论文标题
移动性驱动的云 - 模具 - 地点感知服务的框架:全面评论
Mobility driven Cloud-Fog-Edge Framework for Location-aware Services: A Comprehensive Review
论文作者
论文摘要
随着物联网设备,智能手机和位置跟踪技术的改进的普遍性,生成了大量的异质地理标签(位置特定)数据,从而促进了几种位置感知的服务。使用此时空时期(具有位置和时间维度)数据集的分析提供了各种重要服务,例如智能运输,紧急服务(医疗保健,国防或城市规划)。虽然云范式适合存储和计算的能力,但主要的瓶颈是网络连通性损失。在紧急服务提供实时响应的时间至关重要的应用中,此类连接问题会增加延迟,从而影响系统的整体质量(QOS)。为了克服该问题,已经出现了雾/边缘拓扑,在网络边缘进行部分计算以减少通信延迟。这种基于雾/边缘的系统可以补充云技术并扩展系统的功能。本章讨论了基于云 - 模具 - 边缘的层次协作框架,其中部署了几个组件以改善QoS。在另一边。移动性是增强此类位置感知服务提供功效的另一个关键因素。因此,本章讨论了与基于移动性驱动的云障碍框架相关的担忧和挑战,以有效地为最终用户提供多种位置感知服务。
With the pervasiveness of IoT devices, smart-phones and improvement of location-tracking technologies huge volume of heterogeneous geo-tagged (location specific) data is generated which facilitates several location-aware services. The analytics with this spatio-temporal (having location and time dimensions) datasets provide varied important services such as, smart transportation, emergency services (health-care, national defence or urban planning). While cloud paradigm is suitable for the capability of storage and computation, the major bottleneck is network connectivity loss. In time-critical application, where real-time response is required for emergency service-provisioning, such connectivity issues increases the latency and thus affects the overall quality of system (QoS). To overcome the issue, fog/ edge topology has emerged, where partial computation is carried out in the edge of the network to reduce the delay in communication. Such fog/ edge based system complements the cloud technology and extends the features of the system. This chapter discusses cloud-fog-edge based hierarchical collaborative framework, where several components are deployed to improve the QoS. On the other side. mobility is another critical factor to enhance the efficacy of such location-aware service provisioning. Therefore, this chapter discusses the concerns and challenges associated with mobility-driven cloud-fog-edge based framework to provide several location-aware services to the end-users efficiently.