RCPFH:在软件定义网络中使用模糊系统和改进的海象优化算法的可靠控制器布局

IF 3.5 2区 计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Maryam Shamsoddini, Ali Ghaffari, Masoud Kargar, Nahideh Derakhshanfard
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引用次数: 0

摘要

软件定义网络(SDN)是一种新颖的网络架构,它将控制平面和数据平面分离开来,实现对网络资源的集中和可编程管理。SDN的关键挑战之一是确定控制器的最佳数量和位置,称为控制器放置问题(CPP),以确保均衡的负载分配,最小的延迟和高网络可靠性。本文介绍了一种使用模糊逻辑和元启发式算法(RCPFH)的新型三相方法,称为可靠控制器放置,该方法有效地优化了SDN环境中的控制器放置。在第一阶段,该方法采用以Levy Flight参数为指导的模糊逻辑系统,通过评估整个网络的能耗、拥塞水平和负载变化等关键因素来估计控制器的最优数量。第二阶段采用改进的海象优化算法,考虑路径可靠性、处理能力和传播延迟,确定最合适的控制器位置。最后,在第三阶段,选择备用控制器,以提高系统在控制器失效时的可靠性。使用来自ZOO Topology数据集的四种真实网络拓扑来评估所提出的RCPFH框架。与最先进的方法进行的比较实验显示了显著的性能改进:能耗减少38%,负载变化减少11%,网络可用性增加36%,平均延迟减少17%,链路故障率减少15%。这些结果验证了RCPFH在优化SDN性能的同时保持鲁棒性和运行效率的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
RCPFH: Reliable controller placement in software-defined networks using fuzzy systems and a modified walrus optimization algorithm
Software-Defined Networking (SDN) is a novel network architecture that separates the control plane from the data plane, enabling centralized and programmable management of network resources. One of the key challenges in SDN is determining the optimal number and locations of controllers, called the Controller Placement Problem (CPP), to ensure balanced load distribution, minimal latency, and high network reliability. This paper introduces a novel three-phase approach called Reliable Controller Placement using Fuzzy Logic and Metaheuristic Algorithms (RCPFH), which efficiently optimizes controller placement in SDN environments. In the first phase, the approach employs a fuzzy logic system guided by Levy Flight parameters to estimate the optimal number of controllers by evaluating critical factors such as energy consumption, congestion levels, and load variance across the network. The second phase utilizes a Modified Walrus Optimization Algorithm to identify the most suitable controller positions, considering path reliability, processing capacity, and propagation delay. Finally, in the third phase, backup controllers are selected to enhance system reliability in the event of controller failure. The proposed RCPFH framework is evaluated using four real-world network topologies from the ZOO Topology dataset. Comparative experiments with state-of-the-art approaches demonstrate significant performance improvements: up to a 38 % reduction in energy consumption, an 11 % decrease in load variance, a 36 % increase in network availability, a 17 % reduction in average latency, and a 15 % decrease in link failure rate. These results validate the effectiveness of RCPFH in optimizing SDN performance while maintaining robustness and operational efficiency.
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来源期刊
Simulation Modelling Practice and Theory
Simulation Modelling Practice and Theory 工程技术-计算机:跨学科应用
CiteScore
9.80
自引率
4.80%
发文量
142
审稿时长
21 days
期刊介绍: The journal Simulation Modelling Practice and Theory provides a forum for original, high-quality papers dealing with any aspect of systems simulation and modelling. The journal aims at being a reference and a powerful tool to all those professionally active and/or interested in the methods and applications of simulation. Submitted papers will be peer reviewed and must significantly contribute to modelling and simulation in general or use modelling and simulation in application areas. Paper submission is solicited on: • theoretical aspects of modelling and simulation including formal modelling, model-checking, random number generators, sensitivity analysis, variance reduction techniques, experimental design, meta-modelling, methods and algorithms for validation and verification, selection and comparison procedures etc.; • methodology and application of modelling and simulation in any area, including computer systems, networks, real-time and embedded systems, mobile and intelligent agents, manufacturing and transportation systems, management, engineering, biomedical engineering, economics, ecology and environment, education, transaction handling, etc.; • simulation languages and environments including those, specific to distributed computing, grid computing, high performance computers or computer networks, etc.; • distributed and real-time simulation, simulation interoperability; • tools for high performance computing simulation, including dedicated architectures and parallel computing.
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