面向多约束QoS路由的启发式算法设计与性能分析

Design and Performance Analysis of Heuristic Algor-ithms for Multi-constrained QoS Routing

摘要:

移动自组织网络(MANET)中的服务质量(QoS)路由是保障现代网络应用性能的关键技术。本文针对具有带宽、时延和丢包率多重约束的QoS路由优化问题展开研究。在构建网络模型的基础上,本文分别设计了基于遗传算法(GA)和蚁群算法(ACO)的两种智能求解方案,详细阐述了其求解流程与关键设计。通过在不同网络规模下的仿真实验对比分析,结果表明两种算法均能有效求解该NP问题,但蚁群算法凭借其启发式信息引导与信息素正反馈机制,在收敛速度与路径带宽、时延性能上均优于遗传算法。本研究为MANET中复杂QoS路由问题提供了有效的解决方案与算法选型依据。

Abstract:

Quality of Service (QoS) routing in Mobile Ad hoc Networks (MANET) is a key technology for ensuring the performance of modern network applications. This paper focuses on the QoS routing optimization problem with multiple constraints, including band-width, delay, and packet loss rate. Based on the construction of a network model, two in-telligent solution schemes are designed using Genetic Algorithm (GA) and Ant Colony O-ptimization (ACO), with detailed explanations of their solution processes and key design e-lements. Through comparative analysis of simulation experiments conducted under differe-nt network scales, the results show that both algorithms can effectively solve this NP-hard problem. However, the Ant Colony Optimization algorithm outperforms the Genetic Algo-rithm in terms of convergence speed, as well as path bandwidth and delay performance, due to its heuristic information guidance and pheromone positive feedback mechanism. Th-is study provides an effective solution and a basis for algorithm selection in addressing c-omplex QoS routing problems in MANETs.