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Proceedings Paper

The construction of a FBG-based hierarchical AOFSN with high reliability and scalability
Author(s): Li-mei Peng; Won-Hyuk Yang; Xin-wan Li; Young-Chon Kim
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Paper Abstract

To improve the reliability and scalability that are very important for large-scale all optical fiber sensor networks (AOFSN), three-level hierarchical sensor network architectures are proposed. The first two levels consist of active interrogation and RNs, respectively. The third level called sensor subnet (SSN) consists of passive FBGs and a few switches. As AOFSN is mainly multiplexed by wired and passive FBGs, the routing algorithm for scanning sensors is determined by the virtual topology of SSN due to the passivity. Therefore, the research concentrates on the construction of SSN and aims at proposing regular and unicursal virtual topology to realize reliable and scalable routing schemes. Two regular types of SSNs are proposed. Each type consists of several sensor cells (SC), square-based SC (SSC) or pentagon-based SC (PSC) and is scaled several times from the SCs. The virtual topologies maintain the self-similar square- or pentagon-like architecture so as to gain simple routing. Finally, the switch architecture of RN is proposed for the reliability of the first two levels; and then, the reliability and scalability of SSN are discussed in view of how much link failures can be tolerant, and how each SC is scaled to maintain the self-similarity, respectively.

Paper Details

Date Published: 11 November 2008
PDF: 12 pages
Proc. SPIE 7136, Optical Transmission, Switching, and Subsystems VI, 71362J (11 November 2008); doi: 10.1117/12.803518
Show Author Affiliations
Li-mei Peng, Chonbuk National Univ. (Korea, Republic of)
Won-Hyuk Yang, Chonbuk National Univ. (Korea, Republic of)
Xin-wan Li, Shanghai Jiao Tong Univ. (China)
Young-Chon Kim, Chonbuk National Univ. (Korea, Republic of)


Published in SPIE Proceedings Vol. 7136:
Optical Transmission, Switching, and Subsystems VI
Ken-ichi Kitayama; Pierpaolo C. Ghiggino; Kim Roberts; Yikai Su, Editor(s)

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