Geography-informed energy conservation for Ad Hoc routing

By Ya Xu, John S. Heidemann, Deborah Estrin. 2001

3,270 citations recorded by the source corpus.

Subfields: Computer Networks and Communications

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

In Computer Networks and Communications

Citations in the corpus

Over-the-air Function Computation in Sensor Networks (2016, background): “(a) Aggregated Wireless Sensor Networks : Most data aggregation work can be classified as: tree-based [17, 26, 16, 13], cluster-based [12, 27, 30, 18] or multipath [20, 19, 7].”
A Multi-Agent Framework for Packet Routing in Wireless Sensor Networks (2015, background): “GAF (geographic adaptive fidelity) [25] is an energy-aware location-based routing algorithm designed primarily for mobile ad hoc networks, but may be applicable to WSNs, as well.”
Research challenges and applications for underwater sensor networking (2006, neutral): “An application-level approach exploits dense deployment by putting redundant nodes into sleep [49], [8], [7].”
Rumor Routing Algorithm For Sensor Networks (2002, background): “[6] Moreover, because of the relatively short lifespan of nodes, as well as the large amount of system and data redundancy possible, it may be more useful to address data instead of individual nodes.”
A node scheduling scheme for energy conservation in large wireless sensor networks (2003, methodology): “In [13,15], the other two algorithms for dominating set formation are discussed, although the authors didn’t explicitly mention the concept of dominating set.”
A MAC protocol to reduce sensor network energy consumption using a wakeup radio (2005, background): “AFECA [13] and GAF [14] allow nodes to sleep based on their neighborhood size and geographic location, respectively.”
The Node Distribution of the Random Waypoint Mobility Model for Wireless Ad Hoc Networks (2003, methodology): “Such settings have been used, for instance, in the evaluation of routing ([11], [12], [18], [20], [21], [32]), multicast [27], and energy-conserving [33] protocols.”
Exploiting Sink Mobility for Maximizing Sensor Networks Lifetime (2005, methodology): “Previous research aimed toward this major goal has been prevalently concerned with developing techniques for topology control [ 2 ], [3], energy efficient MAC [4] and routing [5], [6].”
Topology management techniques for tolerating node failures in wireless sensor networks: A survey (2014, background): “Further classification is done within each category based on the system assumptions, required network state, metrics and objectives for the recovery process, etc.”
Ultra-low duty cycle MAC with scheduled channel polling (2006, background): “Separate from MAC protocols, as number of researchers have proposed higher-level approaches to conserve power, either as a topology management layer [28], [3], [22], integrated with routing, or at the application layer [20].”
Optimizing Sensor Networks in the Energy-Latency-Density Design Space (2002, background): “One of the key aspects is the organization of network communications as the radio is the main energy consumer in a sensor node [1], [3], [4].”
DCTC: dynamic convoy tree-based collaboration for target tracking in sensor networks (2004, methodology): “To save power, the sensor nodes stay in the sleep mode most of the time based on the geographical adaptive fidelity (GAF) protocol [20].”
Differentiated surveillance for sensor networks (2003, background): “Research on network topologies control addresses the problem of providing communication coverage within an energy conservation context such as SPAN [3], LEACH [8] and GAF [24] , to name a few.”
Wireless sensor networks for habitat monitoring (2002, methodology): “Methods like GAF [9] and SPAN [10] have been used to extend the longevity of the network by selecting representatives to participate in the network; thereby these algorithms reduce the average per node power consumption.”