Connected sensor cover: self-organization of sensor networks for efficient query execution

By Himanshu Gupta, Samir R Das, Quinyi Gu. IEEE/ACM Transactions on Networking, 2003

459 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering, Media Technology

View Paper: https://www.semanticscholar.org/paper/6116f7f0351c35d5cde0a7aa20af54bae7139e4a

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

In Electrical and Electronic Engineering

In Media Technology

Citations in the corpus

Coverage problems in sensor networks: A survey (2011, methodology): “A greedy algorithm [Gupta et al. 2003, 2006] to select connected active nodes can be as follows: At each selection stage, only those nodes in N (Sa) are considered, and the node in N (Sa) that can maximize a pro.t function is selected.”
Relay node placement in large scale wireless sensor networks (2006, unknown): “The authors of [ 7 ] propose an approximation algorithm to compute a connected sensor cover which includes minimum number of sensor nodes forming a connected topology.”
Coverage and connectivity issues in wireless sensor networks: A survey (2008, methodology): “Under this category of selecting an optimal number of nodes to provide connected-coverage, the problem of minimum connected-sensor cover (MCSC) [24] is well known.”
A distributed coverage- and connectivity-centric technique for selecting active nodes in wireless sensor networks (2005, background): “In [ 14 ], Gupta et al. proposed a greedy algorithm for efficient querying based on the notion of a connected sensor cover, which manages the topology without sacrificing connectivity and sensing coverage.”
A dynamic clustering and energy efficient routing technique for sensor networks (2007, background): “Another way is to select a minimum set of sensors that form a connected communication graph to cover the entire network region, by iteratively searching for one path at a time and adding the nodes of the path to a set of already selected sensors [7].”
Near-optimal sensor placements: maximizing information while minimizing communication cost (2006, background): “Existing work on sensor placement under communication constraints [11, 13, 6] has considered the problem mainly from a geometric perspective: Sensors have a fixed sensing region, such as a disc with a certain radius, and can only communicate with other sensors which are at most a specified distance ”
Maintaining Sensing Coverage and Connectivity in Large Sensor Networks (2005, methodology): “On the other hand, the work in [11] assumes error-free channels and requires reliable broadcasting in a certain range, which is hard to implement in wireless environments.”