边缘计算
计算机科学
云计算
软件部署
边缘设备
互联网
杠杆(统计)
GSM演进的增强数据速率
移动边缘计算
分布式计算
计算机网络
效用计算
电信
万维网
操作系统
云安全计算
人工智能
作者
Gopika Premsankar,Mario Di Francesco,Tarik Taleb
出处
期刊:IEEE Internet of Things Journal
[Institute of Electrical and Electronics Engineers]
日期:2018-02-12
卷期号:5 (2): 1275-1284
被引量:579
标识
DOI:10.1109/jiot.2018.2805263
摘要
The amount of data generated by sensors, actuators, and other devices in the Internet of Things (IoT) has substantially increased in the last few years. IoT data are currently processed in the cloud, mostly through computing resources located in distant data centers. As a consequence, network bandwidth and communication latency become serious bottlenecks. This paper advocates edge computing for emerging IoT applications that leverage sensor streams to augment interactive applications. First, we classify and survey current edge computing architectures and platforms, then describe key IoT application scenarios that benefit from edge computing. Second, we carry out an experimental evaluation of edge computing and its enabling technologies in a selected use case represented by mobile gaming. To this end, we consider a resource-intensive 3-D application as a paradigmatic example and evaluate the response delay in different deployment scenarios. Our experimental results show that edge computing is necessary to meet the latency requirements of applications involving virtual and augmented reality. We conclude by discussing what can be achieved with current edge computing platforms and how emerging technologies will impact on the deployment of future IoT applications.
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