计算机科学

计算机科学 ›› 2025, Vol. 52 ›› Issue (8): 343-353.doi: 10.11896/jsjkx.240900174

• 计算机网络 • 上一篇    下一篇

基于SDN的通存一体化边缘在网存储节点选择方法

叶苗1, 王珏1, 蒋秋香2, 王勇3   

  1. 1 桂林电子科技大学信息与通信学院 广西 桂林 541004
    2 桂林电子科技大学光电工程学院 广西 桂林 541004
    3 桂林电子科技大学计算机与信息安全学院 广西 桂林 541004
  • 收稿日期:2024-09-30 修回日期:2024-12-14 出版日期:2025-08-15 发布日期:2025-08-08
  • 通讯作者: 蒋秋香(jiangqiuxiang@guet.edu.cn)
  • 作者简介:(yemiao@guet.edu.cn)
  • 基金资助:
    国家自然科学基金(62161006,62172095);广西研究生教育创新计划(YCSW2023310);“认知无线电与信息处理”教育部重点实验室主任基金项目(CRKL220103);广西无线宽带通信与信号处理重点实验室主任基金项目(GXKL06220110)

SDN-based Integrated Communication and Storage Edge In-network Storage Node Selection Method

YE Miao1, WANG Jue1, JIANG Qiuxiang2, WANG Yong3   

  1. 1 School of Information and Communications,Guilin University of Electronic Technology,Guilin,Guangxi 541004,China
    2 School of Optoelectronic Engineering,Guilin University of Electronic Technology,Guilin,Guangxi 541004,China
    3 School of Computer Science and Information Security,Guilin University of Electronic Technology,Guilin,Guangxi 541004,China
  • Received:2024-09-30 Revised:2024-12-14 Online:2025-08-15 Published:2025-08-08
  • About author:YE Miao,born in 1977,Ph.D,professor,doctoral supervisor.His main research interests include edge storage,cloud storage,software-defined networking,wireless sensor networks,pattern recognition,machine learning,deep reinforcement learning and graph neural network.
    JIANG Qiuxiang,born in 1978,engineer.Her main research interests include wireless sensor networks,pattern recognition,machine learning and graph neural networks.
  • Supported by:
    National Natural Science Foundation of China(62161006,62172095),Subsidization of Innovation Project of Guangxi Graduate Education(YCSW2023310),Ministry of Education of Key Laboratory of Cognitive Radio and Information Processing(Guilin University of Electronic Technology)(CRKL220103) and Guangxi Key Laboratory of Wireless Wideband Communication and Signal Processing(GXKL06220110).

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摘要： 通常的边缘分布式存储系统将数据存储在多个边缘端服务器上,不仅传输时延受限于数据到边缘服务器的距离,而且服务器节点之间的网络通信管理和配置不够灵活,数据通过网络传输完成边缘存储受到带宽、吞吐量和网络故障等因素的影响,并且在考虑数据存储位置时只考虑存储节点容量,忽略了边缘网络负载和存储节点负载的因素给数据存储效率带来的影响。为解决这些问题,设计了一种通存一体化边缘在网存储架构。该架构融合了软件定义网络(SDN)的灵活性与服务消息块协议(SMB)的高效性,将边缘网络产生的数据存储在部分网络转发节点,并通过开发定制边缘通存一体化网络交换机实现了所设计的原型系统。首先,利用开发定制一种耦合存储功能的SDN交换机作为具备在网存储功能的存储节点,将数据存储到这些网络转发节点上,以有效减少数据传输的网络延迟;然后,通过使用SDN技术实时获取网络状态信息和存储节点自身信息,不仅实现了网络传输的动态优化,解决了网络配置管理繁琐的问题,还能以此为基础,建立一种数据存储节点选择的多属性决策模型和设计相应的层次分析求解算法,综合考虑网络状态和节点状态来完成数据在网存储位置的选择;最后,通过系列实验表明,与现有边缘分布式存储系统的数据存储方法相比,所设计和实现的通存一体化边缘在网存储系统能够更灵活地进行网络管理和配置,显著地降低数据存储的时延。

关键词: 分布式存储, 在网存储, 软件定义网络, 无线通信, 节点选择

Abstract: In conventional edge-distributed storage systems,data is stored across multiple edge servers,where transmission latency is constrained by the distance to the edge servers,and network communication management and configuration between server nodes lack flexibility.Data transfer for edge storage is affected by factors such as bandwidth,throughput,and network failures.Moreover,traditional systems often consider only storage node capacity when selecting storage locations,overlooking the impact of edge network load and storage node load on data storage efficiency.To address these issues,this paper designs a converged edge in-network storage architecture,integrating the flexibility of Software-Defined Networking(SDN) with the efficiency of the Server Message Block(SMB) protocol.The architecture stores data generated within the edge network on certain network forwarding nodes,and the prototype system is implemented through a custom-developed edge-converged network switch.Firstly,a custom SDN switch,coupled with storage functionality,is developed to serve as an in-network storage node,allowing data to be stored on these network forwarding nodes to effectively reduce data transmission latency.Then,using SDN technology to acquire real-time network status and storage node information,dynamic optimization of network transmission is achieved,alleviating the complexity of network configuration and management.Based on this data,a multi-attribute decision-making model for data storage node selection is established,along with a hierarchical analytical algorithm that considers both network and node states for in-network storage placement.Finally,experimental results demonstrate that,compared to conventional data storage methods in edge-distributed storage systems,the designed and implemented converged edge in-network storage system offers more flexible network management and configuration,significantly reducing data storage latency.

Key words: Distributed storage, In-network storage, SDN, Wireless communication, Node selection

中图分类号: 

  • TP393
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