Innovation and Application of Intelligent Processing of Data, Information and Knowledge as Resources in Edge Computing

Submission Deadline:  29 February 2020

IEEE Access invites manuscript submissions in the area of Innovation and Application of Intelligent Processing of Data, Information and Knowledge as Resources in Edge Computing.

Recently, edge computing is proposed as a new computing paradigm where resources like computation and storage are placed closer to the data and information source. Compared to cloud computing, edge computing enables a new class of latency and bandwidth sensitive applications since data can be processed at the network edge. It also brings new possibilities for the security and privacy research field, especially in data resilience and accessibility. A foreseeable developing direction is that more types of resources will be automatically and cooperatively processed at the edge and at the Cloud. Specifically, the resources to be processed will cover all types of data, information, knowledge and wisdom (DIKW) pyramid; the supported processing will include data sensing and acquisition, information analysis and abstraction, and knowledge generation and reasoning (potentially in the form of graphs).

However, there are still several issues which need to be solved: (a) conceptual modeling of the typed resources of data, information and knowledge at the source, (b) data-driven scheduling policies, especially the tradeoff of the computation/bandwidth cost and the performance improvement with the potential offloading overhead between the edge and the Cloud, and (c) the optimal organization of the network nodes at both the edge and the Cloud in terms of storage, bandwidth and computation distribution.

The goals of this Special Section in IEEE Access are (1) to present the state-of-the-art research on typed resource processing in Edge computing, and (2) to provide a forum for experts to disseminate their recent advanced views and ideas on future directions in this field.

In this Special Section, we encourage articles that present new theories, methods and techniques applied to value or quality-driven resource processing in Edge Computing. We particularly prefer articles demonstrating novel strategies to handle the types of processed resources. Applications may be drawn by investigating the usage of novel methods for all aspects of resource processing, including system design, performance optimization, algorithm design, scheduling, energy saving, and security management.

The topics of interest include, but are not limited to:

  • Typed resources modeling for Edge Computing
  • Data acquisition and linking for Edge Computing
  • Services composition and recommendation for Edge Computing
  • Testing technology for Edge Computing
  • Information analysis and abstraction for Edge Computing
  • Knowledge creation and reasoning for Edge Computing
  • Quality evaluation for resources management
  • Resources management, transfer and storage
  • Energy efficiency in Edge Computing
  • Value-driven optimization of resources processing
  • Smart Technologies for resource processing and utilization
  • Formal Modeling and Verification for resources processing
  • Big data and data analysis in Edge Computing
  • Security and privacy in resources processing and utilization
  • Device management (configuration, performance, and capacity) at the Edge
  • Offloading and cooperation between Edge and Cloud


We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.


Associate Editor: Honghao Gao, Shanghai University, China

Guest Editors:

  1. Ying Li, Zhejiang University, China
  2. Antonella Longo, Unversity of Salento, Italy
  3. Gongzhu Hu, Central Michigan University , USA
  4. Christophe Cruz, University of Bourgogne, France
  5. Jung-Yoon Kim, Gachon University, South Korea
  6. Alex Norta, Tallinn University of Technology, Estonia


Relevant IEEE Access Special Sections:

  1. Trusted Computing
  2. Internet-of-Things (IoT) Big Data Trust Management
  3. Data Mining and Granular Computing in Big Data and Knowledge Processing

IEEE Access Editor-in-Chief:
Derek Abbott, Professor, University of Adelaide

Paper submission: Contact Associate Editor and submit manuscript to:

For inquiries regarding this Special Section, please contact: