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36
Opportunitybased topology control in wireless sensor networks
 in ICDCS
, 2008
"... Topology control is an effective method to improve the energy efficiency of wireless sensor networks (WSNs). Traditional approaches are based on the assumption that a pair of nodes is either “connected ” or “disconnected”. These approaches are called connectivitybased topology control. In real envi ..."
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Cited by 91 (15 self)
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Topology control is an effective method to improve the energy efficiency of wireless sensor networks (WSNs). Traditional approaches are based on the assumption that a pair of nodes is either “connected ” or “disconnected”. These approaches are called connectivitybased topology control. In real environments however, there are many intermittently connected wireless links called lossy links. Taking a succeeded lossy link as an advantage, we are able to construct more energyefficient topologies. Towards this end, we propose a novel opportunitybased topology control. We show that opportunitybased topology control is a problem of NPhard. To address this problem in a practical way, we design a fully distributed algorithm called CONREAP based on reliability theory. We prove that CONREAP has a guaranteed performance. The worst running time is O(E) where E is the link set of the original topology, and the space requirement for individual nodes is O(d) where d is the node degree. To evaluate the performance of CONREAP, we design and implement a prototype system consisting of 50 Berkeley Mica2 motes. We also conducted comprehensive simulations. Experimental results show that compared with the connectivitybased topology control algorithms, CONREAP can improve the energy efficiency of a network up to 6 times. 1
LowInterference Topology Control for Wireless Ad Hoc Networks
 ACM Wireless Networks
, 2005
"... supported by NSF CCR0311174. Abstract — Topology control has been well studied in wireless ad hoc networks. However, only a few topology control methods take into account the low interference as a goal of the methods. Some researchers tried to reduce the interference by lowering node energy consump ..."
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Cited by 56 (0 self)
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supported by NSF CCR0311174. Abstract — Topology control has been well studied in wireless ad hoc networks. However, only a few topology control methods take into account the low interference as a goal of the methods. Some researchers tried to reduce the interference by lowering node energy consumption (i.e. by reducing the transmission power) or by devising low degree topology controls, but none of those protocols can guarantee low interference. Recently, Burkhart et al. [?] proposed several methods to construct topologies whose maximum link interference is minimized while the topology is connected or is a spanner for Euclidean length. In this paper we give algorithms to construct a network topology for wireless ad hoc network such that the maximum (or average) link (or node) interference of the topology is either minimized or approximately minimized. Index Terms — Topology control, interference, wireless ad hoc networks.
Network Lifetime and Power Assignment in AdHoc Wireless Networks
 in ESA
, 2003
"... Abstract. Used for topology control in adhoc wireless networks, Power Assignment is a family of problems, each defined by a certain connectivity constraint (such as strong connectivity) The input consists of a directed complete weighted graph G = (V; c). The power of a vertex u in a directed spanni ..."
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Cited by 42 (3 self)
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Abstract. Used for topology control in adhoc wireless networks, Power Assignment is a family of problems, each defined by a certain connectivity constraint (such as strong connectivity) The input consists of a directed complete weighted graph G = (V; c). The power of a vertex u in a directed spanning subgraph H is given by pH(u) = maxuv2E(H) c(uv). The power of H is given by p(H) = P u2V pH(u), Power Assignment seeks to minimize p(H) while H satisfies the given connectivity constraint. We
Some Recent Theoretical Advances and Open Questions on Energy Consumption in AdHoc Wireless Networks
, 2002
"... One of the main benefits of power controlled adhoc wireless networks is their ability to vary the range in order to reduce the power consumption. Minimizing energy consumption is crucial on such kind of networks since, typically, wireless devices are portable and benefit only of limited power resou ..."
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Cited by 30 (9 self)
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One of the main benefits of power controlled adhoc wireless networks is their ability to vary the range in order to reduce the power consumption. Minimizing energy consumption is crucial on such kind of networks since, typically, wireless devices are portable and benefit only of limited power resources. On the other hand, the network must have a sufficient degree of connectivity in order to guarantee fast and efficient communication. These two aspects yield a class of fundamental optimization problems, denoted as range assignment problems, that have been the subject of several works in the area of wireless network theory. The primary aim of this paper is to describe the most important recent advances on this class of problems. Rather than completeness, the paper will try to provide results and techniques that seem to be the most promising to address the several important related problems which are still open. Discussing such related open problems are indeed our other main goal.
MinimumEnergy Broadcasting in Static Ad Hoc Wireless Networks
 Wireless Networks
, 2002
"... Energy conservation is a critical issue in ad hoc wireless networks for node and network life since the nodes are powered by batteries only. One major approach for... ..."
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Cited by 30 (3 self)
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Energy conservation is a critical issue in ad hoc wireless networks for node and network life since the nodes are powered by batteries only. One major approach for...
Poweraware Base Station Positioning for Sensor Networks
 in Proc. IEEE Infocom
, 2004
"... We consider the problem of positioning data collecting base stations in a sensor network. We show that in general, the choice of positions has a marked influence on the data rate, or equivalently, the power efficiency, of the network. In our model, which is partly motivated by an experimental enviro ..."
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Cited by 26 (0 self)
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We consider the problem of positioning data collecting base stations in a sensor network. We show that in general, the choice of positions has a marked influence on the data rate, or equivalently, the power efficiency, of the network. In our model, which is partly motivated by an experimental environmental monitoring system, the optimum data rate for a fixed layout of base stations can be found by a maximum flow algorithm. Finding the optimum layout of base stations, however, turns out to be an NPcomplete problem, even in the special case of homogeneous networks. Our analysis of the optimum layout for the special case of the regular grid shows that all layouts that meet certain constraints are equally good. We also consider two classes of random graphs, chosen to model networks that might be realistically encountered, and empirically evaluate the performance of several base station positioning algorithms on instances of these classes. In comparison to manually choosing positions along the periphery of the network or randomly choosing them within the network, the algorithms tested find positions which significantly improve the data rate and power efficiency of the network.
Algorithmic, Geometric and Graphs Issues in Wireless Networks
 Wireless Communications and Mobile Computing
, 2002
"... We present an overview of the recent progress of applying computational geometry techniques to solve some questions, such as topology construction and broadcasting, in wireless ad hoc networks. Treating each wireless device as a node in a two dimensional plane, we model the wireless networks by unit ..."
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Cited by 24 (2 self)
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We present an overview of the recent progress of applying computational geometry techniques to solve some questions, such as topology construction and broadcasting, in wireless ad hoc networks. Treating each wireless device as a node in a two dimensional plane, we model the wireless networks by unit disk graphs in which two nodes are connected if their Euclidean distance is no more than one. We rst summarize the current status of constructing sparse spanners for unit disk graphs with various combinations of the following properties: bounded stretch factor, bounded node degree, planar, and bounded total edges weight (compared with the minimum spanning tree). Instead of constructing subgraphs by removing links, we then review the algorithms for constructing a sparse backbone (connected dominating set), i.e., subgraph from the subset of nodes. We then review some ecient methods for broadcasting and multicasting with theoretic guaranteed performance.
Power efficient range assignment for symmetric connectivity in static adhoc wireless networks. Wireless Networks
 Wireless Networks
, 2006
"... In this paper we study the problem of assigning transmission ranges to the nodes of a static ad hoc wireless network so as to minimize the total power consumed under the constraint that enough power is provided to the nodes to ensure that the network is connected. We focus on the MINPOWER SYMMETRIC ..."
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Cited by 19 (1 self)
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In this paper we study the problem of assigning transmission ranges to the nodes of a static ad hoc wireless network so as to minimize the total power consumed under the constraint that enough power is provided to the nodes to ensure that the network is connected. We focus on the MINPOWER SYMMETRIC CONNECTIVITY problem, in which the bidirectional links established by the transmission ranges are required to form a connected graph. Implicit in previous work on transmission range assignment under asymmetric connectivity requirements is the proof that MINPOWER SYMMETRIC CONNECTIVITY is NPhard and that the MST algorithm has an approximation ratio of 2. In this paper we make the following contributions: (1) we show that the related MINPOWER SYMMETRIC UNICAST problem can be solved efficiently by a shortestpath computation in an appropriately constructed graph. (2) we give an exact branch and cut algorithm based on a new integer linear program formulation solving instances with up to 3540 nodes in 1 hour; (3) we establish the similarity between MINPOWER SYMMETRIC CONNECTIVITY and the classic STEINER TREE problem in graphs, and use this similarity to give a polynomialtime approximation scheme with performance ratio approaching 5/3 as well as a more practical approximation algorithm with approximation factor 11/6; and (4) we give a comprehensive experimental study comparing new and previously proposed heuristics with the above exact and approximation algorithms.
Power efficient range assignment in adhoc wireless networks
 In Proc. IEEE Wireless Communications and Networking Conference (WCNC
, 2003
"... Abstract—We study the problem of assigning transmission ranges to the nodes of ad hoc wireless networks so that to minimize power consumption while ensuring network connectivity. We give (1) an exact branch and cut algorithm based on a new integer linear program formulation solving instances with up ..."
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Cited by 18 (2 self)
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Abstract—We study the problem of assigning transmission ranges to the nodes of ad hoc wireless networks so that to minimize power consumption while ensuring network connectivity. We give (1) an exact branch and cut algorithm based on a new integer linear program formulation solving instances with up to 3540 nodes in 1 hour; (2) a proof that MINPOWER SYMMETRIC CONNECTIVITY WITH ASYMMETRIC POWER REQUIREMENTS is inapproximable within £¥¤§¦©¨������� � �� � factor for ¨��� � any unless; (3) an improved analysis for two approximation algorithms recently proposed by Călinescu et al. (TCS’02), decreasing the best known approximation factor to �������� ¨ ; (4) a comprehensive experimental study comparing new and previously proposed heuristics with the above exact and approximation algorithms.
Minimumcost coverage of point sets by disks
 in Symposium on Computational Geometry
, 2006
"... We consider a class of geometric facility location problems in which the goal is to determine a set X of disks given by their centers (t j) and radii (r j) that cover a given set of demand points Y ⊂ R 2 at the smallest possible cost. We consider cost functions of the form ∑ j f(r j), where f(r) = ..."
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Cited by 15 (2 self)
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We consider a class of geometric facility location problems in which the goal is to determine a set X of disks given by their centers (t j) and radii (r j) that cover a given set of demand points Y ⊂ R 2 at the smallest possible cost. We consider cost functions of the form ∑ j f(r j), where f(r) = r α is the cost of transmission to radius r. Special cases arise for α = 1 (sum of radii) and α = 2 (total area); power consumption models in wireless network design often use an exponent α> 2. Different scenarios arise according to possible restrictions on the transmission centers t j, which may be constrained to belong to a given discrete set or to lie on a line, etc. We obtain several new results, including (a) exact and approximation algorithms for selecting transmission points t j on a given line in order to cover demand points Y ⊂ R 2; (b) approximation algorithms (and an algebraic intractability result) for selecting an optimal line on which to place transmission points to cover Y; (c) a proof of NPhardness for a discrete set of transmission points in R 2 and any fixed α> 1; and (d) a polynomialtime approximation scheme for the problem of computing a minimum cost covering tour (MCCT), in which the total cost is a linear combination of the transmission cost for the set of disks and the length of a tour/path that connects the centers of the disks. ACM Classification: F.2.2 Nonnumerical Algorithms and Problems. AMS Classification: 68Q25, 68U05, 90C27.