Research on Load Balancing of Distributed Control Plane in Polymorphic Network

TU Hua-qing; LIU Shuo; FANG Xu-xin; MA Bo; LI Chuan-huang; ZHU Jun; ZOU Tao

doi:10.12263/DZXB.20250421

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Research on Load Balancing of Distributed Control Plane in Polymorphic Network

PAPERS | 更新时间：2026-02-10

- Research on Load Balancing of Distributed Control Plane in Polymorphic Network
- ACTA ELECTRONICA SINICA Vol. 53, Issue 11, Pages: 3996-4009(2025)
- 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：
- 基金信息：
  
  National Natural Science Foundation of China(U22A2005);Zhejiang Provincial Key Research and Development Program(2024SSYS0001)
- DOI：10.12263/DZXB.20250421
  CLC： TP393;
- Received：26 May 2025，
  
  Accepted：03 November 2025，
  
  Published：25 November 2025
- 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

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