4,115 research outputs found
Resilient Backhaul Network Design Using Hybrid Radio/Free-Space Optical Technology
The radio-frequency (RF) technology is a scalable solution for the backhaul
planning. However, its performance is limited in terms of data rate and
latency. Free Space Optical (FSO) backhaul, on the other hand, offers a higher
data rate but is sensitive to weather conditions. To combine the advantages of
RF and FSO backhauls, this paper proposes a cost-efficient backhaul network
using the hybrid RF/FSO technology. To ensure a resilient backhaul, the paper
imposes a given degree of redundancy by connecting each node through
link-disjoint paths so as to cope with potential link failures. Hence, the
network planning problem considered in this paper is the one of minimizing the
total deployment cost by choosing the appropriate link type, i.e., either
hybrid RF/FSO or optical fiber (OF), between each couple of base-stations while
guaranteeing link-disjoint connections, a data rate target, and a
reliability threshold. The paper solves the problem using graph theory
techniques. It reformulates the problem as a maximum weight clique problem in
the planning graph, under a specified realistic assumption about the cost of OF
and hybrid RF/FSO links. Simulation results show the cost of the different
planning and suggest that the proposed heuristic solution has a
close-to-optimal performance for a significant gain in computation complexity
A Tutorial on Clique Problems in Communications and Signal Processing
Since its first use by Euler on the problem of the seven bridges of
K\"onigsberg, graph theory has shown excellent abilities in solving and
unveiling the properties of multiple discrete optimization problems. The study
of the structure of some integer programs reveals equivalence with graph theory
problems making a large body of the literature readily available for solving
and characterizing the complexity of these problems. This tutorial presents a
framework for utilizing a particular graph theory problem, known as the clique
problem, for solving communications and signal processing problems. In
particular, the paper aims to illustrate the structural properties of integer
programs that can be formulated as clique problems through multiple examples in
communications and signal processing. To that end, the first part of the
tutorial provides various optimal and heuristic solutions for the maximum
clique, maximum weight clique, and -clique problems. The tutorial, further,
illustrates the use of the clique formulation through numerous contemporary
examples in communications and signal processing, mainly in maximum access for
non-orthogonal multiple access networks, throughput maximization using index
and instantly decodable network coding, collision-free radio frequency
identification networks, and resource allocation in cloud-radio access
networks. Finally, the tutorial sheds light on the recent advances of such
applications, and provides technical insights on ways of dealing with mixed
discrete-continuous optimization problems
Hybrid Radio/Free-Space Optical Design for Next Generation Backhaul Systems
The deluge of date rate in today's networks imposes a cost burden on the
backhaul network design. Developing cost efficient backhaul solutions becomes
an exciting, yet challenging, problem. Traditional technologies for backhaul
networks include either radio-frequency backhauls (RF) or optical fibers (OF).
While RF is a cost-effective solution as compared to OF, it supports lower data
rate requirements. Another promising backhaul solution is the free-space optics
(FSO) as it offers both a high data rate and a relatively low cost. FSO,
however, is sensitive to nature conditions, e.g., rain, fog, line-of-sight.
This paper combines both RF and FSO advantages and proposes a hybrid RF/FSO
backhaul solution. It considers the problem of minimizing the cost of the
backhaul network by choosing either OF or hybrid RF/FSO backhaul links between
the base-stations (BS) so as to satisfy data rate, connectivity, and
reliability constraints. It shows that under a specified realistic assumption
about the cost of OF and hybrid RF/FSO links, the problem is equivalent to a
maximum weight clique problem, which can be solved with moderate complexity.
Simulation results show that the proposed solution shows a close-to-optimal
performance, especially for practical prices of the hybrid RF/FSO links
Hybrid tractability of soft constraint problems
The constraint satisfaction problem (CSP) is a central generic problem in
computer science and artificial intelligence: it provides a common framework
for many theoretical problems as well as for many real-life applications. Soft
constraint problems are a generalisation of the CSP which allow the user to
model optimisation problems. Considerable effort has been made in identifying
properties which ensure tractability in such problems. In this work, we
initiate the study of hybrid tractability of soft constraint problems; that is,
properties which guarantee tractability of the given soft constraint problem,
but which do not depend only on the underlying structure of the instance (such
as being tree-structured) or only on the types of soft constraints in the
instance (such as submodularity). We present several novel hybrid classes of
soft constraint problems, which include a machine scheduling problem,
constraint problems of arbitrary arities with no overlapping nogoods, and the
SoftAllDiff constraint with arbitrary unary soft constraints. An important tool
in our investigation will be the notion of forbidden substructures.Comment: A full version of a CP'10 paper, 26 page
Algorithms for the minimum sum coloring problem: a review
The Minimum Sum Coloring Problem (MSCP) is a variant of the well-known vertex
coloring problem which has a number of AI related applications. Due to its
theoretical and practical relevance, MSCP attracts increasing attention. The
only existing review on the problem dates back to 2004 and mainly covers the
history of MSCP and theoretical developments on specific graphs. In recent
years, the field has witnessed significant progresses on approximation
algorithms and practical solution algorithms. The purpose of this review is to
provide a comprehensive inspection of the most recent and representative MSCP
algorithms. To be informative, we identify the general framework followed by
practical solution algorithms and the key ingredients that make them
successful. By classifying the main search strategies and putting forward the
critical elements of the reviewed methods, we wish to encourage future
development of more powerful methods and motivate new applications
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