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173
Barrier coverage with wireless sensors
 In ACM MobiCom
, 2005
"... When a sensor network is deployed to detect objects penetrating a protected region, it is not necessary to have every point in the deployment region covered by a sensor. It is enough if the penetrating objects are detected at some point in their trajectory. If a sensor network guarantees that every ..."
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Cited by 66 (8 self)
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When a sensor network is deployed to detect objects penetrating a protected region, it is not necessary to have every point in the deployment region covered by a sensor. It is enough if the penetrating objects are detected at some point in their trajectory. If a sensor network guarantees that every penetrating object will be detected by at least £ distinct sensors before it crosses the barrier of wireless sensors, we say the network provides £barrier coverage. In this paper, we develop theoretical foundations for £barrier coverage. We propose efficient algorithms using which one can quickly determine, after deploying the sensors, whether the deployment region is £barrier covered. Next, we establish the optimal deployment pattern to achieve £barrier coverage when deploying sensors deterministically. Finally, we consider barrier coverage with high probability when sensors are deployed randomly. The major challenge, when dealing with probabilistic barrier coverage, is to derive critical conditions using which one can compute the minimum number of sensors needed to ensure barrier coverage with high probability. Deriving critical conditions for £barrier coverage is, however, still an open problem. We derive critical conditions for a weaker notion of barrier coverage, called weak £barrier coverage.
Finding shortest nonseparating and noncontractible cycles for topologically embedded graphs
 Discrete Comput. Geom
, 2005
"... We present an algorithm for finding shortest surface nonseparating cycles in graphs embedded on surfaces in O(g 3/2 V 3/2 log V + g 5/2 V 1/2) time, where V is the number of vertices in the graph and g is the genus of the surface. If g = o(V 1/3−ε), this represents a considerable improvement over p ..."
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Cited by 39 (8 self)
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We present an algorithm for finding shortest surface nonseparating cycles in graphs embedded on surfaces in O(g 3/2 V 3/2 log V + g 5/2 V 1/2) time, where V is the number of vertices in the graph and g is the genus of the surface. If g = o(V 1/3−ε), this represents a considerable improvement over previous results by Thomassen, and Erickson and HarPeled. We also give algorithms to find a shortest noncontractible cycle in O(g O(g) V 3/2) time, which improves previous results for fixed genus. This result can be applied for computing the (nonseparating) facewidth of embedded graphs. Using similar ideas we provide the first nearlinear running time algorithm for computing the facewidth of a graph embedded on the projective plane, and an algorithm to find the facewidth of embedded toroidal graphs in O(V 5/4 log V) time. 1
Approximation algorithms via contraction decomposition
 Proc. 18th Ann. ACMSIAM Symp. Discrete Algorithms ACMSIAM symposium on Discrete algorithms
, 2007
"... We prove that the edges of every graph of bounded (Euler) genus can be partitioned into any prescribed number k of pieces such that contracting any piece results in a graph of bounded treewidth (where the bound depends on k). This decomposition result parallels an analogous, simpler result for edge ..."
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Cited by 24 (7 self)
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We prove that the edges of every graph of bounded (Euler) genus can be partitioned into any prescribed number k of pieces such that contracting any piece results in a graph of bounded treewidth (where the bound depends on k). This decomposition result parallels an analogous, simpler result for edge deletions instead of contractions, obtained in [Bak94, Epp00, DDO + 04, DHK05], and it generalizes a similar result for “compression ” (a variant of contraction) in planar graphs [Kle05]. Our decomposition result is a powerful tool for obtaining PTASs for contractionclosed problems (whose optimal solution only improves under contraction), a much more general class than minorclosed problems. We prove that any contractionclosed problem satisfying just a few simple conditions has a PTAS in boundedgenus graphs. In particular, our framework yields PTASs for the weighted Traveling Salesman Problem and for minimumweight cedgeconnected submultigraph on boundedgenus graphs, improving and generalizing previous algorithms of [GKP95, AGK + 98, Kle05, Gri00, CGSZ04, BCGZ05]. We also highlight the only main difficulty in extending our results to general Hminorfree graphs.
Fast Parameterized Algorithms for Graphs on Surfaces: Linear Kernel and Exponential Speedup
"... Preprocessing by data reduction is a simple but powerful technique used for practically solving di#erent network problems. A number of empirical studies shows that a set of reduction rules for solving Dominating Set problems introduced by Alber, Fellows & Niedermeier leads e#ciently to optimal s ..."
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Cited by 23 (5 self)
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Preprocessing by data reduction is a simple but powerful technique used for practically solving di#erent network problems. A number of empirical studies shows that a set of reduction rules for solving Dominating Set problems introduced by Alber, Fellows & Niedermeier leads e#ciently to optimal solutions for many realistic networks. Despite of the encouraging experiments, the only class of graphs with proven performance guarantee of reductions rules was the class of planar graphs.
Coloring graphs with fixed genus and girth
 Trans. Am. Math. Soc
, 1997
"... Abstract. It is well known that the maximum chromatic number of a graph on the orientable surface Sg is θ(g1/2). We prove that there are positive constants c1,c2 such that every trianglefree graph on Sg has chromatic number less than c2(g / log(g)) 1/3 and that some trianglefree graph on Sg has ch ..."
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Cited by 21 (1 self)
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Abstract. It is well known that the maximum chromatic number of a graph on the orientable surface Sg is θ(g1/2). We prove that there are positive constants c1,c2 such that every trianglefree graph on Sg has chromatic number less than c2(g / log(g)) 1/3 and that some trianglefree graph on Sg has chromatic number at least c1 g1/3 log(g). We obtain similar results for graphs with restricted clique number or girth on Sg or Nk. As an application, we prove that an Sgpolytope has chromatic number at most O(g3/7). For specific surfaces we prove that every graph on the double torus and of girth at least six is 3colorable and we characterize completely those trianglefree projective graphs that are not 3colorable. 1.
Splitting (complicated) surfaces is hard
 COMPUT. GEOM. THEORY APPL
, 2006
"... Let M be an orientable surface without boundary. A cycle on M is splitting if it has no selfintersections and it partitions M into two components, neither homeomorphic to a disk. In other words, splitting cycles are simple, separating, and noncontractible. We prove that finding the shortest splitt ..."
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Cited by 21 (10 self)
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Let M be an orientable surface without boundary. A cycle on M is splitting if it has no selfintersections and it partitions M into two components, neither homeomorphic to a disk. In other words, splitting cycles are simple, separating, and noncontractible. We prove that finding the shortest splitting cycle on a combinatorial surface is NPhard but fixedparameter tractable with respect to the surface genus. Specifically, we describe an algorithm to compute the shortest splitting cycle in g^O(g) n log n time.
The directed planar reachability problem
 In Proc. 25th annual Conference on Foundations of Software Technology and Theoretical Computer Science (FST&TCS), number 1373 in Lecture Notes in Computer Science
, 2005
"... Abstract. We investigate the stconnectivity problem for directed planar graphs, which is hard for L and is contained in NL but is not known to be complete. We show that this problem is logspacereducible to its complement, and we show that the problem of searching graphs of genus 1 reduces to the ..."
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Cited by 20 (8 self)
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Abstract. We investigate the stconnectivity problem for directed planar graphs, which is hard for L and is contained in NL but is not known to be complete. We show that this problem is logspacereducible to its complement, and we show that the problem of searching graphs of genus 1 reduces to the planar case. We also consider a previouslystudied subclass of planar graphs known as grid graphs. We show that the directed planar stconnectivity problem reduces to the reachability problem for directed grid graphs. A special case of the gridgraph reachability problem where no edges are directed from right to left is known as the “acyclic grid graph reachability problem”. We show that this problem lies in the complexity class UL. 1
The OneRound Voronoi Game
, 2002
"... In the oneround Voronoi game, the FRST player places n sites inside a unitsquare Q. Next, the ..."
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Cited by 17 (4 self)
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In the oneround Voronoi game, the FRST player places n sites inside a unitsquare Q. Next, the
Minimum Cuts and Shortest Homologous Cycles
 SYMPOSIUM ON COMPUTATIONAL GEOMETRY
, 2009
"... We describe the first algorithms to compute minimum cuts in surfaceembedded graphs in nearlinear time. Given an undirected graph embedded on an orientable surface of genus g, with two specified vertices s and t, our algorithm computes a minimum (s, t)cut in g O(g) n log n time. Except for the spec ..."
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Cited by 17 (7 self)
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We describe the first algorithms to compute minimum cuts in surfaceembedded graphs in nearlinear time. Given an undirected graph embedded on an orientable surface of genus g, with two specified vertices s and t, our algorithm computes a minimum (s, t)cut in g O(g) n log n time. Except for the special case of planar graphs, for which O(n log n)time algorithms have been known for more than 20 years, the best previous time bounds for finding minimum cuts in embedded graphs follow from algorithms for general sparse graphs. A slight generalization of our minimumcut algorithm computes a minimumcost subgraph in every Z2homology class. We also prove that finding a minimumcost subgraph homologous to a single input cycle is NPhard.