CLC number: TP393
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 0000-00-00
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MAO Jian-lin, WU Zhi-ming. Optimal distributed resource allocation in a wireless sensor network for control systems[J]. Journal of Zhejiang University Science A, 2007, 8(1): 106-112.
@article{title="Optimal distributed resource allocation in a wireless sensor network for control systems",
author="MAO Jian-lin, WU Zhi-ming",
journal="Journal of Zhejiang University Science A",
volume="8",
number="1",
pages="106-112",
year="2007",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2007.A0106"
}
%0 Journal Article
%T Optimal distributed resource allocation in a wireless sensor network for control systems
%A MAO Jian-lin
%A WU Zhi-ming
%J Journal of Zhejiang University SCIENCE A
%V 8
%N 1
%P 106-112
%@ 1673-565X
%D 2007
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2007.A0106
TY - JOUR
T1 - Optimal distributed resource allocation in a wireless sensor network for control systems
A1 - MAO Jian-lin
A1 - WU Zhi-ming
J0 - Journal of Zhejiang University Science A
VL - 8
IS - 1
SP - 106
EP - 112
%@ 1673-565X
Y1 - 2007
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.2007.A0106
Abstract: Wireless technology is applied increasingly in networked control systems. A new form of wireless network called wireless sensor network can bring control systems some advantages, such as flexibility and feasibility of network deployment at low costs, while it also raises some new challenges. First, the communication resources shared by all the control loops are limited. Second, the wireless and multi-hop character of sensor network makes the resources scheduling more difficult. Thus, how to effectively allocate the limited communication resources for those control loops is an important problem. In this paper, this problem is formulated as an optimal sampling frequency assignment problem, where the objective function is to maximize the utility of control systems, subject to channel capacity constraints. Then an iterative distributed algorithm based on local buffer information is proposed. Finally, the simulation results show that the proposed algorithm can effectively allocate the limited communication resource in a distributed way. It can achieve the optimal quality of the control system and adapt to the network load changes.
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