Engineering the Transition of Interactive Collaborative Software from Cloud Computing to Edge Computing

被引:0
|
作者
Ortegat G. [1 ]
Grolaux D. [2 ]
Riviere E. [1 ]
Vanderdonckt J. [1 ]
机构
[1] Université Catholique de Louvain, Louvain-la-Neuve
[2] ICHEC Brussels Management School, Brussels
关键词
cloud computing; distributed user interfaces; edge computing; peer-To-peer computing; perceived latency; system latency; traffic control; user interface migration;
D O I
10.1145/3532210
中图分类号
学科分类号
摘要
The "Software as a Service"(SaaS) model of cloud computing popularized online multiuser collaborative software. Two famous examples of this class of software are Office 365 from Microsoft and Google Workspace. Cloud technology removes the need to install and update the software on end users' computers and provides the necessary underlying infrastructure for online collaboration. However, to provide a good end-user experience, cloud services require an infrastructure able to scale up to the task and allow low-latency interactions with a variety of users worldwide. This is a limiting factor for actors that do not possess such infrastructure. Unlike cloud computing which forgets the computational and interactional capabilities of end users' devices, the edge computing paradigm promises to exploit them as much as possible. To investigate the potential of edge computing over cloud computing, this paper presents a method for engineering interactive collaborative software supported by edge devices for the replacement of cloud computing resources. Our method is able to handle user interface aspects such as connection, execution, migration, and disconnection differently depending on the available technology. We exemplify our approach by developing a distributed Pictionary game deployed in two scenarios: A nonshared scenario where each participant interacts only with their own device and a shared scenario where participants also share a common device, including a TV. After a theoretical comparative study of edge vs. cloud computing, an experiment compares the two implementations to determine their effect on the end user's perceived experience and latency vs. real latency. © 2022 ACM.
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