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146
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.
Atpc: Adaptive transmission power control for wireless sensor networks
 In Proceedings of the Fourth International Conference on Embedded Networked Sensor Systems (SenSys
, 2006
"... Extensive empirical studies presented in this paper confirm that the quality of radio communication between low power sensor devices varies significantly with time and environment. This phenomenon indicates that the previous topology control solutions, which use static transmission power, transmissi ..."
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Cited by 146 (10 self)
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Extensive empirical studies presented in this paper confirm that the quality of radio communication between low power sensor devices varies significantly with time and environment. This phenomenon indicates that the previous topology control solutions, which use static transmission power, transmission range, and link quality, might not be effective in the physical world. To address this issue, online transmission power control that adapts to external changes is necessary. This paper presents ATPC, a lightweight algorithm of Adaptive Transmission Power Control for wireless sensor networks. In ATPC, each node builds a model for each of its neighbors, describing the correlation between transmission power and link quality. With this model, we employ a feedbackbased transmission power control algorithm to dynamically maintain individual link quality over time. The intellectual contribution of this work lies in a novel pairwise transmission power control, which is significantly different from existing nodelevel or networklevel power control methods. Also different from most existing simulation work, the ATPC design is guided by extensive field experiments of link quality dynamics at various locations and over a long period of time. The results from the realworld experiments demonstrate that 1) with pairwise adjustment, ATPC achieves more energy savings with a finer tuning capability and 2) with online control, ATPC is robust even with environmental changes over time.
A mathematical theory of network interference and its applications,
 Proc. IEEE 97
, 2009
"... A unifying framework is developed to characterize the aggregate interference in wireless networks, and several applications are presented. By Moe Z. Win, Fellow IEEE, Pedro C. Pinto, Student Member IEEE, and Lawrence A. Shepp ABSTRACT  In this paper, we introduce a mathematical framework for the c ..."
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Cited by 101 (13 self)
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A unifying framework is developed to characterize the aggregate interference in wireless networks, and several applications are presented. By Moe Z. Win, Fellow IEEE, Pedro C. Pinto, Student Member IEEE, and Lawrence A. Shepp ABSTRACT  In this paper, we introduce a mathematical framework for the characterization of network interference in wireless systems. We consider a network in which the interferers are scattered according to a spatial Poisson process and are operating asynchronously in a wireless environment subject to path loss, shadowing, and multipath fading. We start by determining the statistical distribution of the aggregate network interference. We then investigate four applications of the proposed model: 1) interference in cognitive radio networks; 2) interference in wireless packet networks; 3) spectrum of the aggregate radiofrequency emission of wireless networks; and 4) coexistence between ultrawideband and narrowband systems. Our framework accounts for all the essential physical parameters that affect network interference, such as the wireless propagation effects, the transmission technology, the spatial density of interferers, and the transmitted power of the interferers.
Correlated link shadow fading in multihop wireless networks
 IEEE Trans. Wireless Commun
, 2009
"... Abstract—Accurate representation of the physical layer is required for analysis and simulation of multihop networking in sensor, ad hoc, and mesh networks. Radio links that are geographically proximate often experience similar environmental shadowing effects and thus have correlated shadowing. This ..."
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Cited by 57 (15 self)
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Abstract—Accurate representation of the physical layer is required for analysis and simulation of multihop networking in sensor, ad hoc, and mesh networks. Radio links that are geographically proximate often experience similar environmental shadowing effects and thus have correlated shadowing. This paper presents and analyzes a nonsitespecific statistical propagation model which accounts for the correlations that exist in shadow fading between links in multihop networks. We describe two measurement campaigns to measure a large number of multihop networks in an ensemble of environments. The measurements show statistically significant correlations among shadowing experienced on different links in the network, with correlation coefficients up to 0.33. Finally, we analyze multihop paths in three and four node networks using both correlated and independent shadowing models and show that independent shadowing models can underestimate the probability of route failure by a factor of two or greater. Index Terms—Wireless sensor, ad hoc, mesh networks, shadowing, correlation, statistical channel model, wireless communication, measurement, performance I.
Coverage and Connectivity of Ad Hoc Networks in Presence of Channel Randomness
 in Proc. IEEE INFOCOM 2005
, 2005
"... In this paper, we present an analytical procedure for the computation of the node isolation probability in an ad hoc network in the presence of channel randomness, with applications to shadowing and fading phenomena. Such a probability coincides with the complement of the coverage probability, given ..."
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Cited by 53 (4 self)
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In this paper, we present an analytical procedure for the computation of the node isolation probability in an ad hoc network in the presence of channel randomness, with applications to shadowing and fading phenomena. Such a probability coincides with the complement of the coverage probability, given that nodes are distributed according to a Poisson point process. These results are used to obtain an estimate of the connectivity features for very dense networks. For the case of superimposed lognormal shadowing and Rayleigh fading, the connectivity improvements achievable by means of diversity schemes are investigated.
An analysis of unreliability and asymmetry in lowpower wireless links
 ACM Transactions on Sensor Networks
"... All intext references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately. ..."
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Cited by 52 (6 self)
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All intext references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately.
Effects of correlated shadowing: Connectivity, localization, and RF tomography
 In ACM/IEEE Information Processing in Sensor Networks (IPSN
, 2008
"... Unlike current models for radio channel shadowing indicate, realworld shadowing losses on different links in a network are not independent. The correlations have both detrimental and beneficial impacts on sensor, ad hoc, and mesh networks. First, the probability of network connectivity reduces when ..."
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Cited by 49 (16 self)
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Unlike current models for radio channel shadowing indicate, realworld shadowing losses on different links in a network are not independent. The correlations have both detrimental and beneficial impacts on sensor, ad hoc, and mesh networks. First, the probability of network connectivity reduces when link shadowing correlations are considered. Next, the variance bounds for sensor selflocalization change, and provide the insight that algorithms must infer localization information from link correlations in order to avoid significant degradation from correlated shadowing. Finally, a major benefit is that shadowing correlations between links enable the tomographic imaging of an environment from pairwise RSS measurements. This paper applies measurementbased models, and measurements themselves, to analyze and to verify both the benefits and drawbacks of correlated link shadowing. 1.
A Randomized, Efficient, and Distributed Protocol for the Detection of Node Replication Attacks in Wireless Sensor Networks
 MOBIHOC'07
, 2007
"... Wireless sensor networks are often deployed in hostile environments, where an adversary can physically capture some of the nodes. Once a node is captured, the attacker can reprogram it and replicate the node in a large number of clones, thus easily taking over the network. The detection of node rep ..."
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Cited by 46 (6 self)
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Wireless sensor networks are often deployed in hostile environments, where an adversary can physically capture some of the nodes. Once a node is captured, the attacker can reprogram it and replicate the node in a large number of clones, thus easily taking over the network. The detection of node replication attacks in a wireless sensor network is therefore a fundamental problem. A few distributed solutions have recently been proposed. However, these solutions are not satisfactory. First, they are energy and memory demanding: A serious drawback for any protocol that is to be used in resource constrained environment such as a sensor network. Further, they are vulnerable to specific adversary models introduced in this paper. The contributions of this work are threefold. First, we analyze the desirable properties of a distributed mechanism for the detection of node replication attacks. Second, we show that the known solutions for this problem do not completely meet our requirements. Third, we propose a new Randomized, Efficient, and Distributed (RED) protocol for the detection of node replication attacks and we show that it is completely satisfactory with respect to the requirements. Extensive simulations also show that our protocol is highly efficient in communication, memory, and computation, that it sets out an improved attack detection probability compared to the best solutions in the literature, and that it is resistant to the new kind of attacks we introduce in this paper, while other solutions are not.
An Analysis of Unreliability and Asymmetry in LowPower Wireless Links
"... Experimental studies have demonstrated that the behavior of real links in lowpower wireless networks (such as wireless sensor networks) deviates to a large extent from the ideal binary model used in several simulation studies. In particular, there is a large transitional region in wireless link qua ..."
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Cited by 45 (2 self)
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Experimental studies have demonstrated that the behavior of real links in lowpower wireless networks (such as wireless sensor networks) deviates to a large extent from the ideal binary model used in several simulation studies. In particular, there is a large transitional region in wireless link quality that is characterized by significant levels of unreliability and asymmetry, significantly impacting the performance of higherlayer protocols. We provide a comprehensive analysis of the root causes of unreliability and asymmetry. In particular, we derive expressions for the distribution, expectation, and variance of the packet reception rate as a function of distance, as well as for the location and extent of the transitional region. These expressions incorporate important environmental and radio parameters such as the path loss exponent and shadowing variance of the channel, and the modulation, encoding, and hardware variance of the radios.
Mieghem, “Connectivity in wireless ad–hoc networks with a log–normal radio model
 Mobile Networks and Applications
, 2006
"... Abstract. In this paper we study connectivity in wireless adhoc networks by modeling the network as an undirected geometric random graph. The novel aspect in our study is that for finding the link probability between nodes we use a radio model that takes into account statistical variations of the r ..."
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Cited by 39 (0 self)
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Abstract. In this paper we study connectivity in wireless adhoc networks by modeling the network as an undirected geometric random graph. The novel aspect in our study is that for finding the link probability between nodes we use a radio model that takes into account statistical variations of the radio signal power around its mean value. We show that these variations, that are unavoidably caused by the obstructions and irregularities in the surroundings of the transmitting and the receiving antennas, have two distinct effects on the network. Firstly, they reduce the amount of correlation between links causing the geometric random graph tend to behave like a random graph with uncorrelated links. Secondly, these variations increase the probability of long links, which enhances the probability of connectivity for the network. Another new result in our paper is an equation found for the calculation of the giant component size in wireless adhoc networks, that takes into account the level of radio signal power variations. With simulations we show that for the planning and design of wireless adhoc networks or sensor networks the giant component size is a good measure for “connectivity”.