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Optimal Modeling of Wireless LANs: A Decision-Making Multiobjective Approach

机译:无线局域网的最佳建模:一种决策多目标方法

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Communication infrastructure planning is a critical design task that typically requires handling complex concepts on networking aimed at optimizing performance and resources, thus demanding high analytical and problem-solving skills to engineers. To reduce this gap, this paper describes an optimization algorithm—based on evolutionary strategy—created as an aid for decision-making prior to the real deployment of wireless LANs. The developed algorithm allows automating the design process, traditionally handmade by network technicians, in order to save time and cost by improving the WLAN arrangement. To this end, we implemented a multiobjective genetic algorithm (MOGA) with the purpose of meeting two simultaneous design objectives, namely, to minimize the number of APs while maximizing the coverage signal over a whole planning area. Such approach provides efficient and scalable solutions closer to the best network design, so that we integrated the developed algorithm into an engineering tool with the goal of modelling the behavior of WLANs in ICT infrastructures. Called WiFiSim, it allows the investigation of various complex issues concerning the design of IEEE 802.11-based WLANs, thereby facilitating design of the study and design and optimal deployment of wireless LANs through complete modelling software. As a result, we comparatively evaluated three target applications considering small, medium, and large scenarios with a previous approach developed, a monoobjective genetic algorithm.
机译:通信基础架构规划是一项关键的设计任务,通常需要处理网络上的复杂概念,以优化性能和资源,从而要求工程师具备较高的分析和解决问题的技能。为了缩小这种差距,本文介绍了一种基于进化策略的优化算法,该算法是在实际部署无线LAN之前为决策制定提供帮助的。所开发的算法允许自动化设计过程(通常由网络技术人员手工完成),以通过改进WLAN安排节省时间和成本。为此,我们实现了一个多目标遗传算法(MOGA),目的是满足两个同时的设计目标,即最小化AP的数量,同时在整个规划区域内最大化覆盖信号。这种方法提供了更有效的,可扩展的解决方案,更接近最佳网络设计,因此我们将开发的算法集成到了工程工具中,目的是对ICT基础设施中WLAN的行为进行建模。称为WiFiSim,它允许研究与基于IEEE 802.11的WLAN设计有关的各种复杂问题,从而通过完整的建模软件来简化研究设计和无线局域网的最佳部署。结果,我们使用先前开发的单目标遗传算法比较了考虑小,中和大场景的三个目标应用程序。

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