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Computational complexity closed-form upper bounds derivation for fingerprint-based Point-Of-Interest recognition algorithms
IEEE Transactions on Vehicular Technology ( IF 6.8 ) Pub Date : 2020-08-01 , DOI: 10.1109/tvt.2020.3000568 Igor Bisio , Chiara Garibotto , Fabio Lavagetto , Andrea Sciarrone
IEEE Transactions on Vehicular Technology ( IF 6.8 ) Pub Date : 2020-08-01 , DOI: 10.1109/tvt.2020.3000568 Igor Bisio , Chiara Garibotto , Fabio Lavagetto , Andrea Sciarrone
Place recognition and user positioning methods are becoming trending topics among the research community thanks to the need of providing cutting-edge solutions to enable innovative and efficient Location-Based Services (LBS) and applications. However, the mobile framework suffers from typical constraints on energy and computational capabilities due to the inherent characteristics of wireless mobile devices. For this reason, in order to be suitable for deploying in such framework, a place recognition algorithm should be thrifty in terms of resource consumption. In this paper we consider six different WiFi-based outdoor positioning approaches and we analytically derive an upper-bound for their computational burden in terms of number of FLoating-point OPerations (FLOPs).
中文翻译:
基于指纹的兴趣点识别算法的计算复杂度闭式上限推导
由于需要提供尖端解决方案以实现创新和高效的基于位置的服务 (LBS) 和应用程序,地点识别和用户定位方法正在成为研究界的热门话题。然而,由于无线移动设备的固有特性,移动框架受到能量和计算能力的典型限制。为此,为了适合部署在这样的框架中,地点识别算法在资源消耗方面应该是节俭的。在本文中,我们考虑了六种不同的基于 WiFi 的室外定位方法,并根据浮点操作 (FLOP) 的数量分析得出了它们的计算负担的上限。
更新日期:2020-08-01
中文翻译:
基于指纹的兴趣点识别算法的计算复杂度闭式上限推导
由于需要提供尖端解决方案以实现创新和高效的基于位置的服务 (LBS) 和应用程序,地点识别和用户定位方法正在成为研究界的热门话题。然而,由于无线移动设备的固有特性,移动框架受到能量和计算能力的典型限制。为此,为了适合部署在这样的框架中,地点识别算法在资源消耗方面应该是节俭的。在本文中,我们考虑了六种不同的基于 WiFi 的室外定位方法,并根据浮点操作 (FLOP) 的数量分析得出了它们的计算负担的上限。