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Connectivity in AdHoc and Hybrid Networks
 IN PROC. IEEE INFOCOM
, 2002
"... We consider a largescale wireless network, but with a low density of nodes per unit area. Interferences are then less critical, contrary to connectivity. This paper studies the latter property for both a purely adhoc network and a hybrid network, where fixed base stations can be reached in multipl ..."
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Cited by 160 (6 self)
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We consider a largescale wireless network, but with a low density of nodes per unit area. Interferences are then less critical, contrary to connectivity. This paper studies the latter property for both a purely adhoc network and a hybrid network, where fixed base stations can be reached in multiple hops. We assume here that power constraints are modeled by a maximal distance above which two nodes are not (directly) connected. We find that
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 100 (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 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
On The Symmetric Range Assignment Problem In Wireless Ad Hoc Networks
, 2002
"... In this paper we consider a constrained version of the range assignment problem for wireless ad hoc networks, where the value the node transmitting ranges must be assigned in such a way that the resulting communication graph is strongly connected and the energy cost is minimum. We impose the further ..."
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Cited by 38 (1 self)
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In this paper we consider a constrained version of the range assignment problem for wireless ad hoc networks, where the value the node transmitting ranges must be assigned in such a way that the resulting communication graph is strongly connected and the energy cost is minimum. We impose the further requirement of symmetry on the resulting communication graph. We also consider a weaker notion of symmetry, in which only the existence of a set of symmetric edges that renders the communication graph connected is required. Our interest in these problems is motivated by the fact that a (weakly) symmetric range assignment can be more easily integrated with existing higher and lowerlevel protocols for ad hoc networks, which assume that all the nodes have the same transmitting range. We show that imposing symmetry does not change the complexity of the problem, which remains NPhard in two and threedimensional networks. We also show that a weakly symmetric range assignment can reduce the energy cost considerably with respect to the homogeneous case, in which all the nodes have the same transmitting range, and that no further (asymptotic) bene t is expected from the asymmetric range assignment. Hence, the results presented in this paper indicate that weak symmetry is a desirable property of the range assignment.
Strong minimum energy topology in wireless sensor networks: NPcompleteness and heuristics
 IEEE Transactions on Mobile Computing 2(3) (JulySeptember
"... Abstract—Wireless sensor networks have recently attracted lots of research effort due to its wide range of applications. These networks must operate for months or years. However, the sensors are powered by battery, which may not be possible to be recharged after they are deployed. Thus, energyaware ..."
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Cited by 28 (5 self)
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Abstract—Wireless sensor networks have recently attracted lots of research effort due to its wide range of applications. These networks must operate for months or years. However, the sensors are powered by battery, which may not be possible to be recharged after they are deployed. Thus, energyaware network management is extremely important. In this paper, we study the following problem: Given a set of sensors in the plane, assign transmit power to each sensor such that the induced topology containing only bidirectional links is strongly connected. This problem is significant in both theory and application. We prove its NPCompleteness and propose two heuristics: power assignment based on minimum spanning tree (denoted by MST) and incremental power. We also show that MST heuristic has a performance ratio of 2. Simulation study indicates that the performance of these two heuristics does not differ very much, but, in average, the incremental power heuristic is always better than MST. Index Terms—Minimum energy topology, power control, wireless sensor networks, NPCompleteness, incremental power heuristic. æ 1
A Statistical Analysis of the LongRun Node Spatial Distribution in Mobile Ad Hoc Networks
, 2002
"... In this paper, we analyze the node spatial distribution of a mobile wireless ad hoc networks. Characterizing this distribution is of fundamental importance in the analysis of many relevant properties of mobile ad hoc networks, such as connectivity, average route length, and network capacity. In part ..."
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Cited by 26 (3 self)
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In this paper, we analyze the node spatial distribution of a mobile wireless ad hoc networks. Characterizing this distribution is of fundamental importance in the analysis of many relevant properties of mobile ad hoc networks, such as connectivity, average route length, and network capacity. In particular, we have investigated under what conditions the node spatial distribution resulting after a large number of mobility steps resembles the uniform distribution. This is motivated by the fact that the existing theoretical results concerning mobile ad hoc networks are based on this assumption. In order to test this hypothesis, we performed extensive simulations using two wellknown mobility models: the random waypoint model, which resembles intentional movement, and a Brownianlike model, which resembles nonintentional movement. Our analysis has shown that in the Brownianlike motion the uniformity assumption does hold, and that the intensity of the concentration of nodes in the center of the deployment region that occurs in the random waypoint model heavily depends on the choice of some mobility parameters. For extreme values of these parameters, the uniformity assumption is impaired.
Topology Control in Ad hoc Wireless Networks with Hitchhiking
, 2004
"... In this paper, we address the Topology Control with Hitchhiking (TCH) problem. Hitchhiking [1] is a novel model introduced recently that allows combining partial messages to decode a complete message. By effective use of partial signals, a specific topology can be obtained with less transmission ..."
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Cited by 17 (1 self)
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In this paper, we address the Topology Control with Hitchhiking (TCH) problem. Hitchhiking [1] is a novel model introduced recently that allows combining partial messages to decode a complete message. By effective use of partial signals, a specific topology can be obtained with less transmission power. The objective of the TCH problem is to obtain a stronglyconnected topology with minimum total energy consumption. We prove the TCH problem to be NPcomplete and design a distributed and localized algorithm (DTCH) that can be applied on top of any symmetric, stronglyconnected topology to reduce total power consumption. We analyze the performance of our approach through simulation.