欢迎您访问《智慧农业(中英文)》官方网站! English

Smart Agriculture ›› 2020, Vol. 2 ›› Issue (3): 98-107.doi: 10.12133/j.smartag.2020.2.3.202007-SA001

• 专题--农业人工智能与大数据 • 上一篇    下一篇

基于粒子群与模拟退火协同优化的农田物联网混合多跳路由算法

孙浩然1(), 孙琳1, 毕春光1,2, 于合龙1,2()   

  1. 1.吉林农业大学 信息技术学院,吉林 长春 130118
    2.吉林农业大学 智慧农业研究院,吉林 长春 130118
  • 收稿日期:2020-07-01 修回日期:2020-09-22 出版日期:2020-09-30
  • 基金资助:
    国家重点研发计划项目(2019YFC1710700);吉林省科技发展计划项目(20190301024NY)
  • 作者简介:孙浩然(1995-),男,硕士,研究方向为智慧农业。E-mail:sunhaoran@nercita.org.cn
  • 通信作者: 于合龙(1974-),男,博士,教授,研究方向为精准农业与农业大数据。电话:13500828956。E-mail:yuhelong@aliyun.com。

Hybrid Multi-Hop Routing Algorithm for Farmland IoT based on Particle Swarm and Simulated Annealing Collaborative Optimization Method

SUN Haoran1(), SUN Lin1, BI Chunguang1,2, YU Helong1,2()   

  1. 1.College of Information Technology, Jilin Agricultural University, Changchun 130118, China
    2.Institute of Smart Agriculture, Jilin Agricultural University, Changchun 130118, China
  • Received:2020-07-01 Revised:2020-09-22 Online:2020-09-30
  • corresponding author: YU Helong, 
  • About author:SUN Haoran, E-mail:sunhaoran@nercita.org.cn
  • Supported by:
    National Key Research and Development Program of China (2019YFC1710700); Jilin Province Science and Technology Development Program Project (20190301024NY)

摘要:

农业无线传感器网络对农田土壤、环境和作物生长的多源异构信息的获取起关键作用。针对传感器在农田中非均匀分布且受到能量制约等问题,本研究提出了一种基于粒子群和模拟退火协同优化的农田物联网混合多跳路由算法(PSMR)。首先,通过节点剩余能量和节点度加权选择簇首,采用成簇结构实现异构网络高效动态组网。然后通过簇首间多跳数据结构解决簇首远距离传输能耗过高问题,利用粒子群与模拟退火协同优化方法提高算法收敛速度,实现sink节点加速采集簇首中的聚合数据。对算法的仿真试验结果表明,PSMR算法与基于能量有效负载均衡的多路径路由策略方法(EMR)相比,无线传感器网络生命周期提升了57%;与贪婪外围无状态路由算法(GPSR-A)相比,在相同的网络生命周期内,第1个死亡传感器节点推迟了两轮,剩余能量标准差减少了0.04 J,具有良好的网络能耗均衡性。本研究提出的PSMR算法通过簇首间多跳降低远端簇首额外能耗,提高了不同距离簇首的能耗均衡性能,为实现大规模农田复杂环境的长时间、高效、稳定地数据采集监测提供了技术基础,可提高农业物联网的资源利用效率。

关键词: 大规模农田, 粒子群优化, 模拟退火, 无线传感器网络, 路由优化, 混合型网络结构, 数据传输链路, 物联网

Abstract:

Agricultural wireless sensor networks plays a key role in obtaining multi-source heterogeneous big data of farmland soil, environment and crop growth. The increasing network scale brings challenges to the application of agricultural Internet of Things. In order to solve the problem that sensors are not uniformly distributed in farmland and constrained by energy, a collaborative optimization hybrid multi hop routing algorithm, particle simulated multipath routing (PSMR) based on particle swarm optimization and simulated annealing was proposed. Firstly, cluster heads were selected by node residual energy and node degree weighting, and cluster structure was used to realize efficient dynamic networking of heterogeneous networks. Then, the multi hop data structure between cluster heads was used to solve the problem of high energy consumption in long-distance transmission of cluster heads. Particle swarm optimization and simulated annealing were used to improve the convergence speed, and sink nodes could accelerate the collection of aggregated data in cluster heads. The simulation results showed that compared with the energy-efficient load balancing multipath routing scheme (EMR), the network lifetime of PSMR algorithm was increased by 57%. EMR selected the data transmission link with low energy consumption and small delay by calculating the weight of total link hops and transmission energy consumption. Compared with greedy perimeter stateless routing-algorithm (GPSR-A algorithm), which could ensure the shortest data transmission distance and lower network transmission delay, the first dead sensor node was delayed for two rounds in the same network life cycle, and the residual energy standard deviation was reduced by 0.04 J, which had good network energy consumption balance. PSMR algorithm could reduce the extra energy consumption of remote cluster heads by multi hop between cluster heads, and improved the energy balance performance of cluster heads with different distances. It can provide technical basis for long-term, efficient and stable data acquisition and monitoring of large-scale farmland complex environment, and improve the resource utilization efficiency of agricultural Internet of Things.

Key words: large-scale farmland, particle swarm optimization, simulated annealing, wireless sensor networks, routing optimization, hybrid network architecture, data transmission link, Internet of Things

中图分类号: