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174
Topology Control in Wireless Ad Hoc and Sensor Networks
 ACM Computing Surveys
, 2005
"... Topology Control (TC) is one of the most important techniques used in wireless ad hoc and sensor networks to reduce energy consumption (which is essential to extend the network operational time) and radio interference (with a positive effect on the network traffic carrying capacity). The goal of thi ..."
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Cited by 304 (4 self)
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Topology Control (TC) is one of the most important techniques used in wireless ad hoc and sensor networks to reduce energy consumption (which is essential to extend the network operational time) and radio interference (with a positive effect on the network traffic carrying capacity). The goal of this technique is to control the topology of the graph representing the communication links between network nodes with the purpose of maintaining some global graph property (e.g., connectivity), while reducing energy consumption and/or interference that are strictly related to the nodes ’ transmitting range. In this article, we state several problems related to topology control in wireless ad hoc and sensor networks, and we survey stateoftheart solutions which have been proposed to tackle them. We also outline several directions for further research which we hope will motivate researchers to undertake additional studies in this field.
Design and Analysis of an MSTBased Topology Control Algorithm
, 2002
"... In this paper, we present a Minimum Spanning Tree (MST) based topology control algorithm, called Local Minimum Spanning Tree (LMST), for wireless multihop networks. In this algorithm, each node builds its local minimum spanning tree independently and only keeps ontree nodes that are onehop away a ..."
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Cited by 278 (7 self)
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In this paper, we present a Minimum Spanning Tree (MST) based topology control algorithm, called Local Minimum Spanning Tree (LMST), for wireless multihop networks. In this algorithm, each node builds its local minimum spanning tree independently and only keeps ontree nodes that are onehop away as its neighbors in the final topology. We analytically prove several important properties of LMST: (1) the topology derived under LMST preserves the network connectivity; (2) the node degree of any node in the resulting topology is bounded by 6; and (3) the topology can be transformed into one with bidirectional links (without impairing the network connectivity) after removal of all unidirectional links. These results are corroborated in the simulation study.
Joint mobility and routing for lifetime elongation in wireless sensor networks
 In Proceedijngs of IEEE INFOCOM
"... Abstract — Although many energy efficient/conserving routing protocols have been proposed for wireless sensor networks, the concentration of data traffic towards a small number of base stations remains a major threat to the network lifetime. The main reason is that the sensor nodes located near a ba ..."
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Cited by 175 (9 self)
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Abstract — Although many energy efficient/conserving routing protocols have been proposed for wireless sensor networks, the concentration of data traffic towards a small number of base stations remains a major threat to the network lifetime. The main reason is that the sensor nodes located near a base station have to relay data for a large part of the network and thus deplete their batteries very quickly. The solution we propose in this paper suggests that the base station be mobile; in this way, the nodes located close to it change over time. Data collection protocols can then be optimized by taking both base station mobility and multihop routing into account. We first study the former, and conclude that the best mobility strategy consists in following the periphery of the network (we assume that the sensors are deployed within a circle). We then consider jointly mobility and routing algorithms in this case, and show that a better routing strategy uses a combination of round routes and short paths. We provide a detailed analytical model for each of our statements, and corroborate it with simulation results. We show that the obtained improvement in terms of network lifetime is in the order of 500%.
Topology Control and Routing in Ad hoc Networks: A Survey
 SIGACT News
, 2002
"... this article, we review some of the characteristic features of ad hoc networks, formulate problems and survey research work done in the area. We focus on two basic problem domains: topology control, the problem of computing and maintaining a connected topology among the network nodes, and routing. T ..."
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Cited by 164 (0 self)
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this article, we review some of the characteristic features of ad hoc networks, formulate problems and survey research work done in the area. We focus on two basic problem domains: topology control, the problem of computing and maintaining a connected topology among the network nodes, and routing. This article is not intended to be a comprehensive survey on ad hoc networking. The choice of the problems discussed in this article are somewhat biased by the research interests of the author
The Critical Transmitting Range for Connectivity in Sparse Wireless Ad Hoc Networks
, 2003
"... In this paper, we analyze the critical transmitting range for connectivity in wireless ad hoc networks. More specifically, we consider the following problem: assume n nodes, each capable of communicating with nodes within a radius of r, are randomly and uniformly distributed in a ddimensional re ..."
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Cited by 149 (12 self)
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In this paper, we analyze the critical transmitting range for connectivity in wireless ad hoc networks. More specifically, we consider the following problem: assume n nodes, each capable of communicating with nodes within a radius of r, are randomly and uniformly distributed in a ddimensional region with a side of length l; how large must the transmitting range r be to ensure that the resulting network is connected with high probability? First, we consider this problem for stationary networks, and we provide tight upper and lower bounds on the critical transmitting range for onedimensional networks, and nontight bounds for two and threedimensional networks. Due to the presence of the geometric parameter l in the model, our results can be applied to dense as well as sparse ad hoc networks, contrary to existing theoretical results that apply only to dense networks. We also investigate several related questions through extensive simulations. First, we evaluate the relationship between the critical transmitting range and the minimum transmitting range that ensures formation of a connected component containing a large fraction (e.g. 90%) of the nodes. Then, we consider the mobile version of the
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 139 (21 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
Algorithmic Aspects of Topology Control Problems for Ad hoc Networks
, 2002
"... Topology control problems are concerned with the assignment of power values to the nodes of an ad~hoc network so that the power assignment leads to a graph topology satisfying some specified properties. This paper considers such problems under several optimization objectives, including minimizing th ..."
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Cited by 120 (6 self)
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Topology control problems are concerned with the assignment of power values to the nodes of an ad~hoc network so that the power assignment leads to a graph topology satisfying some specified properties. This paper considers such problems under several optimization objectives, including minimizing the maximum power and minimizing the total power. A general approach leading to a polynomial algorithm is presented for minimizing maximum power for a class of graph properties called monotone properties. The difficulty of generalizing the approach to properties that are not monotone is discussed. Problems involving the minimization of total power are known to be NPcomplete even for simple graph properties. A general approach that leads to an approximation algorithm for minimizing the total power for some monotone properties is presented. Using this approach, a new approximation algorithm for the problem of minimizing the total power for obtaining a 2nodeconnected graph is obtained. It is shown that this algorithm provides a constant performance guarantee. Experimental results from an implementation of the approximation algorithm are also presented.
On neighbor discovery in wireless networks with directional antennas
 In IEEE INFOCOM
, 2005
"... Neighbor discovery is one of the first steps in the initialization of a wireless ad hoc network. In this paper, we design and analyze practical algorithms for neighbor discovery in wireless networks. We first consider an ALOHAlike neighbor discovery algorithm in a synchronous system, proposed in ..."
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Cited by 111 (4 self)
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Neighbor discovery is one of the first steps in the initialization of a wireless ad hoc network. In this paper, we design and analyze practical algorithms for neighbor discovery in wireless networks. We first consider an ALOHAlike neighbor discovery algorithm in a synchronous system, proposed in an earlier work. When nodes do not have a collision detection mechanism, we show that this algorithm reduces to the classical Coupon Collector’s Problem. Consequently, we show that each node discovers all its n neighbors in an expected time equal to ne(lnn+c), for some constant c. When nodes have a collision detection mechanism, we propose an algorithm based on receiver status feedback which yields a lnn improvement over the ALOHAlike algorithm. Our algorithms do not require nodes to have any estimate of the number of neighbors. In particular, we show that not knowing n results in no more than a factor of two slowdown in the algorithm performance. In the absence of node synchronization, we develop asynchronous neighbor discovery algorithms that are only a factor of two slower than their synchronous counterparts. We show that our algorithms can achieve neighbor discovery despite allowing nodes to begin execution at different time instants. Furthermore, our algorithms allow each node to detect when to terminate the neighbor discovery phase.
Improving spatial reuse through tuning transmit power, carrier sense threshold, and data rate in multihop wireless networks
 In Proc. of ACM MobiCom
, 2006
"... The importance of spatial reuse in wireless adhoc networks has been long recognized as a key to improving the network capacity. One can increase the level of spatial reuse by either reducing the transmit power or increasing the carrier sense threshold (thereby reducing the carrier sense range). On ..."
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Cited by 97 (6 self)
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The importance of spatial reuse in wireless adhoc networks has been long recognized as a key to improving the network capacity. One can increase the level of spatial reuse by either reducing the transmit power or increasing the carrier sense threshold (thereby reducing the carrier sense range). On the other hand, as the transmit power decreases or the carrier sense threshold increases, the SINR decreases as a result of the smaller received signal or the increased interference level. Consequently, the data rate sustained by each transmission may decrease. This leads naturally to the following questions: (1) How can the tradeoff between the increased level of spatial reuse and the decreased data rate each node can sustain be quantified? In other words, is there an optimal range of transmit power/carrier sense threshold in which the network capacity is maximized? (2) What is the relation between
RealTime communication and coordination in embedded sensor networks
 PROCEEDINGS OF THE IEEE
, 2003
"... Sensor networks can be considered distributed computing platforms with many severe constraints including limited CPU speed, memory size, power, and bandwidth. Individual nodes in sensor networks are typically unreliable and the network topology dynamically changes, possibly frequently. Sensor networ ..."
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Cited by 96 (11 self)
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Sensor networks can be considered distributed computing platforms with many severe constraints including limited CPU speed, memory size, power, and bandwidth. Individual nodes in sensor networks are typically unreliable and the network topology dynamically changes, possibly frequently. Sensor networks can also be considered a form of ad hoc network. However, here also many constraints in sensor networks are different or more severe. Sensor networks also differ because of their tight interaction with the physical environment via sensors and actuators. Due to all of these differences many solutions developed for general distributed computing platforms and for ad hoc networks cannot be applied to sensor networks. Many new and exciting research challenges exist. This paper discusses the state of the art and presents the key research challenges to be solved, some with initial solutions or approaches.