[hpc-announce] CFP: IEEE Transactions on Service Computing Special Issue on Edge AI As-a-Service

[Xiao Liu]

Call for Papers: IEEE TSC Special Issue on Edge AI-as-a-Service

It is essential to deliver learning-based artificial intelligence (AI) capabilities through API service endpoints at the edge under the as-a-service model to meet the growing demand for integrating big data, Internet of Things (IoT), and cloud computing capabilities. The edge AI services expedite making data-driven decisions (e.g., optimizing control, coordination, investment, medical services allocation, etc.). A sample research challenge addresses learning and/or inferencing efficiency of the edge AI service (or microservice) under development that meets the requirements for minimum level of quality of service (QoS), processing power, energy consumption, robustness, extensibility, and/or DevOps. Policy-based federated learning services at edge are typical edge AI use cases in which data processing and management constraints need to be considered in terms of data origin, ownership, heterogeneity, security, and privacy. 5G/6G edge nodes provide unprecedented high QoS wireless operating environments for edge AI services and related applications.

This special issue aims at promoting high-quality research on recent advances in edge AI-as-a-service and at inspiring related research efforts. Topics of interest include, but are not limited to, the following:

Deep-learning services at the edge
Learning-based service/microservice systems running atop edge devices/nodes Learning-based services/microservices hosted by 5G/6G edge nodes Policy-based learning services at the edge Edge-centric distributed or collaborative learning services Edge-centric federated learning services Learning-based event stream processing and/or contextual data enrichment of edge services Learning-based edge service management, optimization, and/or continuous improvement Learning-based security, privacy, trust, and/or risk management of edge services

Important Dates
Manuscript Submissions Due: December 31, 2020 First Round Notification: March 31, 2021 Revised Submissions Due: May 31, 2021 Final Decision Notification: June 30, 2021 Final Manuscript Submissions Due: July 31, 2021

Guest Editors
Prof. Andrzej Goscinski, Deakin University and RMIT Prof. Elisa Bertino, Purdue University Prof. Shangguang Wang, BUPT

Paper Submission
Please select "SI on Edge AI-as-a-Service" when submitting your manuscripts in the online system at https://mc.manuscriptcentral.com/tsc-cs. Please read the author guidelines before submitting. Every manuscript should be no more than 14 pages. Submitted manuscripts should not have been previously published nor be currently under review for publication elsewhere. Moreover, they should provide a minimum of 30% original technical contributions in comparison to previous publications.

_________________________
Dr. Xiao Liu BMgt, MMgt, PhD, SMIEEE
Associate Head Of School (International) and Senior Lecturer School of Information Technology, Deakin University, 221 Burwood Hwy, Burwood, VIC 3125.
www.deakin.edu.au
Deakin University CRICOS Provider Code 00113B

Ph: +61 3 92445428
e: xiao.liu at deakin.edu.au
office: T2.19, Melbourne Burwood Campus
w: https://sites.google.com/site/drxiaoliu/


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