151 research outputs found
Multiple-Edge-Fault-Tolerant Approximate Shortest-Path Trees
Let be an -node and -edge positively real-weighted undirected
graph. For any given integer , we study the problem of designing a
sparse \emph{f-edge-fault-tolerant} (-EFT) {\em -approximate
single-source shortest-path tree} (-ASPT), namely a subgraph of
having as few edges as possible and which, following the failure of a set
of at most edges in , contains paths from a fixed source that are
stretched at most by a factor of . To this respect, we provide an
algorithm that efficiently computes an -EFT -ASPT of size . Our structure improves on a previous related construction designed for
\emph{unweighted} graphs, having the same size but guaranteeing a larger
stretch factor of , plus an additive term of .
Then, we show how to convert our structure into an efficient -EFT
\emph{single-source distance oracle} (SSDO), that can be built in
time, has size , and is able to report,
after the failure of the edge set , in time a
-approximate distance from the source to any node, and a
corresponding approximate path in the same amount of time plus the path's size.
Such an oracle is obtained by handling another fundamental problem, namely that
of updating a \emph{minimum spanning forest} (MSF) of after that a
\emph{batch} of simultaneous edge modifications (i.e., edge insertions,
deletions and weight changes) is performed. For this problem, we build in time a \emph{sensitivity} oracle of size , that
reports in time the (at most ) edges either exiting from
or entering into the MSF. [...]Comment: 16 pages, 4 figure
The Max-Distance Network Creation Game on General Host Graphs
In this paper we study a generalization of the classic \emph{network creation
game} in the scenario in which the players sit on a given arbitrary
\emph{host graph}, which constrains the set of edges a player can activate at a
cost of each. This finds its motivations in the physical
limitations one can have in constructing links in practice, and it has been
studied in the past only when the routing cost component of a player is given
by the sum of distances to all the other nodes. Here, we focus on another
popular routing cost, namely that which takes into account for each player its
\emph{maximum} distance to any other player. For this version of the game, we
first analyze some of its computational and dynamic aspects, and then we
address the problem of understanding the structure of associated pure Nash
equilibria. In this respect, we show that the corresponding price of anarchy
(PoA) is fairly bad, even for several basic classes of host graphs. More
precisely, we first exhibit a lower bound of
for any . Notice that this implies a counter-intuitive lower
bound of for very small values of (i.e., edges can
be activated almost for free). Then, we show that when the host graph is
restricted to be either -regular (for any constant ), or a
2-dimensional grid, the PoA is still , which is proven to be tight for
. On the positive side, if , we show
the PoA is . Finally, in the case in which the host graph is very sparse
(i.e., , with ), we prove that the PoA is , for any
.Comment: 17 pages, 4 figure
Rational Fair Consensus in the GOSSIP Model
The \emph{rational fair consensus problem} can be informally defined as
follows. Consider a network of (selfish) \emph{rational agents}, each of
them initially supporting a \emph{color} chosen from a finite set .
The goal is to design a protocol that leads the network to a stable
monochromatic configuration (i.e. a consensus) such that the probability that
the winning color is is equal to the fraction of the agents that initially
support , for any . Furthermore, this fairness property must
be guaranteed (with high probability) even in presence of any fixed
\emph{coalition} of rational agents that may deviate from the protocol in order
to increase the winning probability of their supported colors. A protocol
having this property, in presence of coalitions of size at most , is said to
be a \emph{whp\,--strong equilibrium}. We investigate, for the first time,
the rational fair consensus problem in the GOSSIP communication model where, at
every round, every agent can actively contact at most one neighbor via a
\emph{pushpull} operation. We provide a randomized GOSSIP protocol that,
starting from any initial color configuration of the complete graph, achieves
rational fair consensus within rounds using messages of
size, w.h.p. More in details, we prove that our protocol is a
whp\,--strong equilibrium for any and, moreover, it
tolerates worst-case permanent faults provided that the number of non-faulty
agents is . As far as we know, our protocol is the first solution
which avoids any all-to-all communication, thus resulting in message
complexity.Comment: Accepted at IPDPS'1
Specializations and Generalizations of the Stackelberg Minimum Spanning Tree Game
Let be given a graph whose edge set is partitioned into a set
of \emph{red} edges and a set of \emph{blue} edges, and assume that red
edges are weighted and form a spanning tree of . Then, the \emph{Stackelberg
Minimum Spanning Tree} (\stack) problem is that of pricing (i.e., weighting)
the blue edges in such a way that the total weight of the blue edges selected
in a minimum spanning tree of the resulting graph is maximized. \stack \ is
known to be \apx-hard already when the number of distinct red weights is 2. In
this paper we analyze some meaningful specializations and generalizations of
\stack, which shed some more light on the computational complexity of the
problem. More precisely, we first show that if is restricted to be
\emph{complete}, then the following holds: (i) if there are only 2 distinct red
weights, then the problem can be solved optimally (this contrasts with the
corresponding \apx-hardness of the general problem); (ii) otherwise, the
problem can be approximated within , for any .
Afterwards, we define a natural extension of \stack, namely that in which blue
edges have a non-negative \emph{activation cost} associated, and it is given a
global \emph{activation budget} that must not be exceeded when pricing blue
edges. Here, after showing that the very same approximation ratio as that of
the original problem can be achieved, we prove that if the spanning tree of red
edges can be rooted so as that any root-leaf path contains at most edges,
then the problem admits a -approximation algorithm, for any
.Comment: 22 pages, 7 figure
Multiple-Edge-Fault-Tolerant Approximate Shortest-Path Trees
Let G be an n-node and m-edge positively real-weighted undirected graph. For any given integer f >= 1, we study the problem of designing a sparse f-edge-fault-tolerant (f-EFT) sigma-approximate single-source shortest-path tree (sigma-ASPT), namely a subgraph of G having as few edges as possible and which, following the failure of a set F of at most f edges in G, contains paths from a fixed source that are stretched at most by a factor of sigma. To this respect, we provide an algorithm that efficiently computes an f-EFT (2|F|+1)-ASPT of size O(f n). Our structure improves on a previous related construction designed for unweighted graphs, having the same size but guaranteeing a larger stretch factor of 3(f+1), plus an additive term of (f+1)*log(n).
Then, we show how to convert our structure into an efficient f-EFT single-source distance oracle (SSDO), that can be built in ~{O}(f m) time, has size O(fn *log^2(n)), and is able to report, after the failure of the edge set F, in O(|F|^2 * log^2(n)) time a (2|F|+1)-approximate distance from the source to any node, and a corresponding approximate path in the same amount of time plus the path\u27s size. Such an oracle is obtained by handling another fundamental problem, namely that of updating a minimum spanning forest (MSF) of G after that a batch of k simultaneous edge modifications (i.e., edge insertions, deletions and weight changes) is performed. For this problem, we build in O(m * log^3(n)) time a sensitivity oracle of size O(m * log^2(n)), that reports in O(k^2 * log^2(n)) time the (at most 2k) edges either exiting from or entering into the MSF. As a result of independent interest, it is worth noticing that our MSF oracle can be employed to handle arbitrary sequences of o(sqrt[4]{n}/log(n)) (non-simultaneous) updates with a worst-case time per update of o(sqrt{n}). Thus, for relatively short sequences of updates, our oracle should be preferred w.r.t. the best-known (in a worst-case sense) MSF fully-dynamic algorithm, requiring O(sqrt{n}) time per update
Improved Purely Additive Fault-Tolerant Spanners
Let be an unweighted -node undirected graph. A \emph{-additive
spanner} of is a spanning subgraph of such that distances in
are stretched at most by an additive term w.r.t. the corresponding
distances in . A natural research goal related with spanners is that of
designing \emph{sparse} spanners with \emph{low} stretch.
In this paper, we focus on \emph{fault-tolerant} additive spanners, namely
additive spanners which are able to preserve their additive stretch even when
one edge fails. We are able to improve all known such spanners, in terms of
either sparsity or stretch. In particular, we consider the sparsest known
spanners with stretch , , and , and reduce the stretch to , ,
and , respectively (while keeping the same sparsity).
Our results are based on two different constructions. On one hand, we show
how to augment (by adding a \emph{small} number of edges) a fault-tolerant
additive \emph{sourcewise spanner} (that approximately preserves distances only
from a given set of source nodes) into one such spanner that preserves all
pairwise distances. On the other hand, we show how to augment some known
fault-tolerant additive spanners, based on clustering techniques. This way we
decrease the additive stretch without any asymptotic increase in their size. We
also obtain improved fault-tolerant additive spanners for the case of one
vertex failure, and for the case of edge failures.Comment: 17 pages, 4 figures, ESA 201
Nearly Linear Time Minimum Spanning TreeMaintenance for Transient Node Failures
Given a 2-node connected, real weighted, and undirected graph , with nodes and edges, and given a minimum spanning tree (MST) of , we study the problem of finding, for every node , a set of replacement edges which can be used for constructing an MST of (i.e., the graph deprived of and all its incident edges). We show that this problem can be solved on a pointer machine in time and space, where is the functional inverse of Ackermann's function. Our solution improves over the previously best known time bound, and allows us to close the gap existing with the fastest solution for the edge-removal version of the problem (i.e., that of finding, for every edge , a replacement edge which can be used for constructing an MST of ). Our algorithm finds immediate application in maintaining MST-based communication networks undergoing temporary node failures. Moreover, in a distributed environment in which nodes are managed by selfish agents, it can be used to design an efficient, truthful mechanism for building an MS
Dynamic mechanism design
AbstractIn this paper we address the question of designing truthful mechanisms for solving optimization problems on dynamic graphs with selfish edges. More precisely, we are given a graph G of n nodes, and we assume that each edge of G is owned by a selfish agent. The strategy of an agent consists in revealing to the system–at each time instant–the cost at the actual time for using its edge. Additionally, edges can enter into and exit from G. Among the various possible assumptions which can be made to model how this edge-cost modifications take place, we focus on two settings: (i) the dynamic, in which modifications can happen at any time, and for a given optimization problem on G, the mechanism has to maintain efficiently the output specification and the payment scheme for the agents; (ii) the time-sequenced, in which modifications happens at fixed time steps, and the mechanism has to minimize an objective function which takes into consideration both the quality and the set-up cost of a new solution. In both settings, we investigate the existence of exact and approximate truthful (w.r.t. to suitable equilibrium concepts) mechanisms. In particular, for the dynamic setting, we analyze the minimum spanning tree problem, and we show that if edge costs can only decrease and each agent adopts a myopic best response strategy (i.e., its utility is only measured instantaneously), then there exists an efficient dynamic truthful (in myopic best response equilibrium) mechanism for handling a sequence of k declarations of edge-cost reductions having runtime O((h+k)logn), where h is the overall number of payment changes
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