity, many network applications nowadays rely upon some measure of network distance between a pair of connected nodes. In these systems, a metric related to network functionality is associated to each edge. A pair of nodes only being functional if the weighted, shortest-path distance between the pair is below a given threshold \texttt{T}. Consequently, a natural question is on which degree the change of edge weights can damage the network functionality? With this motivation, we study a new problem, \tex…

Offline Algorithms for Several Network Design, Clustering and QoS Optimization Problems

In this paper we address several network design, clustering and Quality of Service (QoS) optimization problems and present novel, efficient, offline algorithms which compute optimal or near-optimal solutions. The QoS optimization problems consist of reliability improvement (by computing backup shortest paths) and network link upgrades (in order to reduce the latency on several paths). The network design problems consist of determining small diameter networks, as well as very well connected and regular network topologies. The network clustering problems consider only the restricted model of sta…

Planar Maximum Coverage Location Problem with Partial Coverage, Continuous Spatial Demand, and Adjustable Quality of Service

We consider a generalization of the classical planar maximum coverage location problem (PMCLP) in which partial coverage is allowed, facilities have adjustable quality of service (QoS) or service range, and demand zones and service zone of each facility are represented by two-dimensional spatial objects such as rectangles, circles, polygons, etc. We denote this generalization by PMCLP-PC-QoS. A key challenge in this problem is to simultaneously decide position of the facilities on a continuous two-dimensional plane and their QoS. We present a greedy algorithm and a pseudo-greedy algorithm for …

Computing Sparse Jacobians and Hessians Using Algorithmic Differentiation

Stochastic scientific models and machine learning optimization estimators have a large number of variables; hence computing large sparse Jacobians and Hessians is important. Algorithmic differentiation (AD) greatly reduces the programming effort required to obtain the sparsity patterns and values for these matrices. We present forward, reverse, and subgraph methods for computing sparse Jacobians and Hessians. Special attention is given the the subgraph method because it is new. The coloring and compression steps are not necessary when computing sparse Jacobians and Hessians using subgraphs. Co…

计算圆交叠面积的算法解决方案及其在无线通信中的应用

An Algorithmic Solution for Computing Circle Intersection Areas and its Applications to Wireless Communications

本文提出一种基于网格结构的迭代算法，通过代数运算高效计算任意数量圆的交叠面积，并应用于无线网络中上行链路中断概率的分析。

Efficient Offline Algorithmic Techniques for Several Packet Routing Problems in Distributed Systems

In this paper we consider several problems concerning packet routing in distributed systems. Each problem is formulated using terms from Graph Theory and for each problem we present efficient, novel, algorithmic techniques for computing optimal solutions. We address topics like: bottleneck paths (trees), optimal paths with non-linear costs, optimal paths with multiple optimization objectives, maintaining aggregate connectivity information under a sequence of network link failures, and several others.