Proceedings of the 2015 International Conference on Industrial Technology and Management Science

A Borrowed Address Assignment Algorithm Based on the Depth Model for ZigBee Network

Authors
Leqiang Bai, Zhenhu Zhang
Corresponding Author
Leqiang Bai
Available Online November 2015.
DOI
https://doi.org/10.2991/itms-15.2015.425How to use a DOI?
Keywords
ZigBee network; Orphan node; Address assignment; Depth model; Tree routing
Abstract
Aiming at the problems of the shortcomings of the ZigBee distributed address assignment mechanism lead to orphan nodes and the lower success rate of address assignment, a borrowed address assignment algorithm based on the depth model for ZigBee network is proposed. The algorithm utilizes 16-bit network address that DAAM algorithm unused to assign addresses for different network depth orphan nodes. Meanwhile, the tree routing algorithm to suit the address assignment mechanism is proposed. Theoretical analysis and simulation results show that, in the condition of the same computational complexity and the same maximum network depth, the algorithm outperforms DAAM, SLAR, DAAM-THN and SOSSA in terms of the success rate of address assignment, and the average time of assigning address etc.
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

Proceedings
2015 International Conference on Industrial Technology and Management Science
Part of series
Advances in Computer Science Research
Publication Date
November 2015
ISBN
978-94-6252-123-0
ISSN
2352-538X
DOI
https://doi.org/10.2991/itms-15.2015.425How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Leqiang Bai
AU  - Zhenhu Zhang
PY  - 2015/11
DA  - 2015/11
TI  - A Borrowed Address Assignment Algorithm Based on the Depth Model for ZigBee Network
BT  - 2015 International Conference on Industrial Technology and Management Science
PB  - Atlantis Press
SN  - 2352-538X
UR  - https://doi.org/10.2991/itms-15.2015.425
DO  - https://doi.org/10.2991/itms-15.2015.425
ID  - Bai2015/11
ER  -