Results 1 - 10 of 2,307

On determining cluster size of randomly deployed heterogeneous WSNs

by Cüneyt Sevgi , Altan Koçyigit - IEEE Communications Letters , 2008
"... Abstract-Clustering is an efficient method to solve scalability problems and energy consumption challenges. For this reason it is widely exploited in Wireless Sensor Network (WSN) applications. It is very critical to determine the number of required clusterheads and thus the overall cost of WSNs wh ..."
Abstract - Cited by 4 (0 self) - Add to MetaCart
while satisfying the desired level of coverage. Our objective is to study cluster size, i.e., how much a clusterhead together with sensors can cover a region when all the devices in a WSN are deployed randomly. Therefore, it is possible to compute the required number of nodes of each type for given

Coverage by Randomly Deployed Wireless Sensors Networks

by Peng-jun Wan, Chih-wei Yi - IEEE Trans. Inform. Theory 2006
"... One of the main applications of wireless sensor networks is to provide proper coverage of their deployment regions. A wireless sensor network k-covers its deployment region if every point in its deployment region is within the coverage ranges of at least k sensors. In this paper, we assume that the ..."
Abstract - Cited by 53 (3 self) - Add to MetaCart
One of the main applications of wireless sensor networks is to provide proper coverage of their deployment regions. A wireless sensor network k-covers its deployment region if every point in its deployment region is within the coverage ranges of at least k sensors. In this paper, we assume

Random Key Predistribution Schemes for Sensor Networks”,

by Haowen Chan , Adrian Perrig , Dawn Song - IEEE Symposium on Security and Privacy, , 2003
"... Abstract Efficient key distribution is the basis for providing secure communication, a necessary requirement for many emerging sensor network applications. Many applications require authentic and secret communication among neighboring sensor nodes. However, establishing keys for secure communicatio ..."
Abstract - Cited by 832 (12 self) - Add to MetaCart
before deployment. In the field, neighboring nodes exchange information to find one common key within their random subset and use that key as their shared secret to secure subsequent communication. In this paper, we generalize the Eschenauer-Gligor key distribution approach. First, we propose two new

Minimum energy mobile wireless networks

by Volkan Rodoplu, Teresa H. Meng - IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS , 1999
"... We describe a distributed position-based network protocol optimized for minimum energy consumption in mobile wireless networks that support peer-to-peer communications. Given any number of randomly deployed nodes over an area, we illustrate that a simple local optimization scheme executed at each n ..."
Abstract - Cited by 749 (0 self) - Add to MetaCart
We describe a distributed position-based network protocol optimized for minimum energy consumption in mobile wireless networks that support peer-to-peer communications. Given any number of randomly deployed nodes over an area, we illustrate that a simple local optimization scheme executed at each

Monitoring Schedules for Randomly Deployed Sensor Networks

by Gruia Calinescu, Robert B. Ellis - WORKSHOP ON DISCRETE ALGOTHRITHMS AND METHODS FOR MOBILE COMPUTING AND COMMUNICATIONS , 2009
"... Given n sensors and m targets, a monitoring schedule is a partition of the sensor set such that each part of the partition can monitor all targets. Monitoring schedules are used to maximize the time all targets are monitored when there is no possibility of replacing the batteries of the sensors. Eac ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
sensors are randomly distributed uniformly in a large square containing the targets, 3) the number of sensors is high enough given the area the square, and 4) the communication range is twice the sensing range (thus any two sensors which can monitor the same target can communicate in one hop). Our results

Performance Analysis of Quasi-Random Deployment Strategy in Sensor Networks

by Itu Snigdh , Nisha Gupta
"... Abstract-This article evaluates the performance of a quasi random deployment strategy for wireless sensor networks on the basis of the application invoked for tree based communication networks. The quasi random deployment strategy tries to combine the benefits of both random and deterministic appro ..."
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Abstract-This article evaluates the performance of a quasi random deployment strategy for wireless sensor networks on the basis of the application invoked for tree based communication networks. The quasi random deployment strategy tries to combine the benefits of both random and deterministic

Is Deterministic Deployment Worse than Random Deployment for Wireless Sensor Networks?

by unknown authors
"... Abstract — Before a sensor network is deployed, it is important to determine how many sensors are required to achieve a certain coverage degree. The number of sensor required for maintaining k-coverage depends on the area of the monitored region, the probability that a node fails or powers off (to s ..."
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save energy), and the deployment strategy. In this paper, we derive the density required to maintain k-coverage under three deployment strategies: (i) nodes are deployed as a Poisson point process, (ii) nodes are uniformly randomly distributed, (iii) nodes are deployed on regular grids. Our results

1 Is Deterministic Deployment Worse than Random Deployment for Wireless Sensor Networks?

by Honghai Zhang, Jennifer C. Hou
"... Abstract — Before a sensor network is deployed, it is important to determine how many sensors are required to achieve a certain coverage degree. The number of sensor required for maintaining k-coverage depends on the area of the monitored region, the probability that a node fails or powers off (to s ..."
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save energy), and the deployment strategy. In this paper, we derive the density required to maintain k-coverage under three deployment strategies: (i) nodes are deployed as a Poisson point process, (ii) nodes are uniformly randomly distributed, (iii) nodes are deployed on regular grids. Our results

Comment to “Coverage by Randomly Deployed Wireless Sensor Networks”.

by Bhupendra Gupta , 904
"... In the above paper, Lemma (4), on page 2659 play the key role for deriving the main results in the paper. The statement as well as the proof of Lemma (4), page 2659, [1] is not correct. Here mainly two serious errors in this ..."
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In the above paper, Lemma (4), on page 2659 play the key role for deriving the main results in the paper. The statement as well as the proof of Lemma (4), page 2659, [1] is not correct. Here mainly two serious errors in this

Learning in graphical models

by Michael I. Jordan - STATISTICAL SCIENCE , 2004
"... Statistical applications in fields such as bioinformatics, information retrieval, speech processing, image processing and communications often involve large-scale models in which thousands or millions of random variables are linked in complex ways. Graphical models provide a general methodology for ..."
Abstract - Cited by 806 (10 self) - Add to MetaCart
Statistical applications in fields such as bioinformatics, information retrieval, speech processing, image processing and communications often involve large-scale models in which thousands or millions of random variables are linked in complex ways. Graphical models provide a general methodology
Results 1 - 10 of 2,307