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263
GPSR: Greedy perimeter stateless routing for wireless networks
, 2000
"... karp @ eecs.harvard.edu We present Greedy Perimeter Stateless Routing (GPSR), a novel routing protocol for wireless datagram networks that uses the positions of touters and a packer's destination to make packet forwarding decisions. GPSR makes greedy forwarding decisions using only informati ..."
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Cited by 1780 (8 self)
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karp @ eecs.harvard.edu We present Greedy Perimeter Stateless Routing (GPSR), a novel routing protocol for wireless datagram networks that uses the positions of touters and a packer's destination to make packet forwarding decisions. GPSR makes greedy forwarding decisions using only information about a router's immediate neighbors in the network topology. When a packet reaches a region where greedy forwarding is impossible, the algorithm recovers by routing around the perimeter of the region. By keeping state only about the local topology, GPSR scales better in perrouter state than shortestpath and adhoc routing protocols as the number of network destinations increases. Under mobility's frequent topology changes, GPSR can use local topology information to find correct new routes quickly. We describe the GPSR protocol, and use extensive simulation of mobile wireless networks to compare its performance with that of Dynamic Source Routing. Our simulations demonstrate GPSR's scalability on densely deployed wireless networks.
Data Clustering: A Review
 ACM COMPUTING SURVEYS
, 1999
"... Clustering is the unsupervised classification of patterns (observations, data items, or feature vectors) into groups (clusters). The clustering problem has been addressed in many contexts and by researchers in many disciplines; this reflects its broad appeal and usefulness as one of the steps in exp ..."
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Cited by 1413 (13 self)
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Clustering is the unsupervised classification of patterns (observations, data items, or feature vectors) into groups (clusters). The clustering problem has been addressed in many contexts and by researchers in many disciplines; this reflects its broad appeal and usefulness as one of the steps in exploratory data analysis. However, clustering is a difficult problem combinatorially, and differences in assumptions and contexts in different communities has made the transfer of useful generic concepts and methodologies slow to occur. This paper presents an overview of pattern clustering methods from a statistical pattern recognition perspective, with a goal of providing useful advice and references to fundamental concepts accessible to the broad community of clustering practitioners. We present a taxonomy of clustering techniques, and identify crosscutting themes and recent advances. We also describe some important applications of clustering algorithms such as image segmentation, object recognition, and information retrieval.
Voronoi diagrams  a survey of a fundamental geometric data structure
 ACM COMPUTING SURVEYS
, 1991
"... This paper presents a survey of the Voronoi diagram, one of the most fundamental data structures in computational geometry. It demonstrates the importance and usefulness of the Voronoi diagram in a wide variety of fields inside and outside computer science and surveys the history of its development. ..."
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Cited by 621 (5 self)
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This paper presents a survey of the Voronoi diagram, one of the most fundamental data structures in computational geometry. It demonstrates the importance and usefulness of the Voronoi diagram in a wide variety of fields inside and outside computer science and surveys the history of its development. The paper puts particular emphasis on the unified exposition of its mathematical and algorithmic properties. Finally, the paper provides the first comprehensive bibliography on Voronoi diagrams and related structures.
A Survey on PositionBased Routing in Mobile AdHoc Networks
 IEEE Network
, 2001
"... We present an overview of adhoc routing protocols that make forwarding decisions based on the geographical position of a packet's destination. Other than the destination 's position, each node needs to know only its own position and the position of its onehop neighbors in order to forwar ..."
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Cited by 411 (16 self)
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We present an overview of adhoc routing protocols that make forwarding decisions based on the geographical position of a packet's destination. Other than the destination 's position, each node needs to know only its own position and the position of its onehop neighbors in order to forward packets. Since it is not necessary to maintain explicit routes, positionbased routing does scale well even if the network is highly dynamic. This is a major advantage in a mobile adhoc network where the topology may change frequently. The main prerequisite for positionbased routing is that a sender can obtain the current position of the destination. Therefore, recently proposed location services are discussed in addition to positionbased packet forwarding strategies. We provide a qualitative comparison of the approaches in both areas and investigate opportunities for future research.
Geographic routing made practical
, 2005
"... Geographic routing has been widely hailed as the most promising approach to generally scalable wireless routing. However, the correctness of all currently proposed geographic routing algorithms relies on idealized assumptions about radios and their resulting connectivity graphs. We use testbed measu ..."
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Cited by 148 (4 self)
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Geographic routing has been widely hailed as the most promising approach to generally scalable wireless routing. However, the correctness of all currently proposed geographic routing algorithms relies on idealized assumptions about radios and their resulting connectivity graphs. We use testbed measurements to show that these idealized assumptions are grossly violated by real radios, and that these violations cause persistent failures in geographic routing, even on static topologies. Having identified this problem, we then fix it by proposing the CrossLink Detection Protocol (CLDP), which enables provably correct geographic routing on arbitrary connectivity graphs. We confirm in simulation and further testbed measurements that CLDP is not only correct but practical: it incurs low overhead, exhibits low path stretch, always succeeds in real, static wireless networks, and converges quickly after topology changes. 1
Analysis of a conebased distributed topology control algorithm for wireless multihop networks
 In ACM Symposium on Principle of Distributed Computing (PODC
, 2001
"... bahl~microsoft, corn ymwang~microsoft, corn rogerwa~microsoft, corn The topology of a wireless multihop network can be controlled by varying the transmission power at each node. In this paper, we give a detailed analysis of a conebased distributed topology control algorithm. This algorithm, intr ..."
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Cited by 147 (9 self)
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bahl~microsoft, corn ymwang~microsoft, corn rogerwa~microsoft, corn The topology of a wireless multihop network can be controlled by varying the transmission power at each node. In this paper, we give a detailed analysis of a conebased distributed topology control algorithm. This algorithm, introduced in [16], does not assume that nodes have GPS information available; rather it depends only on directional information. Roughly speaking, the basic idea of the algorithm is that a node u transmits with the minimum power P~,,a required to ensure that in every cone of degree a around u, there is some node that u can reach with power Pma We show that taking a = 57r/6 is a necessary and sufficient condition to guarantee that network connectivity is preserved. More precisely, if there is a path from a to t when every node communicates at maximum power then, if a < _ 5~r/6, there is still a path in the smallest symmetric graph Ga containing all edges (u, v) such that u can communicate with v using power p~,a. On the other hand, if ~> 51r/6, connectivity is not necessarily preserved. We also propose a set of optimizations that further reduce power consumption and prove that they retain network connectivity. Dynamic reconfiguration in the presence of failures and mobility is also discussed. Simulation results are presented to demonstrate the effectiveness of the algorithm and the optimizations. 1.
Coverage in Wireless Adhoc Sensor Networks
, 2002
"... Sensor networks pose a number of challenging conceptual and optimization problems such as location, deployment, and tracking [1]. One of the fundamental problems in sensor networks is the calculation of the coverage. In [1], it is assumed that the sensor has the uniform sensing ability. In this pape ..."
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Cited by 128 (10 self)
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Sensor networks pose a number of challenging conceptual and optimization problems such as location, deployment, and tracking [1]. One of the fundamental problems in sensor networks is the calculation of the coverage. In [1], it is assumed that the sensor has the uniform sensing ability. In this paper, we give efficient distributed algorithms to optimally solve the bestcoverage problem raised in [1]. Here, we consider the sensing model: the sensing ability diminishes as the distance increases. As energy conservation is a major concern in wireless (or sensor) networks, we also consider how to find an optimum bestcoverage path with the least energy consumption. We also consider how to find an optimum bestcoveragepath that travels a small distance. In addition, we justify the correctness of the method proposed in [1] that uses the Delaunay triangulation to solve the best coverage problem. Moreover, we show that the search space of the best coverage problem can be confined to the relative neighborhood graph, which can be constructed locally.
Distributed Construction of a Planar Spanner and Routing for Ad Hoc Wireless Networks
, 2002
"... Several localized routing protocols [1] guarantee the delivery of the packets when the underlying network topology is the Delaunay triangulation of all wireless nodes. However, it is expensive to construct the Delaunay triangulation in a distributed manner. Given a set of wireless nodes, we more acc ..."
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Cited by 119 (22 self)
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Several localized routing protocols [1] guarantee the delivery of the packets when the underlying network topology is the Delaunay triangulation of all wireless nodes. However, it is expensive to construct the Delaunay triangulation in a distributed manner. Given a set of wireless nodes, we more accurately model the network as a unitdisk graph UDG , in which a link in between two nodes exist only if the distance in between them is at most the maximum transmission range.
AdHoc Networks Beyond Unit Disk Graphs
, 2003
"... In this paper we study a model for adhoc networks close enough to reality as to represent existing networks, being at the same time concise enough to promote strong theoretical results. The Quasi Unit Disk Graph model contains all edges shorter than a parameter d between 0 and 1 and no edges longer ..."
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Cited by 116 (11 self)
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In this paper we study a model for adhoc networks close enough to reality as to represent existing networks, being at the same time concise enough to promote strong theoretical results. The Quasi Unit Disk Graph model contains all edges shorter than a parameter d between 0 and 1 and no edges longer than 1. We show that  in comparison to the cost known on Unit Disk Graphs  the complexity results in this model contain the additional factor 1/d&sup2;. We prove that in Quasi Unit Disk Graphs flooding is an asymptotically messageoptimal routing technique, provide a geometric routing algorithm being more efficient above all in dense networks, and show that classic geometric routing is possible with the same performance guarantees as for Unit Disk Graphs if d 1/ # 2.