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119
Range-Free Localization Schemes for Large Scale Sensor Networks
, 2003
"... Wireless Sensor Networks have been proposed for a multitude of location-dependent applications. For such systems, the cost and limitations of hardware on sensing nodes prevent the use of range-based localization schemes that depend on absolute point-to-point distance estimates. Because coarse accura ..."
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Cited by 525 (8 self)
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Wireless Sensor Networks have been proposed for a multitude of location-dependent applications. For such systems, the cost and limitations of hardware on sensing nodes prevent the use of range-based localization schemes that depend on absolute point-to-point distance estimates. Because coarse accuracy is sufficient for most sensor network applications, solutions in range-free localization are being pursued as a cost-effective alternative to more expensive range-based approaches. In this paper, we present APIT, a novel localization algorithm that is range-free. We show that our APIT scheme performs best when an irregular radio pattern and random node placement are considered, and low communication overhead is desired. We compare our work via extensive simulation, with three state-of-the-art range-free localization schemes to identify the preferable system configurations of each. In addition, we study the effect of location error on routing and tracking performance. We show that routing performance and tracking accuracy are not significantly affected by localization error when the error is less than 0.4 times the communication radio radius.
An Energy Efficient Hierarchical Clustering Algorithm for Wireless Sensor Networks
, 2003
"... A wireless network consisting of a large number of small sensors with low-power transceivers can be an effective tool for gathering data in a variety of environments. The data collected by each sensor is communicated through the network to a single processing center that uses all reported data to de ..."
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Cited by 390 (1 self)
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A wireless network consisting of a large number of small sensors with low-power transceivers can be an effective tool for gathering data in a variety of environments. The data collected by each sensor is communicated through the network to a single processing center that uses all reported data to determine characteristics of the environment or detect an event. The communication or message passing process must be designed to conserve the Hmited energy resources of the sensors. Clustering sensors into groups, so that sensors communicate information only to clusterheads and then the clusterheads communicate the aggregated information to the processing center, may save energy. In this paper, we propose a distributed, randomized clustering algorithm to organize the sensors in a wireless sensor network into clusters. We then extend this algorithm to generate a hierarchy of clusterheads and observe that the energy savings increase with the number of levels in the hierarchy. Results in stochastic geometry are used to derive solutions for the values of parameters of our algorithm that minimize the total energy spent in the network when all sensors report data through the clusterheads to the processing center.
An Incremental Self-Deployment Algorithm for Mobile Sensor Networks
- AUTONOMOUS ROBOTS, SPECIAL ISSUE ON INTELLIGENT EMBEDDED SYSTEMS
, 2001
"... This paper describes an incremental deployment algorithm for mobile sensor networks. A mobile sensor network is a distributed collection of nodes, each of which has sensing, computation, communication and locomotion capabilities. The algorithm deploys nodes one-at-atime into an unknown environment, ..."
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Cited by 228 (9 self)
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This paper describes an incremental deployment algorithm for mobile sensor networks. A mobile sensor network is a distributed collection of nodes, each of which has sensing, computation, communication and locomotion capabilities. The algorithm deploys nodes one-at-atime into an unknown environment, with each node making use of information gathered by previously deployed nodes to determine its target location. The algorithm is designed to maximize network `coverage' whilst simultaneously ensuring that nodes retain line-of-sight with one another (this latter constraint arises from the need to localize the nodes; in our previous work on mesh-based localization [12, 13] we have shown how nodes can localize themselves in a completely unknown environment by using other nodes as landmarks). This paper describes the incremental deployment algorithm and presents the results of an extensive series of simulation experiments. These experiments serve to both validate the algorithm and illuminate its empirical properties.
Sensor Deployment and Target Localization Based on Virtual Forces
, 2003
"... The effectiveness of cluster-based distributed sensor networks depends to a large extent on the coverage provided by the sensor deployment. We propose a virtual force algorithm (VFA) as a sensor deployment strategy to enhance the coverage after an initial random placement of sensors. For a given num ..."
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Cited by 211 (3 self)
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The effectiveness of cluster-based distributed sensor networks depends to a large extent on the coverage provided by the sensor deployment. We propose a virtual force algorithm (VFA) as a sensor deployment strategy to enhance the coverage after an initial random placement of sensors. For a given number of sensors, the VFA algorithm attempts to maximize the sensor field coverage. A judicious combination of attractive and repulsive forces is used to determine virtual motion paths and the rate of movement for the randomly-placed sensors. Once the effective sensor positions are identified, a one-time movement with energy consideration incorporated is carried out, i.e., the sensors are redeployed to these positions. We also propose a novel probabilistic target localization algorithm that is executed by the cluster head. The localization results are used by the cluster head to query only a few sensors (out of those that report the presence of a target) for more detailed information. Simulation results are presented to demonstrate the effectiveness of the proposed approach.
Sensor Positioning in Wireless Ad-hoc Sensor Networks Using Multidimensional Scaling
, 2004
"... Sensor Positioning is a fundamental and crucial issue for sensor network operation and management. In the paper, we first study some situations where most existing sensor positioning methods tend to fail to perform well, an example being when the topology of a sensor network is anisotropic. Then, we ..."
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Cited by 147 (0 self)
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Sensor Positioning is a fundamental and crucial issue for sensor network operation and management. In the paper, we first study some situations where most existing sensor positioning methods tend to fail to perform well, an example being when the topology of a sensor network is anisotropic. Then, we explore the idea of using dimensionality reduction techniques to estimate sensors coordinates in two (or three) dimensional space, and we propose a distributed sensor positioning method based on multidimensional scaling technique to deal with these challenging conditions. Multidimensional scaling and coordinate alignment techniques are applied to recover positions of adjacent sensors. The estimated positions of the anchors are compared with their true physical positions and corrected, The positions of other sensors are corrected accordingly. With iterative adjustment, our method can overcome adverse network and terrain conditions, and generate accurate sensor position. We also propose an on demand sensor positioning method based on the above method.
Scalable coordination for wireless sensor networks: self-configuring localization systems
- in Proc. 6th International Symposium on Communication Theory and Applications (ISCTA ’01),Ambleside, Lake District
, 2001
"... Pervasive networks of micro-sensors and actuators offer to revolutionize the ways in which we understand and construct complex physical systems. Sensor networks must be scalable, long-lived and robust systems, overcoming energy limitations and a lack of pre-installed infrastructure. We explore three ..."
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Cited by 128 (1 self)
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Pervasive networks of micro-sensors and actuators offer to revolutionize the ways in which we understand and construct complex physical systems. Sensor networks must be scalable, long-lived and robust systems, overcoming energy limitations and a lack of pre-installed infrastructure. We explore three themes in the design of self-configuring sensor networks: tuning density to trade operational quality against lifetime; using multiple sensor modalities to obtain robust measurements; and exploiting fixed environmental characteristics. We illustrate these themes through the problem of localization, which is a key building block for sensor systems that itself requires coordination.
Sensor placement for effective coverage and surveillance in distributed sensor networks
- IEEE Wireless Communications and Networking
, 2003
"... Abstract- We present two algorithms for the efficient placement of sensors in a sensor field. The proposed approach is aimed at optimizing the number of sensors and determining their placement to support distributed sensor networks. The optimization framework is inherently probabilistic due to the u ..."
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Cited by 109 (3 self)
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Abstract- We present two algorithms for the efficient placement of sensors in a sensor field. The proposed approach is aimed at optimizing the number of sensors and determining their placement to support distributed sensor networks. The optimization framework is inherently probabilistic due to the uncertainty associated with sensor detections. The proposed algorithms address coverage optimization under the constraints of imprecise detections and terrain properties. These algorithms are targeted at average coverage as well as at maximizing the coverage of the most vulnerable grid points. The issue of preferential coverage of grid points (based on relative measures of security and tactical importance) is also modeled. Experimental results for an example sensor field with obstacles demonstrate the application of our approach. Keywords-Ad hoc wireless sensor networks; preferential coverage; obstacles; sensor detection; sensor field coverage; terrain modeling. I.
Sensor Placement for Grid Coverage under Imprecise Detections
- In Proceedings of International Conference on Information Fusion
, 2002
"... We present a resource-bounded optimization framework for sensor resource management under the constraints of sufficient grid coverage of the sensor field. We offer a unique "minimalistic" view of distributed sensor networks in which sensors transmit/report a minimum amount of sensed data. ..."
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Cited by 96 (2 self)
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We present a resource-bounded optimization framework for sensor resource management under the constraints of sufficient grid coverage of the sensor field. We offer a unique "minimalistic" view of distributed sensor networks in which sensors transmit/report a minimum amount of sensed data. The proposed theory is aimed at optimizing the number of sensors and determine their placement to support such minimalistic sensor networks. We represent the sensor field as a grid (two- or three-dimensional) of points. The optimization framework is inherently probabilistic due to the uncertainty associated with sensor detections. The proposed algorithm addresses coverage optimization under constraints of imprecise detections and terrain properties. The issue of preferential coverage of grid points (based on relative measures of security and tactical importance) is also modeled. Experimental results for an example sensor field with obstacles demonstrate the application of our approach.
Sensor Deployment and Target Localization in Distributed Sensor Networks
- ACM TRANSACTIONS ON EMBEDDED COMPUTING SYSTEMS
, 2004
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Self-Configuring Localization Systems: Design and Experimental Evaluation
- ACM TRANSACTIONS ON EMBEDDED COMPUTING SYSTEMS
, 2003
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