2 research outputs found
Maximum Weight Disjoint Paths in Outerplanar Graphs via Single-Tree Cut Approximators
Since 1997 there has been a steady stream of advances for the maximum
disjoint paths problem. Achieving tractable results has usually required
focusing on relaxations such as: (i) to allow some bounded edge congestion in
solutions, (ii) to only consider the unit weight (cardinality) setting, (iii)
to only require fractional routability of the selected demands (the
all-or-nothing flow setting). For the general form (no congestion, general
weights, integral routing) of edge-disjoint paths ({\sc edp}) even the case of
unit capacity trees which are stars generalizes the maximum matching problem
for which Edmonds provided an exact algorithm. For general capacitated trees,
Garg, Vazirani, Yannakakis showed the problem is APX-Hard and Chekuri, Mydlarz,
Shepherd provided a -approximation. This is essentially the only setting
where a constant approximation is known for the general form of \textsc{edp}.
We extend their result by giving a constant-factor approximation algorithm for
general-form \textsc{edp} in outerplanar graphs. A key component for the
algorithm is to find a {\em single-tree} cut approximator for
outerplanar graphs. Previously cut approximators were only known via
distributions on trees and these were based implicitly on the results of Gupta,
Newman, Rabinovich and Sinclair for distance tree embeddings combined with
results of Anderson and Feige.Comment: 19 pages, 6 figure
Maximizing Routing Throughput with Applications to Delay Tolerant Networks
abstract: Many applications require efficient data routing and dissemination in Delay Tolerant Networks (DTNs) in order to maximize the throughput of data in the network, such as providing healthcare to remote communities, and spreading related information in Mobile Social Networks (MSNs). In this thesis, the feasibility of using boats in the Amazon Delta Riverine region as data mule nodes is investigated and a robust data routing algorithm based on a fountain code approach is designed to ensure fast and timely data delivery considering unpredictable boat delays, break-downs, and high transmission failures. Then, the scenario of providing healthcare in Amazon Delta Region is extended to a general All-or-Nothing (Splittable) Multicommodity Flow (ANF) problem and a polynomial time constant approximation algorithm is designed for the maximum throughput routing problem based on a randomized rounding scheme with applications to DTNs. In an MSN, message content is closely related to users’ preferences, and can be used to significantly impact the performance of data dissemination. An interest- and content-based algorithm is developed where the contents of the messages, along with the network structural information are taken into consideration when making message relay decisions in order to maximize data throughput in an MSN. Extensive experiments show the effectiveness of the above proposed data dissemination algorithm by comparing it with state-of-the-art techniques.Dissertation/ThesisDoctoral Dissertation Computer Science 201