The Bandwidth Allocation Algorithm for Mixed-criticality Traffic in Industrial Wireless Sensor Networks

WANG Jun; WANG Qiu-shi; WANG Jin-tao

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The Bandwidth Allocation Algorithm for Mixed-criticality Traffic in Industrial Wireless Sensor Networks

更新时间：2026-09-04

- The Bandwidth Allocation Algorithm for Mixed-criticality Traffic in Industrial Wireless Sensor Networks
- Vol. 35, Issue 4, Pages: 22-25(2018)
- 作者机构：
  
  1. 中国石油化工股份有限公司天津石化分公司,天津,300271
  2. 中国科学院机构沈阳自动化研究所工业控制网络与系统研究室,辽宁,沈阳,110016
  3. 中国科学院大学机构,北京,101408
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2018
- 稿件说明：
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王军, 王秋石, 王金涛. 工业无线传感网混合关键性业务带宽分配算法[J]. 微电子学与计算机, 2018, 35(4): 22-25, 31.

WANG Jun, WANG Qiu-shi, WANG Jin-tao. The Bandwidth Allocation Algorithm for Mixed-criticality Traffic in Industrial Wireless Sensor Networks[J]. 2018, 35(4): 22-25.
王军, 王秋石, 王金涛. 工业无线传感网混合关键性业务带宽分配算法[J]. 微电子学与计算机, 2018, 35(4): 22-25, 31. DOI：

WANG Jun, WANG Qiu-shi, WANG Jin-tao. The Bandwidth Allocation Algorithm for Mixed-criticality Traffic in Industrial Wireless Sensor Networks[J]. 2018, 35(4): 22-25. DOI：

摘要

在工业无线传感网中

对业务传输的实时性和可靠性都有较高的要求.本文基于广义的最大-最小效用公平准则

通过线性分段函数对计算过程进行简化

提出基于线性分段函数的一种带宽分配方法.该方法基于集中式控制的结构

既保障高关键性业务的及时传输

又不会对高实时性低带宽需求的业务造成影响.通过部署在天津石化的无线数据采集网络对算法性能进行测试

验证了算法的有效性和可行性.

Abstract

In industrial wireless sensor networks

it has higher requirements in real-time and reliability. based on the generalized UMM fair principles

using the ideas of piecewise linear function to simplify the calculation

we presents a resource allocation algorithm based on piecewise linear function. The method is based on the structure of centralized control

and can ensure timely transfer of the high time critical traffic

but not affect the traffic with high real-time and low bandwidth requirements. Finally

through the wireless data acquisition network deployed in Tianjin Chemical Corporation

we test the performance of algorithm.

关键词

Keywords

references

Gaj Piotr, Jurgen Jasperneite, Max Felser. Computer communication within industrial distributed environment: A survey[J]. IEEE Transactions on Industrial Informatics, 2013, 9(1): 182-189. DOI: 182

Feamster, Nick, Jennifer Rexford, Ellen Zegura. The road to SDN: an intellectual history of programmable networks[J]. ACM SIGCOMM Computer Communication Review, 2014, 44(2): 87-98. DOI: 87

基于萤火虫算法的无线传感器网络移动sink节点路径规划方法[J]微电子学与计算机, 2016, 33(5): 47-51.

Kohli, Nidhi, Jeffrey R. Harring. Modeling growth in latent variables using a piecewise function[J]. Multivariate behavioral research, 2013, 48(3): 370-397. DOI: 370

Hwang, Renhung, Huiping Tseng. Load balancing and routing mechanism based on software defined network in data centers[C]//2016 IEEE International Computer Symposium (ICS). Coogee Beach, Sydney, Australia, 2016: 165-170.

Georgia Giannopoulou, Nikolay Stoimenov, Pengcheng Huang, et al. Mixed-criticality scheduling on cluster-based manycores with shared communication and storage resources[J]. Real-Time Systems, 2016, 52(4): 399-449. DOI: 399

Shenker Scott. Fundamental design issues for the future Internet[J]. IEEE Journal on selected areas in communications, 1995, 13(7): 1176-1188. DOI: 1176

谷传才, 关楠, 于金铭, 等. 多处理器混合关键性系统中的划分调度策略[J]. 软件学报, 2014, 25(2): 284-297. DOI: 284

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Related Institution

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