物联网异构融合数据延迟保护传输策略

徐九韵; 孙姗

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物联网异构融合数据延迟保护传输策略

更新时间：2026-09-04

- 物联网异构融合数据延迟保护传输策略
- Delay-guaranteed transmission strategy for heterogeneous fusion data in the internet of things
- 微电子学与计算机 2021年38卷第7期页码：42-47
- 作者机构：
  
  1. 中国石油大学(华东) 计算机科学与技术学院,山东,青岛,266580
  2. 中国石油大学(华东) 海洋与空间信息学院,山东,青岛,266580
- 作者简介：
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- 纸质出版：2021
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徐九韵, 孙姗. 物联网异构融合数据延迟保护传输策略[J]. 微电子学与计算机, 2021, 38(7): 42-47.

XU Jiuyun, SUN Shan. Delay-guaranteed transmission strategy for heterogeneous fusion data in the internet of things[J]. 2021, 38(7): 42-47.
徐九韵, 孙姗. 物联网异构融合数据延迟保护传输策略[J]. 微电子学与计算机, 2021, 38(7): 42-47. DOI：

XU Jiuyun, SUN Shan. Delay-guaranteed transmission strategy for heterogeneous fusion data in the internet of things[J]. 2021, 38(7): 42-47. DOI：

摘要

物联网中部署在不同监控区域的传感器传递监控数据到融合中心，所有链路试图通过不公平地获取信道访问来增加它们的传输机会.但是，单条链路的自私行为将会加剧链路之间的传输冲突，这使得对延迟敏感的实时数据吞吐量恶化，严重影响数据融合的性能.为了保障融合数据实时可靠地传输，提出了一种基于博弈论的分布式调度策略NCG-CSMA.在参与者不需要彼此进行信息交互的前提下，以分布式的方式引导每个参与者做出理性决策，为带有严格时延约束的异构融合数据提供传输服务，同时保障对数据融合价值大的数据包的传输，保障数据融合的性能.实验结果表明：提出的策略与其它现有的策略相比具有更好的实时性能.

Abstract

In the Internet of Things (IoT)

sensors deployed in different monitoring areas transmit monitoring data to the fusion center

and all links attempt to increase their transmission opportunities by unfairly acquiring channel access. However

the selfish behavior of a single link will aggravate the transmission conflicts between links

which will worsen the real-time data throughput sensitive to latency and seriously affect the performance of data fusion. In order to guarantee the real-time and reliable transmission of fusion data

this paper proposes a distributed scheduling strategy

named NCG-CSMA

based on game theory

which does not require players to interact to their own information with other competitors and guides each player to make rational decisions in a distributedway. Considering the value attribute and time characteristic of data packets

this strategy provides more transmission opportunities for packets that are urgent and of high value for data fusion

so asto guarantee the performance of data fusion. The simulation results have shown that the proposed strategy achieves good delay-guaranteed satisfaction compared with the existing strategies.

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references

YAN Z, LIU J, YANG L T, et al. Big data fusion in Internet of Things[J]. Information Fusion, 2018(40): 32-33. DOI: 10.1016/j.inffus.2017.04.005.

SHEN B, ZHOU X S, KIM M. Mixed scheduling with heterogeneous delay constraints in cyber-physical systems[J]. Future Generation Computer Systems, 2016(61): 108-117. DOI: 10.1016/j.future.2015.10.021.

IEEE/ACM transactions on networking[J]. IEEE/ACM Transactions on Networking, 2010, 18(5): C1-C4. DOI: 10.1109/TNET.2010.2086813.

BARDE A, JAIN S. A survey of multi-sensor data fusion in wireless sensor networks[C]//Proceedings of the 3rd International Conference on Internet of Things and Connected Technologies. [s. l. ]. 2018. DOI: 10.2139/ssrn.3167286.

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XU J Y, LIU S, LU X X, et al. A temporal adaptive access mechanism for data fusion in an IoTenvironment[J]. Sensors, 2018, 18(12): 4205. DOI: 10.3390/S1812 4205.

RIAHI S, RIAHI A. Game theory for resource sharing in large distributed systems[J]. International Journal of Electrical and Computer Engineering, 2019, 9(2): 1249-1257. DOI: 10.11591/ijece.v9i2.pp 1249-1257.

AKKARAJITSAKUL K, HOSSAIN E, NIYATO D. Distributed resource allocation in wireless networks under uncertainty and application of Bayesian game[J]. IEEE Communications Magazine, 2011, 49(8): 120-127. DOI: 10.1109/MCOM.2011.5978425.

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