22,559 research outputs found
Towards Scalable Network Delay Minimization
Reduction of end-to-end network delays is an optimization task with
applications in multiple domains. Low delays enable improved information flow
in social networks, quick spread of ideas in collaboration networks, low travel
times for vehicles on road networks and increased rate of packets in the case
of communication networks. Delay reduction can be achieved by both improving
the propagation capabilities of individual nodes and adding additional edges in
the network. One of the main challenges in such design problems is that the
effects of local changes are not independent, and as a consequence, there is a
combinatorial search-space of possible improvements. Thus, minimizing the
cumulative propagation delay requires novel scalable and data-driven
approaches.
In this paper, we consider the problem of network delay minimization via node
upgrades. Although the problem is NP-hard, we show that probabilistic
approximation for a restricted version can be obtained. We design scalable and
high-quality techniques for the general setting based on sampling and targeted
to different models of delay distribution. Our methods scale almost linearly
with the graph size and consistently outperform competitors in quality
Travelling on Graphs with Small Highway Dimension
We study the Travelling Salesperson (TSP) and the Steiner Tree problem (STP)
in graphs of low highway dimension. This graph parameter was introduced by
Abraham et al. [SODA 2010] as a model for transportation networks, on which TSP
and STP naturally occur for various applications in logistics. It was
previously shown [Feldmann et al. ICALP 2015] that these problems admit a
quasi-polynomial time approximation scheme (QPTAS) on graphs of constant
highway dimension. We demonstrate that a significant improvement is possible in
the special case when the highway dimension is 1, for which we present a
fully-polynomial time approximation scheme (FPTAS). We also prove that STP is
weakly NP-hard for these restricted graphs. For TSP we show NP-hardness for
graphs of highway dimension 6, which answers an open problem posed in [Feldmann
et al. ICALP 2015]
Bicriteria Network Design Problems
We study a general class of bicriteria network design problems. A generic
problem in this class is as follows: Given an undirected graph and two
minimization objectives (under different cost functions), with a budget
specified on the first, find a <subgraph \from a given subgraph-class that
minimizes the second objective subject to the budget on the first. We consider
three different criteria - the total edge cost, the diameter and the maximum
degree of the network. Here, we present the first polynomial-time approximation
algorithms for a large class of bicriteria network design problems for the
above mentioned criteria. The following general types of results are presented.
First, we develop a framework for bicriteria problems and their
approximations. Second, when the two criteria are the same %(note that the cost
functions continue to be different) we present a ``black box'' parametric
search technique. This black box takes in as input an (approximation) algorithm
for the unicriterion situation and generates an approximation algorithm for the
bicriteria case with only a constant factor loss in the performance guarantee.
Third, when the two criteria are the diameter and the total edge costs we use a
cluster-based approach to devise a approximation algorithms --- the solutions
output violate both the criteria by a logarithmic factor. Finally, for the
class of treewidth-bounded graphs, we provide pseudopolynomial-time algorithms
for a number of bicriteria problems using dynamic programming. We show how
these pseudopolynomial-time algorithms can be converted to fully
polynomial-time approximation schemes using a scaling technique.Comment: 24 pages 1 figur
Optimal Topology Design for Disturbance Minimization in Power Grids
The transient response of power grids to external disturbances influences
their stable operation. This paper studies the effect of topology in linear
time-invariant dynamics of different power grids. For a variety of objective
functions, a unified framework based on norm is presented to analyze the
robustness to ambient fluctuations. Such objectives include loss reduction,
weighted consensus of phase angle deviations, oscillations in nodal frequency,
and other graphical metrics. The framework is then used to study the problem of
optimal topology design for robust control goals of different grids. For radial
grids, the problem is shown as equivalent to the hard "optimum communication
spanning tree" problem in graph theory and a combinatorial topology
construction is presented with bounded approximation gap. Extended to loopy
(meshed) grids, a greedy topology design algorithm is discussed. The
performance of the topology design algorithms under multiple control objectives
are presented on both loopy and radial test grids. Overall, this paper analyzes
topology design algorithms on a broad class of control problems in power grid
by exploring their combinatorial and graphical properties.Comment: 6 pages, 3 figures, a version of this work will appear in ACC 201
Efficient Wireless Security Through Jamming, Coding and Routing
There is a rich recent literature on how to assist secure communication
between a single transmitter and receiver at the physical layer of wireless
networks through techniques such as cooperative jamming. In this paper, we
consider how these single-hop physical layer security techniques can be
extended to multi-hop wireless networks and show how to augment physical layer
security techniques with higher layer network mechanisms such as coding and
routing. Specifically, we consider the secure minimum energy routing problem,
in which the objective is to compute a minimum energy path between two network
nodes subject to constraints on the end-to-end communication secrecy and
goodput over the path. This problem is formulated as a constrained optimization
of transmission power and link selection, which is proved to be NP-hard.
Nevertheless, we show that efficient algorithms exist to compute both exact and
approximate solutions for the problem. In particular, we develop an exact
solution of pseudo-polynomial complexity, as well as an epsilon-optimal
approximation of polynomial complexity. Simulation results are also provided to
show the utility of our algorithms and quantify their energy savings compared
to a combination of (standard) security-agnostic minimum energy routing and
physical layer security. In the simulated scenarios, we observe that, by
jointly optimizing link selection at the network layer and cooperative jamming
at the physical layer, our algorithms reduce the network energy consumption by
half
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