计算机综合 | 国际会议信息1条

全文截稿: 2021-01-03

开会时间: 2021-05-10

会议难度: ★★

CCF分类: 无

会议地点: Melbourne, Australia

网址：http://icfec2021.eeecs.qub.ac.uk/

Billions of devices and sensors ranging from user gadgets to more complex systems with sensing and actuating capabilities, such as power grids or vehicles, from the physical world are getting connected to the Internet. However, the need to operate the scale of heterogeneous devices and sensors while being performance-efficient in real-time is challenging. Typically, the data generated by the devices and sensors are transferred to and processed centrally by services hosted on geographically distant clouds. This is untenable given the communication latency incurred and the ingress bandwidth demand.

A new and disruptive paradigm spear-headed by academics and industry experts is taking shape so that applications can leverage resources located at the edge of the network and along the continuum between the cloud and the edge. These edge resources may be geographically or in the network topology be closer to devices and sensors, such as home router, gateways or more substantial micro data centres. Edge resources may be used to offload selected services from the cloud to accelerate an application or host edge-native applications. The paradigm within which the edge is harnessed is referred to as 'Fog/Edge computing'.

The Fog/Edge computing paradigm is expected to improve the agility of service deployments, make use of opportunistic and cheap computing, and leverage the network latency and bandwidth diversities between these resources. Numerous challenges arise when using edge resources, which requires the re-examination of operating systems, virtualization and containers, and middleware techniques for fabric management. Extensions to current programming and storage models are required and new abstractions that will allow developers to design novel applications that can benefit from massively distributed and data-driven systems need to be developed. Addressing security, privacy and trust of the edge resources is of paramount importance while managing the resources and context for mobile, transient and hardware constrained resources. Lastly, emerging domains like autonomous vehicles and machine/deep learning need to be supported over such platforms.