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    题名: An integrated optimization model for wireless access point deployment construction, and enhancement
    作者: 林湘霖
    Wang, C.-S.
    Lin, Shiang-Lin
    贡献者: 資管系
    关键词: Artificial intelligence;Budget control;Genetic algorithms;Interference suppression;Linear programming;Multiobjective optimization;Optimization;Signal interference;Software engineering;Tabu search;Wireless telecommunication systems;Access points;Dynamic throughputs;Integrated optimization models;Networking infrastructure;Tabu search algorithms;Wireless access points;Wireless communications;Wireless lans;C (programming language)
    日期: 2015-08
    上传时间: 2017-08-09 17:28:39 (UTC+8)
    摘要: Appropriate wireless LAN design is essential for ensuring a good quality of telecommunication service. Optimal access point deployment (APD) presents a typical NP-complex problem that resolves wireless networking infrastructure with the involvement of multiple objectives (MO-APD). MO-APD can be divided into the APD construction (APD-C) problem and the APD enhancement (APD-E) problem. For APD-E problem resolving, the present APD must be taken into consideration for subsequent extensions. This paper proposes a goal-programming-driven model (GM) integrated with a genetic algorithm and an embedded mask mechanism to optimally resolve both the MO-APD-C and MO-APD-E problems in the same model. The GM formulates the target deployment subject to four constraints: budget, coverage rate, capacity requirement and signal interference. In addition, to replicate real wireless communication, the GM addresses the dynamic capacity requirement of the user. Two experiments are designed to validate the feasibility of the GM and compare the experiment results with the Tabu search algorithm. The experimental results of experiment 1 demonstrate that GM can increase 5% networking capacity and decrease 10% interference rate by using less APs and therefore lowering cost. The experimental results of experiment 2 further validate the usefulness of the proposed method to resolve both the APD-C and APD-E problems steadily. © 2015 IEEE.
    關聯: 2015 IEEE/ACIS 16th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2015 - Proceedings
    数据类型: conference
    DOI 連結: http://dx.doi.org/10.1109/SNPD.2015.7176223
    DOI: 10.1109/SNPD.2015.7176223
    显示于类别:[資訊管理學系] 會議論文

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