Chen Yuh-Shyan, Tsai Yi-Ting
Department of Computer Science and Information Engineering, National Taipei University, No. 151, University Rd., San Shia District, New Taipei City 23741, Taiwan.
Sensors (Basel). 2018 Feb 6;18(2):489. doi: 10.3390/s18020489.
Mobility management for supporting the location tracking and location-based service (LBS) is an important issue of smart city by providing the means for the smooth transportation of people and goods. The mobility is useful to contribute the innovation in both public and private transportation infrastructures for smart cities. With the assistance of edge/fog computing, this paper presents a fully new mobility management using the proposed follow-me cloud-cloudlet (FMCL) approach in fog-computing-based radio access networks (Fog-RANs) for smart cities. The proposed follow-me cloud-cloudlet approach is an integration strategy of follow-me cloud (FMC) and follow-me edge (FME) (or called cloudlet). A user equipment (UE) receives the data, transmitted from original cloud, into the original edge cloud before the handover operation. After the handover operation, an UE searches for a new cloud, called as a migrated cloud, and a new edge cloud, called as a migrated edge cloud near to UE, where the remaining data is migrated from the original cloud to the migrated cloud and all the remaining data are received in the new edge cloud. Existing FMC results do not have the property of the VM migration between cloudlets for the purpose of reducing the transmission latency, and existing FME results do not keep the property of the service migration between data centers for reducing the transmission latency. Our proposed FMCL approach can simultaneously keep the VM migration between cloudlets and service migration between data centers to significantly reduce the transmission latency. The new proposed mobility management using FMCL approach aims to reduce the total transmission time if some data packets are pre-scheduled and pre-stored into the cache of cloudlet if UE is switching from the previous Fog-RAN to the serving Fog-RAN. To illustrate the performance achievement, the mathematical analysis and simulation results are examined in terms of the total transmission time, the throughput, the probability of packet loss, and the number of control messages.
通过提供人员和货物顺畅运输的手段,支持位置跟踪和基于位置服务(LBS)的移动性管理是智慧城市的一个重要问题。移动性有助于推动智慧城市公共和私人交通基础设施的创新。在边缘/雾计算的辅助下,本文提出了一种全新的移动性管理方法,即在基于雾计算的无线接入网络(Fog-RAN)中,使用所提出的跟随我云-云小站(FMCL)方法来实现智慧城市的移动性管理。所提出的跟随我云-云小站方法是跟随我云(FMC)和跟随我边缘(FME)(或称为云小站)的一种集成策略。用户设备(UE)在切换操作之前,将从原始云传输来的数据接收至原始边缘云。切换操作之后,UE搜索一个新的云,称为迁移云,以及一个靠近UE的新边缘云,称为迁移边缘云,其中剩余数据从原始云迁移至迁移云,并在新边缘云中接收所有剩余数据。现有的FMC结果不具备为减少传输延迟而在云小站之间进行虚拟机迁移的特性,现有的FME结果也不具备为减少传输延迟而在数据中心之间进行服务迁移的特性。我们提出的FMCL方法可以同时保持云小站之间的虚拟机迁移和数据中心之间的服务迁移,以显著减少传输延迟。使用FMCL方法提出的新移动性管理旨在减少总传输时间,如果一些数据包被预先调度并预存储到云小站的缓存中,前提是UE从先前的Fog-RAN切换到服务中的Fog-RAN。为了说明性能成果,从总传输时间、吞吐量、丢包概率和控制消息数量等方面对数学分析和仿真结果进行了检验。