### Abstract

We propose a novel approach for sparse topology generation in wireless ad hoc networks based on a graph structure known as β-skeletons. Two efficient algorithms are presented in this paper for creating a connected topology from an underlying β-skeleton. One algorithm is a localized algorithm that uses two-hop neighborhood information to generate a connected topology, with a running time of O(n). The other is a distributed algorithm that runs on each component of the β-skeleton creating a connected structure from the disconnected β-skeleton graph, the running time is O(n log n). Simulations show consistent decrease in node degree in the resulting topology. The observed decrease is greater than 33% in comparison to the Relative Neighborhod Graph (RNG) and greater than 50% in comparison to other topology structures such as, the Gabriel Graph (GG) and the Yao construction on GG.

Original language | English (US) |
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Title of host publication | Conference Proceedings of the IEEE International Performance, Computing, and Communications Conference |

Editors | T. Dahlberg, R. Oliver, A. Sen, G. Xue |

Pages | 637-638 |

Number of pages | 2 |

State | Published - 2005 |

Event | 24th IEEE International Performance, Computing, and Communications Conference, IPCCC 2005 - Phoenix, AZ, United States Duration: Apr 7 2005 → Apr 9 2005 |

### Other

Other | 24th IEEE International Performance, Computing, and Communications Conference, IPCCC 2005 |
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Country | United States |

City | Phoenix, AZ |

Period | 4/7/05 → 4/9/05 |

### Fingerprint

### Keywords

- Bounded degree
- Distributed algorithm
- Localized algorithm
- Topology control
- Topology control structure
- Wireless ad hoc networks

### ASJC Scopus subject areas

- Engineering(all)

### Cite this

*Conference Proceedings of the IEEE International Performance, Computing, and Communications Conference*(pp. 637-638)

**Using β-skeletons for localized topology control in wireless ad hoc networks.** / Bhardwaj, Manvendu; Misra, Satyajayant; Xue, Guoliang.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*Conference Proceedings of the IEEE International Performance, Computing, and Communications Conference.*pp. 637-638, 24th IEEE International Performance, Computing, and Communications Conference, IPCCC 2005, Phoenix, AZ, United States, 4/7/05.

}

TY - GEN

T1 - Using β-skeletons for localized topology control in wireless ad hoc networks

AU - Bhardwaj, Manvendu

AU - Misra, Satyajayant

AU - Xue, Guoliang

PY - 2005

Y1 - 2005

N2 - We propose a novel approach for sparse topology generation in wireless ad hoc networks based on a graph structure known as β-skeletons. Two efficient algorithms are presented in this paper for creating a connected topology from an underlying β-skeleton. One algorithm is a localized algorithm that uses two-hop neighborhood information to generate a connected topology, with a running time of O(n). The other is a distributed algorithm that runs on each component of the β-skeleton creating a connected structure from the disconnected β-skeleton graph, the running time is O(n log n). Simulations show consistent decrease in node degree in the resulting topology. The observed decrease is greater than 33% in comparison to the Relative Neighborhod Graph (RNG) and greater than 50% in comparison to other topology structures such as, the Gabriel Graph (GG) and the Yao construction on GG.

AB - We propose a novel approach for sparse topology generation in wireless ad hoc networks based on a graph structure known as β-skeletons. Two efficient algorithms are presented in this paper for creating a connected topology from an underlying β-skeleton. One algorithm is a localized algorithm that uses two-hop neighborhood information to generate a connected topology, with a running time of O(n). The other is a distributed algorithm that runs on each component of the β-skeleton creating a connected structure from the disconnected β-skeleton graph, the running time is O(n log n). Simulations show consistent decrease in node degree in the resulting topology. The observed decrease is greater than 33% in comparison to the Relative Neighborhod Graph (RNG) and greater than 50% in comparison to other topology structures such as, the Gabriel Graph (GG) and the Yao construction on GG.

KW - Bounded degree

KW - Distributed algorithm

KW - Localized algorithm

KW - Topology control

KW - Topology control structure

KW - Wireless ad hoc networks

UR - http://www.scopus.com/inward/record.url?scp=28444461095&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=28444461095&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:28444461095

SP - 637

EP - 638

BT - Conference Proceedings of the IEEE International Performance, Computing, and Communications Conference

A2 - Dahlberg, T.

A2 - Oliver, R.

A2 - Sen, A.

A2 - Xue, G.

ER -