An efficient organization mechanism for spatial networks
Fei Liu and
Qianchuan Zhao
Physica A: Statistical Mechanics and its Applications, 2006, vol. 366, issue C, 608-618
Abstract:
Spatial networks, also known as random geometric graphs, are random graphs with certain distance metric, in which each node is connected to some others within its neighborhood disc. Due to the rapid increase of network scales, the design of spatial networks becomes increasingly challenging. Inspired by the recently discovered small-world topology in relational networks, we identify an efficient organization mechanism for spatial networks, which we believe is useful for spatial network design. Two types of discs are introduced. Edges in the large discs are counterparts of “shortcuts.” We find that such “two-radius” spatial networks exhibit small characteristic path length, yet with low cost. This mechanism is applied to broadcasting protocol design for wireless ad hoc/sensor networks.
Keywords: Statistical physics of complex networks; Spatial network design; Small world; Optimization; Wireless ad hoc/sensor networks (search for similar items in EconPapers)
Date: 2006
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437105011118
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:366:y:2006:i:c:p:608-618
DOI: 10.1016/j.physa.2005.10.022
Access Statistics for this article
Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis
More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().