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Topology Control of Multihop Wireless Networks using Transmit Power Adjustment
, 2000
"... We consider the problem of adjusting the transmit powers of nodes in a multihop wireless network (also called an ad hoc network) to create a desired topology. We formulate it as a constrained optimization problem with two constraints  connectivity and biconnectivity, and one optimization objective ..."
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Cited by 535 (3 self)
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We consider the problem of adjusting the transmit powers of nodes in a multihop wireless network (also called an ad hoc network) to create a desired topology. We formulate it as a constrained optimization problem with two constraints  connectivity and biconnectivity, and one optimization objective  maximum power used. We present two centralized algorithms for use in static networks, and prove their optimality. For mobile networks, we present two distributed heuristics that adaptively adjust node transmit powers in response to topological changes and attempt to maintain a connected topology using minimum power. We analyze the throughput, delay, and power consumption of our algorithms using a prototype software implementation, an emulation of a powercontrollable radio, and a detailed channel model. Our results show that the performance of multihop wireless networks in practice can be substantially increased with topology control.
Distributed topology control for power efficient operation in multihop wireless ad hoc networks
, 2001
"... Abstract — The topology of wireless multihop ad hoc networks can be controlled by varying the transmission power of each node. We propose a simple distributed algorithm where each node makes local decisions about its transmission power and these local decisions collectively guarantee global connecti ..."
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Cited by 313 (20 self)
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Abstract — The topology of wireless multihop ad hoc networks can be controlled by varying the transmission power of each node. We propose a simple distributed algorithm where each node makes local decisions about its transmission power and these local decisions collectively guarantee global connectivity. Specifically, based on the directional information, a node grows it transmission power until it finds a neighbor node in every direction. The resulting network topology increases network lifetime by reducing transmission power and reduces traffic interference by having low node degrees. Moreover, we show that the routes in the multihop network are efficient in power consumption. We give an approximation scheme in which the power consumption of each route can be made arbitrarily close to the optimal by carefully choosing the parameters. Simulation results demonstrate significant performance improvements. I.
Faulttolerant and 3Dimensional Distributed Topology Control Algorithms in Wireless Multihop Networks
 in Proceedings of the 11th IEEE International Conference on Computer Communications and Networks (ICCCN
, 2002
"... We can control the topology of a multihop wireless network by varying the transmission power at each node. The lifetime of such networks depends on battery power at each node. This paper presents a distributed faulttolerant topology control algorithm for minimum energy consumption in these net ..."
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Cited by 60 (9 self)
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We can control the topology of a multihop wireless network by varying the transmission power at each node. The lifetime of such networks depends on battery power at each node. This paper presents a distributed faulttolerant topology control algorithm for minimum energy consumption in these networks. More precisely, we present algorithms which preserve the connectivity of a network upon failing of, at most, k nodes (k is constant) and simultaneously minimize the transmission power at each node to some extent. In addition, we present simulations to support the effectiveness of our algorithm. We also demonstrate some optimizations to further minimize the power at each node. Finally, we show how our algorithms can be extended to 3dimensions.
A ConeBased Distributed TopologyControl Algorithm for Wireless MultiHop Networks
 IEEE/ACM Transactions on Networking
, 2002
"... 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 does not assume that nodes have GPS information available; rather it dep ..."
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Cited by 39 (1 self)
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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 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 u,# required to ensure that in every cone of degree # around u, there is some node that u can reach with power p u,# . We show that taking # = 5#/6 is a necessary and su#cient condition to guarantee that network connectivity is preserved. More precisely, if there is a path from s to t when every node communicates at maximum power then, if # 5#/6, there is still a path in the smallest symmetric graph G # containing all edges (u, v) such that u can communicate with v using power p u,# . On the other hand, if # > 5#/6, # This is a revised and extended version of "Analysis of a conebased topology control algorithm for wireless multihop networks", which appeared in Proceedings of ACM Principles of Distributed Computing (PODC), 2001, and includes results from "Distributed topology control for power e#cient operation in multihop wireless ad hoc networks", by R. Wattenhofer, L. Li, P. Bahl, and Y. M. Wang, which appeared in Proceedings of IEEE INFOCOM, 2001.
A MinimumEnergy PathPreserving TopologyControl Algorithm
"... The topology of a wireless multihop network can be controlled by varying the transmission power at each node. In general, it is not energy efficient to use the communication network where every node transmits with maximum power. For energy efficient operations, it is desirable to have a subnetwork ..."
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Cited by 7 (1 self)
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The topology of a wireless multihop network can be controlled by varying the transmission power at each node. In general, it is not energy efficient to use the communication network where every node transmits with maximum power. For energy efficient operations, it is desirable to have a subnetwork that preserves a minimumenergy path between every pair of nodes (where a minimumenergy path is one that allows messages to be transmitted with a minimum use of energy). In this paper, we first identify conditions that are necessary and sufficient for a subnetwork of to preserve this property. Using this characterization, we then propose an efficient topologycontrol algorithm that, given a communication network, computes a subnetwork that it preserves at least one minimumenergy path between every pair of nodes. We also propose an energyefficient reconfiguration protocol that maintains this minimumenergy path property as the network topology changes dynamically. We demonstrate the performance improvements of our algorithm over other existing topologycontrol algorithms through simulation.
Article On the Relevance of Using Open Wireless Sensor Networks in Environment Monitoring
, 2009
"... sensors ..."
Topology Control of Multihop Wireless Networks using Transmit Power Adjustment
"... AbstractWe consider the problem of adjusting the transmit powers of nodes in a multihop wireless network (also called an ad hoc network) to create a desired topology. We formulate it as a constrained optimization problem with two constraints connectivity and biconnectivity, and one optimization ob ..."
Abstract
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AbstractWe consider the problem of adjusting the transmit powers of nodes in a multihop wireless network (also called an ad hoc network) to create a desired topology. We formulate it as a constrained optimization problem with two constraints connectivity and biconnectivity, and one optimization objective maximum power used. We present two centralized algorithms for use in static networks, and prove their optimality. For mobile networks, we present two distributed heuristics that adaptively adjust node transmit powers in response to topological changes and attempt to maintain a connected topology using minimum power. We analyze the throughput, delay, and power consumption of our algorithms using a prototype software implementation, an emulation of a powercontrollable radio, and a detailed channel model. Our results show that the performance of multihop wireless networks in practice can be substantially increased with topology control. I.
Performance Evaluation for a QuasiSynchronous Packet Radio Network (QSPNET)
, 2001
"... We propose a new mediaaccess and connectionestablishment protocol for an adhoc quasisynchronous packet radio network (QSPNET). In the QSPNET, the bandwidth is partitioned into a data channel, used to transmit packets, and a control channel, used to make reservations. Transmitted waveforms in the ..."
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We propose a new mediaaccess and connectionestablishment protocol for an adhoc quasisynchronous packet radio network (QSPNET). In the QSPNET, the bandwidth is partitioned into a data channel, used to transmit packets, and a control channel, used to make reservations. Transmitted waveforms in the QSPNET are made quasisynchronous by using a local GPS clock. The QSPNET uses a novel linear decorrelator receiver for multiuser detection, which permits the reception of quasisynchronous code division multiple access (QSCDMA) waveforms. We initially describe the QSPNET and its connection and flow control protocols, giving the rules of transmission and reception followed by all mobiles. We also provide performance results for the case where connection requests are generated at each node of the QSPNET according to a random process over an infinite time horizon. In particular, we obtain results on the achievable throughput and the average delay as a function of the transmission radius, the quasisynchronous uncertainty interval, the duration of the connections, and the buffer size per node.
Topology Control of Multihop Wireless Networks using Transmit Power Adjustment
"... AbstractWeconsider the problem of adjusting the transmit powers of nodes in a multihop wireless network (also called an ad hoc network) to create a desired topology. We formulate it as a constrained optimization problem with two constraints connectivity and biconnectivity, and one optimization obj ..."
Abstract
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AbstractWeconsider the problem of adjusting the transmit powers of nodes in a multihop wireless network (also called an ad hoc network) to create a desired topology. We formulate it as a constrained optimization problem with two constraints connectivity and biconnectivity, and one optimization objective maximum power used. We present two centralized algorithms for use in static networks, and prove their optimality. For mobile networks, we present two distributed heuristics that adaptively adjust node transmit powers in response to topological changes and attempt to maintain a connected topology using minimum power. We analyze the throughput, delay, and power consumption of our algorithms using a prototype software implementation, an emulation of a powercontrollable radio, and a detailed channel model. Our results show that the performance of multihop wireless networks in practice can be substantially increased with topology control. I.
SelfOrganized FaultTolerant Feature Extraction in Distributed Wireless Sensor Networks
"... We propose a distributed solution for a canonical task in wireless sensor networks  the extraction of information about interesting environmental features. We explicitly take into account the possibility of sensor measurement faults and develop a distributed Bayesian algorithm for detecting and co ..."
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We propose a distributed solution for a canonical task in wireless sensor networks  the extraction of information about interesting environmental features. We explicitly take into account the possibility of sensor measurement faults and develop a distributed Bayesian algorithm for detecting and correcting such faults. Theoretical analysis and simulation results show that 8595% of faults can be corrected using this algorithm even when as many as 10% of the nodes are faulty.