859 research outputs found
Solving the undirected feedback vertex set problem by local search
An undirected graph consists of a set of vertices and a set of undirected
edges between vertices. Such a graph may contain an abundant number of cycles,
then a feedback vertex set (FVS) is a set of vertices intersecting with each of
these cycles. Constructing a FVS of cardinality approaching the global minimum
value is a optimization problem in the nondeterministic polynomial-complete
complexity class, therefore it might be extremely difficult for some large
graph instances. In this paper we develop a simulated annealing local search
algorithm for the undirected FVS problem. By defining an order for the vertices
outside the FVS, we replace the global cycle constraints by a set of local
vertex constraints on this order. Under these local constraints the cardinality
of the focal FVS is then gradually reduced by the simulated annealing dynamical
process. We test this heuristic algorithm on large instances of Er\"odos-Renyi
random graph and regular random graph, and find that this algorithm is
comparable in performance to the belief propagation-guided decimation
algorithm.Comment: 6 page
Minimum Cost Integral Network Coding
In this paper, we consider finding a minimum cost multicast subgraph with network coding, where the rate to inject packets on each link is constrained to be integral. In the usual minimum cost network coding formulation, the optimal solution cannot always be integral. Fractional rates can be well approximated by choosing the time unit large enough, but this increases the encoding and decoding complexity as well as delay at the terminals. We formulate this problem as an integer program, which is NP-hard. A greedy algorithm and an algorithm based on linear programming rounding are proposed, which have approximation ratios k and 2k respectively, where k is the number of sinks. Moreover, both algorithms can be decentralized. We show by simulation that our algorithms' average performance substantially exceeds their bounds on random graphs
Networking - A Statistical Physics Perspective
Efficient networking has a substantial economic and societal impact in a
broad range of areas including transportation systems, wired and wireless
communications and a range of Internet applications. As transportation and
communication networks become increasingly more complex, the ever increasing
demand for congestion control, higher traffic capacity, quality of service,
robustness and reduced energy consumption require new tools and methods to meet
these conflicting requirements. The new methodology should serve for gaining
better understanding of the properties of networking systems at the macroscopic
level, as well as for the development of new principled optimization and
management algorithms at the microscopic level. Methods of statistical physics
seem best placed to provide new approaches as they have been developed
specifically to deal with non-linear large scale systems. This paper aims at
presenting an overview of tools and methods that have been developed within the
statistical physics community and that can be readily applied to address the
emerging problems in networking. These include diffusion processes, methods
from disordered systems and polymer physics, probabilistic inference, which
have direct relevance to network routing, file and frequency distribution, the
exploration of network structures and vulnerability, and various other
practical networking applications.Comment: (Review article) 71 pages, 14 figure
Near-linear Time Algorithm for Approximate Minimum Degree Spanning Trees
Given a graph , we wish to compute a spanning tree whose maximum
vertex degree, i.e. tree degree, is as small as possible. Computing the exact
optimal solution is known to be NP-hard, since it generalizes the Hamiltonian
path problem. For the approximation version of this problem, a
time algorithm that computes a spanning tree of degree at most is
previously known [F\"urer \& Raghavachari 1994]; here denotes the
minimum tree degree of all the spanning trees. In this paper we give the first
near-linear time approximation algorithm for this problem. Specifically
speaking, we propose an time algorithm that
computes a spanning tree with tree degree for any constant .
Thus, when , we can achieve approximate solutions with
constant approximate ratio arbitrarily close to 1 in near-linear time.Comment: 17 page
Analysis and optimization of highly reliable systems
In the field of network design, the survivability property enables the network to maintain a certain level of network connectivity and quality of service under failure conditions. In this thesis, survivability aspects of communication systems are studied. Aspects of reliability and vulnerability of network design are also addressed. The contributions are three-fold. First, a Hop Constrained node Survivable Network Design Problem (HCSNDP) with optional (Steiner) nodes is modelled. This kind of problems are N P-Hard. An exact integer linear model is built, focused on networks represented by graphs without rooted demands, considering costs in arcs and in Steiner nodes. In addition to the exact model, the calculation of lower and upper bounds to the optimal solution is included. Models were tested over several graphs and instances, in order to validate it in cases with known solution. An Approximation Algorithm is also developed in order to address a particular case of SNDP: the Two Node Survivable Star Problem (2NCSP) with optional nodes. This problem belongs to the class of N P-Hard computational problems too. Second, the research is focused on cascading failures and target/random attacks. The Graph Fragmentation Problem (GFP) is the result of a worst case analysis of a random attack. A fixed number of individuals for protection can be chosen, and a non-protected target node immediately destroys all reachable nodes. The goal is to minimize the expected number of destroyed nodes in the network. This problem belongs to the N P-Hard class. A mathematical programming formulation is introduced and exact resolution for small instances as well as lower and upper bounds to the optimal solution. In addition to exact methods, we address the GFP by several approaches: metaheuristics, approximation algorithms, polytime methods for specific instances and exact methods in exponential time. Finally, the concept of separability in stochastic binary systems is here introduced. Stochastic Binary Systems (SBS) represent a mathematical model of a multi-component on-off system subject to independent failures. The reliability evaluation of an SBS belongs to the N P-Hard class. Therefore, we fully characterize separable systems using Han-Banach separation theorem for convex sets. Using this new concept of separable systems and Markov inequality, reliability bounds are provided for arbitrary SBS
Performance improvement of an optical network providing services based on multicast
Operators of networks covering large areas are confronted with demands from
some of their customers who are virtual service providers. These providers may
call for the connectivity service which fulfils the specificity of their
services, for instance a multicast transition with allocated bandwidth. On the
other hand, network operators want to make profit by trading the connectivity
service of requested quality to their customers and to limit their
infrastructure investments (or do not invest anything at all).
We focus on circuit switching optical networks and work on repetitive
multicast demands whose source and destinations are {\em \`a priori} known by
an operator. He may therefore have corresponding trees "ready to be allocated"
and adapt his network infrastructure according to these recurrent
transmissions. This adjustment consists in setting available branching routers
in the selected nodes of a predefined tree. The branching nodes are
opto-electronic nodes which are able to duplicate data and retransmit it in
several directions. These nodes are, however, more expensive and more energy
consuming than transparent ones.
In this paper we are interested in the choice of nodes of a multicast tree
where the limited number of branching routers should be located in order to
minimize the amount of required bandwidth. After formally stating the problem
we solve it by proposing a polynomial algorithm whose optimality we prove. We
perform exhaustive computations to show an operator gain obtained by using our
algorithm. These computations are made for different methods of the multicast
tree construction. We conclude by giving dimensioning guidelines and outline
our further work.Comment: 16 pages, 13 figures, extended version from Conference ISCIS 201
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