多模态网络分布式控制平面负载均衡研究
Research on Load Balancing of Distributed Control Plane in Polymorphic Network
- 电子学报 2025年53卷第11期 页码：3996-4009
- 作者机构：
1.浙江工商大学，浙江杭州 310018
2.之江实验室，浙江杭州 311100
- 作者简介：
[ "凃化清 女，1995年4月出生于重庆市.现为浙江工商大学助理研究员.主要研究方向为软件定义网络、可编程数据平面、多模态网络等.E-mail: thq@mail.zjgs.edu.cn" ]
[ "刘 硕 男，2001年8月出生于山西省晋中市.现为浙江工商大学信息与电子工程学院硕士研究生.主要研究方向为算力网络、多模态网络.E-mail: 254754614@qq.com" ]
[ "方徐鑫 男，1999年12月出生于浙江省绍兴市.现为浙江工商大学信息与电子工程学院硕士研究生.主要研究方向为多模态网络、可编程网络.E-mail: 22020090054@pop.zjgsu.edu.cn" ]
[ "马 博 男，1991年9月出生于宁夏回族自治区银川市.现为浙江工商大学信息与电子工程学院副教授、硕士生导师.主要研究方向为异构网优化、无人机通信、5G网络中的机器学习算法.E-mail: mabo@mail.zjgsu.edu.cn" ]
[ "李传煌 男，1980年8月出生于江西省九江市.现为浙江工商大学信息与电子工程学院教授、硕士生导师.主要研究方向为新一代网络技术、算力网络、人工智能应用.中国电子学会会员编号：E190024269M.E-mail: chuanhuang_li@zjgsu.edu.cn" ]
[ "朱 俊 男，1981年8月出生于浙江省嘉兴市.现为之江实验室工程专家、高级工程师.主要研究方向为新型网络体系结构、软件定义网络、网络资源管理、网络协议设计优化等.E-mail: zhu_j@zhejianglab.org" ]
[ "邹 涛 男，1974年11月出生于重庆市.现为之江实验室研究专家、研究员.主要研究方向为多模态网络技术和新型网络体系架构.E-mail: zout@zhejianglab.org" ]
- 基金信息：国家自然科学基金(U22A2005);浙江省重点研发计划(2024SSYS0001)
DOI：10.12263/DZXB.20250421
中图分类号： TP393;收稿：2025-05-26，
录用：2025-11-03，
纸质出版：2025-11-25
- 稿件说明：
移动端阅览
凃化清, 刘硕, 方徐鑫, 等. 多模态网络分布式控制平面负载均衡研究[J]. 电子学报, 2025, 53(11): 3996-4009.
TU Hua-qing, LIU Shuo, FANG Xu-xin, et al. Research on Load Balancing of Distributed Control Plane in Polymorphic Network[J]. Acta Electronica Sinica, 2025, 53(11): 3996-4009.
凃化清, 刘硕, 方徐鑫, 等. 多模态网络分布式控制平面负载均衡研究[J]. 电子学报, 2025, 53(11): 3996-4009. DOI：10.12263/DZXB.20250421
TU Hua-qing, LIU Shuo, FANG Xu-xin, et al. Research on Load Balancing of Distributed Control Plane in Polymorphic Network[J]. Acta Electronica Sinica, 2025, 53(11): 3996-4009. DOI：10.12263/DZXB.20250421
摘要
随着工业互联网、车联网、远程医疗等新型服务的快速发展，多模态网络应运而生.该架构基于“技术体制与网络环境分离”的设计思想，使多种网络模态能够在同一基础平台上共生共存.然而，现有研究多集中于多模态网络的环境构建、编译优化与网元设计，缺乏对分布式控制平面负载均衡的系统研究.部分借鉴SDN（Software-Defined Networking）的交换机迁移与动态重分配机制虽可缓解控制器过载，但需在控制器间频繁同步状态信息，迁移开销大、响应延迟高，难以满足多模态网络的实时性与可扩展性要求.针对上述问题，本文通过对数据平面流量路由的合理规划，优化多模态网络中控制平面的负载分布，提出一种对多种网络模态的流量路由与多模态网元-控制器分配进行联合优化（Joint optimization of Routing and polymorphic network Element Controller Allocation，JRECA）方法.该方法将不同模态的控制信息规模差异显式纳入优化框架，综合考虑网元分配、路由选择、控制器处理能力与链路带宽等约束.对于多模态网络的异构特性，本文提出将不同模态控制信息规模差异纳入控制器负载约束的负载均衡机制，构建了同时实现控制平面负载均衡与数据平面吞吐量最大化的统一模型，实现控制平面负载与数据平面吞吐的协同优化，弥补既有研究中两平面割裂求解的不足，并进一步设计具有严格理论保证的“两步走”算法框架.首先，设计基于最大负载优先的多模态网元-控制器分配算法，确定多模态网元与控制器之间的匹配关系，并通过近似比证明严格界定了算法性能边界；然后，在动态流量环境下，设计基于原始-对偶方法的在线路由算法，并通过竞争比分析给出在线优化的理论性能下界.在Fat-Tree和ARPANet两种典型拓扑上的仿真实验表明，本文提出的算法在IPv4、IPv6、工控标识、命名数据标识和身份标识5种网络模态下均取得显著性能提升.与对比算法相比，本文提出的算法可降低17.56%～20.97%的控制器负载，并提高13.86%～29.82%的系统吞吐量.
Abstract
With the rapid development of emerging services such as the Industrial Internet
Internet of Vehicles
and telemedicine
multimodal networks have emerged. This architecture is based on the design principle of “separating technical systems from network environments”
allowing multiple network modalities to coexist on a unified infrastructure platform. However
existing studies mostly focus on the construction of multimodal network environments
compilation optimization
and network element design
while lacking systematic research on load balancing in the distributed control plane. Some approaches inspired by the switch migration and dynamic reallocation mechanisms of software-defined networking (SDN) can alleviate controller overload to some extent
but they require frequent synchronization of state information among controllers. This leads to high migration overhead and response delays
making it difficult to meet the real-time and scalability requirements of multimodal networks.To address these challenges
this paper proposes a method called joint optimization of routing and polymorphic network element controller allocation (JRECA)
which optimizes the control plane load distribution in multimodal networks by rationally planning data-plane traffic routing. The method explicitly incorporates the differences in control information scales among different modalities into the optimization framework
comprehensively considering constraints such as network element allocation
routing selection
controller processing capacity
and link bandwidth. Considering the heterogeneous nature of multimodal networks
this paper introduces a load-balancing mechanism that accounts for the differences in control information scale among modalities within the controller load constraints. It constructs a unified model that simultaneously achieves control-plane load balancing and data-plane throughput maximization
thereby realizing coordinated optimization between the control plane load and data-plane throughput—addressing the shortcomings of decoupled optimization in prior research. Furthermore
a theoretically grounded two-step algorithm framework is designed: First
a multimodal network element-controller allocation algorithm based on maximum-load priority is developed to determine the matching relationships between network elements and controllers
with a proven approximation ratio that strictly bounds algorithmic performance. Then
under dynamic traffic conditions
an online routing algorithm based on the primal-dual method is designed
with competitive ratio analysis providing a theoretical lower bound on online optimization performance. Simulation experiments on two representative topologies—Fat-Tree and ARPANet—demonstrate that the proposed algorithm achieves significant performance improvements across five network modalities: IPv4
IPv6
industrial control identifiers
named data identifiers
and identity identifiers. Compared with benchmark algorithms
the proposed method reduces controller load by 17.56%～20.97% and increases system throughput by 13.86%～29.82%.
关键词
Keywords
references
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