A cone-based distributed topology-control algorithm for wireless multi-hop networks
By Erran L. Li, Joseph Y. Halpern, Paramvir Victor Bahl, Yi-Min Wang, Roger Wattenhofer. IEEE/ACM Transactions on Networking, 2005
343 citations recorded by the source corpus.
Subfields: Computer Networks and Communications
View Paper: https://www.semanticscholar.org/paper/57fe4f1c2ca7875061c1b1a04702a6cd4518be67
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In Computer Networks and Communications
- Magnus Egerstedt
- Michael M. Zavlanos
- George Pappas
- Kin Kwong Leung
- Ming Yu
- Xuemin Shen
- Y. Şekercioğlu
- Aniket Malvankar
Citations in the corpus
- Distributed connectivity control of mobile networks (2007, background): “Closely related to the topics discussed in this paper, is also work in ad-hoc sensor networks, involving cone-based topology control [7] as well as distributed algorithms that do not assume exact knowledge of agent positions [8], which, however, focuses more on the power consumption and routing prob”
- A dynamic clustering and energy efficient routing technique for sensor networks (2007, background): “A problem that is closely related to the static clustering is the localized topology control, which maintains an energy-efficient network connectivity by controlling the transmission power at each node [ 4 ], or selecting a small subset of the local links of a node [5].”
- Topology control for wireless sensor networks (2003, background): “[15] Li L, Halpern JY, Bahl P, Wang YM, Wattenhofer R.”
- A Survey on Distributed Topology Control Techniques for Extending the Lifetime of Battery Powered Wireless Sensor Networks (2013, background): “For example, many authors [11], [13], [42], [44], [64], [53], [79] consider topology control as a technique whereby nodes dynamically change their transmission range to gain energy saving and/or improve throughput.”
- Graph-theoretic connectivity control of mobile robot networks (2011, background): “This line of research has given rise to connectivity or topology control algorithms that regulate the transmission power of the nodes and, therefore, their communication range, and range from cone-based approaches [24], [25] to distributed algorithms that do not involve any position information of t”