Prof. Junshan Zhang, Arizona State University, Tempe, United States
Prof. Xu Chen, Sun Yat-sen University, Guangzhou, China
Prof. George Iosifidis, Trinity College Dublin, Ireland
Prof. Yan Zhang, University of Oslo, Norway
Prof. Yang Yang, Chinese Academy of Science, Shanghai, China
With the rapid development and widespread penetration of artificial intelligence technology, a variety of novel mobile and intelligent Internet of Things (IoT) applications are emerging, such as mobile face recognition, smart video surveillance, flying ad hoc networks for precision agriculture, and smart homes. These intelligent applications are typically resource-hungry, run computationally-intensive machine learning algorithms (e.g., deep learning), and demand real-time processing. Due to physical size limitations, nevertheless, many mobile and IoT devices are in general resource-constrained with limited computing power, and often times cannot fulfill the stringent QoS requirements of these applications.
To mitigate these challenges, edge/fog computing has been proposed as a promising paradigm that leverages a multitude of collaborative end-user devices and near-user infrastructures to carry out a substantial amount of computation, storage, and communication tasks. As edge/fog computing is implemented at network edges, it promises low latency as well as agile computation augmenting services for device users. To successfully support intelligent IoT applications, therefore, there is a significant need for 1) exploring the efficient deployment of edge/fog computing services at the network edges, 2) investigating novel algorithms of efficient edge/fog resource allocation, and 3) designing collaborative and distributed architectures specialized for edge/fog computing.
This workshop seeks original research papers on the design, implementation, evaluation and deployment of systems that embody any aspect of edge/fog computing for intelligent IoT applications. Topics include, but are not limited to:
|Paper submissions:||Feb. 4, 2018|
|Notification of acceptance:||March 4, 2018|
|Camera ready/registration due:||March 18, 2018|