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143
Constructing Plane Spanners of Bounded Degree and Low Weight
 in Proceedings of European Symposium of Algorithms
, 2002
"... Given a set S of n points in the plane, we give an O(n log n)time algorithm that constructs a plane tspanner for S, for t 10:02, such that the degree of each point of S is bounded from above by 27, and the total edge length is proportional to the weight of a minimum spanning tree of S. These c ..."
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Cited by 45 (7 self)
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Given a set S of n points in the plane, we give an O(n log n)time algorithm that constructs a plane tspanner for S, for t 10:02, such that the degree of each point of S is bounded from above by 27, and the total edge length is proportional to the weight of a minimum spanning tree of S. These constants are all worst case constants that are artifacts of our proofs. In practice, we believe them to be much smaller. Previously, no algorithms were known for constructing plane tspanners of bounded degree.
On Greedy Geographic Routing Algorithms in SensingCovered Networks
 IN PROCEEDINGS OF MOBIHOC ’04
, 2004
"... Greedy geographic routing is attractive in wireless sensor networks due to its efficiency and scalability. However, greedy geographic routing may incur long routing paths or even fail due to routing voids on random network topologies. We study greedy geographic routing in an important class of wire ..."
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Cited by 45 (3 self)
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Greedy geographic routing is attractive in wireless sensor networks due to its efficiency and scalability. However, greedy geographic routing may incur long routing paths or even fail due to routing voids on random network topologies. We study greedy geographic routing in an important class of wireless sensor networks that provide sensing coverage over a geographic area (e.g., surveillance or object tracking systems). Our geometric analysis and simulation results demonstrate that existing greedy geographic routing algorithms can successfully find short routing paths based on local states in sensingcovered networks. In particular, we derive theoretical upper bounds on the network dilation of sensingcovered networks under greedy geographic routing algorithms. Furthermore, we propose a new greedy geographic routing algorithm called Bounded Voronoi Greedy Forwarding (BVGF) that allows sensingcovered networks to achieve an asymptotic network dilation lower than 4.62 as long as the communication range is at least twice the sensing range. Our results show that simple greedy geographic routing is an effective routing scheme in many sensingcovered networks.
On Local Algorithms for Topology Control and Routing in Ad Hoc Networks
 In Proc. SPAA
, 2003
"... An ad hoc network is a collection of wireless mobile hosts forming a temporary network without the aid of any fixed infrastructure. Indeed, an important task of an ad hoc network is to determine an appropriate topology over which highlevel routing protocols are implemented. Furthermore, since the u ..."
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Cited by 36 (1 self)
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An ad hoc network is a collection of wireless mobile hosts forming a temporary network without the aid of any fixed infrastructure. Indeed, an important task of an ad hoc network is to determine an appropriate topology over which highlevel routing protocols are implemented. Furthermore, since the underlying topology may change with time, we need to design routing algorithms that effectively react to dynamically changing network conditions. This paper studies algorithms...
The FreezeTag Problem: How to Wake Up a Swarm of Robots
 In Proc. 13th ACMSIAM Sympos. Discrete Algorithms
, 2002
"... An optimization problem that naturally arises in the study of "swarm robotics" is to wake up a set of "asleep" robots, starting with only one "awake" robot. One robot can only awaken another when they are in the same location. As soon as a robot is awake, it assists in ..."
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Cited by 29 (4 self)
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An optimization problem that naturally arises in the study of "swarm robotics" is to wake up a set of "asleep" robots, starting with only one "awake" robot. One robot can only awaken another when they are in the same location. As soon as a robot is awake, it assists in waking up other robots. The goal is to compute an optimal awakening schedule such that all robots are awake by time t , for the smallest possible value of t . We consider both scenarios on graphs and in geometric environments. In the graph setting, robots sleep at vertices and there is a length function on the edges. An awake robot can travel from vertex to vertex along edges, and the length of an edge determines the time it takes to travel from one vertex to the other. While this problem bears some resemblance to problems from various areas in combinatorial optimization such as routing, broadcasting, scheduling and covering, its algorithmic characteristics are surprisingly different. We prove that the problem is NPhard, even for the special case of star graphs. We also establish hardness of approximation, showing that it is NPhard to obtain an approximation factor better than 5/3, even for graphs of bounded degree. These lower bounds are complemented with several algorithmic results. We present a simple online algorithm that is O(log)competitive for graphs with maximum degree . Other results include algorithms that require substantially more sophistication and development of new techniques: (1) The natural greedy strategy on star graphs has a worstcase performance of 7/3, which is tight. (2) There exists a PTAS for star graphs. (3) For the problem Dept. of Appl. Math. and Statistics, SUNY Stony Brook, NY 117943600, festie, jsbmg@ams.sunysb.edu. y Dept. of Computer Science, SUNY St...
Estimating the weight of metric minimum spanning trees in sublineartime
 in Proceedings of the 36th Annual ACM Symposium on Theory of Computing (STOC
"... In this paper we present a sublinear time (1+ ɛ)approximation randomized algorithm to estimate the weight of the minimum spanning tree of an npoint metric space. The running time of the algorithm is Õ(n/ɛO(1)). Since the full description of an npoint metric space is of size Θ(n 2),the complexity ..."
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Cited by 23 (5 self)
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In this paper we present a sublinear time (1+ ɛ)approximation randomized algorithm to estimate the weight of the minimum spanning tree of an npoint metric space. The running time of the algorithm is Õ(n/ɛO(1)). Since the full description of an npoint metric space is of size Θ(n 2),the complexity of our algorithm is sublinear with respect to the input size. Our algorithm is almost optimal as it is not possible to approximate in o(n) time the weight of the minimum spanning tree to within any factor. Furthermore,it has been previously shown that no o(n 2) algorithm exists that returns a spanning tree whose weight is within a constant times the optimum.
Approximating geometric bottleneck shortest paths
 Computational Geometry: Theory and Applications
"... In a geometric bottleneck shortest path problem, we are given a set S of n points in the plane, and want to answer queries of the following type: Given two points p and q of S and a real number L, compute (or approximate) a shortest path between p and q in the subgraph of the complete graph on S con ..."
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Cited by 22 (10 self)
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In a geometric bottleneck shortest path problem, we are given a set S of n points in the plane, and want to answer queries of the following type: Given two points p and q of S and a real number L, compute (or approximate) a shortest path between p and q in the subgraph of the complete graph on S consisting of all edges whose lengths are less than or equal to L. We present efficient algorithms for answering several query problems of this type. Our solutions are based on Euclidean minimum spanning trees, spanners, and the Delaunay triangulation. A result of independent interest is the following. For any two points p and q of S, there is a path between p and q in the Delaunay triangulation, whose length is less than or equal to 2π/(3 cos(π/6)) times the Euclidean distance pq  between p and q, and all of whose edges have length at most pq.
Computing the maximum detour and spanning ratio of planar chains, trees and cycles
 In Proc. 19th Internat. Symp. Theor. Aspects of C.Sc., LNCS 2285:250–261
, 2002
"... Let G = (V, E) be an embedded connected graph with n vertices and m edges. Specifically, the vertex set V consists of points in R 2, and E consists ..."
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Cited by 22 (1 self)
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Let G = (V, E) be an embedded connected graph with n vertices and m edges. Specifically, the vertex set V consists of points in R 2, and E consists
FaultTolerant Geometric Spanners
 DISCRETE & COMPUTATIONAL GEOMETRY
, 2004
"... We present two new results about vertex and edge faulttolerant spanners in Euclidean spaces. We describe the first construction of vertex and edge faulttolerant spanners having optimal bounds for maximum degree and total cost. We present a greedy algorithm that for any t> 1 and any nonnegative ..."
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Cited by 22 (1 self)
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We present two new results about vertex and edge faulttolerant spanners in Euclidean spaces. We describe the first construction of vertex and edge faulttolerant spanners having optimal bounds for maximum degree and total cost. We present a greedy algorithm that for any t> 1 and any nonnegative integer k, constructs a kfaulttolerant tspanner in which every vertex is of degree O(k) and whose total cost is O(k2) times the cost of the minimum spanning tree; these bounds are asymptotically optimal. Our next contribution is an efficient algorithm for constructing good faulttolerant spanners. We present a new, sufficient condition for a graph to be a kfaulttolerant spanner. Using this condition, we design an efficient algorithm that finds faulttolerant spanners with asymptotically optimal bound for the maximum degree and almost optimal bound for the total cost.
On the spanning ratio of gabriel graphs and βskeletons
 SIAM Journal on Discrete Mathematics
, 2002
"... Abstract. The spanning ratio of a graph defined on n points in the Euclidean plane is the maximum ratio, over all pairs of data points (u, v), of the minimum graph distance between u and v divided by the Euclidean distance between u and v. A connected graph is said to be a Sspanner if the spanning ..."
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Cited by 21 (8 self)
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Abstract. The spanning ratio of a graph defined on n points in the Euclidean plane is the maximum ratio, over all pairs of data points (u, v), of the minimum graph distance between u and v divided by the Euclidean distance between u and v. A connected graph is said to be a Sspanner if the spanning ratio does not exceed S. For example, for any S, there exists a point set whose minimum spanning tree is not a Sspanner. At the other end of the spectrum, a Delaunay triangulation is guaranteed to be a 2.42spanner[11]. For proximity graphs between these two extremes, such as Gabriel graphs[8], relative neighborhood graphs[16] and βskeletons[12] with β ∈ [0, 2] some interesting questions arise. We show that the spanning ratio for Gabriel graphs (which are βskeletons with β = 1) is Θ ( √ n) in the worst case. For all βskeletons with β ∈ [0, 1], we prove that the spanning ratio is at most O(nγ) where γ = (1 − log2 (1 + p 1 − β2))/2. For all βskeletons with β ∈ [1, 2), we prove that there exist point sets whose spanning ratio is at least ` 1 2 − o(1) ´ √ n. For relative neighborhood graphs[16] (skeletons with β = 2), we show that there exist point sets where the spanning ratio is Ω(n). For points drawn independently from the uniform distribution on the unit square, we show that the spanning ratio of the (random) Gabriel graph and all βskeletons with β ∈ [1, 2] tends to ∞ in probability as p log n / log log n.
The Geometric Dilation of Finite Point Sets
, 2006
"... Let G be an embedded planar graph whose edges may be curves. For two arbitrary points of G, we can compare the length of the shortest path in G connecting them against their Euclidean distance. The supremum of all these ratios is called the geometric dilation of G. Given a finite point set, we would ..."
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Cited by 20 (10 self)
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Let G be an embedded planar graph whose edges may be curves. For two arbitrary points of G, we can compare the length of the shortest path in G connecting them against their Euclidean distance. The supremum of all these ratios is called the geometric dilation of G. Given a finite point set, we would like to know the smallest possible dilation of any graph that contains the given points. In this paper we prove that a dilation of 1.678 is always sufficient, and that #/2 1.570 ... is sometimes necessary in order to accommodate a finite set of points.