Data gathering in sensor networks using the energy*delay metric

By Stephanie Lindsey, Cauligi S. Raghavendra, Krishna M. Sivalingam. Proceedings, International Parallel and Distributed Processing Symposium (IPDPS), 2001

461 citations recorded by the source corpus.

Subfields: Computer Networks and Communications

View Paper: https://www.semanticscholar.org/paper/f9b29c8580a1d794477059fdef29c59e66f38001

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In Computer Networks and Communications

Citations in the corpus

An efficient clustering-based heuristic for data gathering and aggregation in sensor networks (2003, background): “Lindsey et al [12] describe a hierarchical scheme based on PEGASIS that reduces the average energy consumed and delay incurred in gathering the sensed data.”
Efficient algorithms for maximum lifetime data gathering and aggregation in wireless sensor networks (2003, methodology): “[15] describe a hierarchical scheme based on PEGASIS that reduces the average energy consumed and delay incurred in gathering the sensed data.”
A survey on routing protocols for wireless sensor networks (2005, methodology): “Both MLDR and MLDA are implemented and compared to hierarchical-PEGASIS [21] in terms of system lifetime.”
A Survey of Energy-Efficient Hierarchical Cluster-Based Routing in Wireless Sensor (2010, methodology): “Hierarchical PEGASIS: An extension to PEGASIS, called Hierarchical-PEGASIS was introduced in [43] with the objective of decreasing the delay incurred for packets during transmission to the BS.”
Routing Protocols in Wireless Sensor Networks - A Survey (2010, background): “Braided Paths: Braided multipath [49,50] is a partially disjoint path from primary one after relaxing the disjointedness constraint.”
A survey on clustering algorithms for wireless sensor networks (2007, background): “In networks of homogenous sensor nodes, i.e. all having equal capacity in terms of computation, communication and power, CHs are picked from the deployed sensors [20,35,36].”
Sensor networks with mobile agents (2003, background): “MAC protocols are developed [17] for the transmission from sensors to cluster heads and a variation of this architecture with improved performance is developed in [18].”
MAXIMUM LIFETIME DATA GATHERING AND AGGREGATION IN WIRELESS SENSOR NETWORKS (2002, methodology): “Second, compute a solution to the linear program that consists of equations (9) and (10), by fixing the values of the fi,j variables to the floor of their values obtained in the previous step.”
Energy-efficient computing for wildlife tracking: design tradeoffs and early experiences with ZebraNet (2002, background): “However, the routing algorithms proposed thus far [12, 17, 28] assume stat ic sensor networks, i.”
Low energy adaptive clustering hierarchy with deterministic cluster-head selection (2002, background): “present an interesting chain-based algorithm to solve the problem of collecting data from a microsensor network [13].”
An Energy-Efficient Ant-Based Routing Algorithm for Wireless Sensor Networks (2006, methodology): “Compared to LEACH, the PEGASIS protocol obtains up to 100% of energy cost improvement per round [4].”
On network correlated data gathering (2004, methodology): “The work in [9] introduces the PEGASIS algorithm, that uses the energy × delay metric over the routing tree; their algorithms find chains of nodes instead of clusters.”