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Access Point Design with a Genetic Algorithm

机译:具有遗传算法的接入点设计

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摘要

The interest in deploying local wireless networks has increased in the corporate environment, in recent years, as a result of several improvements in their features. Nevertheless, there are some problems caused by inadequate positions of access points (APs) which overload some cells of the total area to be covered. Some strategies of AP positioning aim only at covering the environment. Some aspects, such as, the number of users per AP and reducing the distance from the users to an AP, could be objective function parameters in the network optimization problem. This article presents a novel model to AP design, where the area covered and the users connected are maximized, and the number of APs is minimized. Two different algorithms to deal with the AP design are presented, the greedy search heuristic and a genetic algorithm. Three experimental studies with different areas to be covered were conducted. in all of them, both algorithms reached their targets, i.e., all the grid area was covered and all users were served.
机译:在近年来,在企业环境中,部署本地无线网络的兴趣增加,由于其特征的几种改进,近年来。然而,由于接入点(APS)的位置不足而导致的一些问题,这使得待覆盖的总面积的一些细胞。 AP定位的一些策略仅涉及环境。一些方面,例如,每个AP的用户数量并将与用户到AP的距离减少,这可能是网络优化问题中的客观函数参数。本文介绍了一个新模型到AP设计,其中覆盖的区域和连接的用户最大化,并且最小化AP的数量。提供了两种不同的算法来处理AP设计,贪婪的搜索启发式和遗传算法。进行了三种与覆盖区域的实验研究。在所有这些中,这两种算法都达到了目标,即,所有网格区域都被覆盖,所有用户都被送达。

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