Surveys in Internet Services and Applications (2026)

Special Call on Surveys in Internet Services and Applications (2026)

This call invites submissions of high-quality, in-depth survey articles that consolidate and critically assess the current state of the variety of topics in Internet Services and Applications. Comprehensive surveys are essential for advancing research fields, as they organize fragmented knowledge, identify unresolved challenges, and inform future research directions. JISA seeks original surveys addressing the three layers of the Internet: Infrastructure and Networking, Middleware and Distributed Software Platforms, and Applications and Services, as well as the cross-cutting topic of Artificial Intelligence applied to Internet Services and Applications.
 

Topics of Interest

We welcome surveys on all topics within the scope of JISA. Topics of interest include, but are not limited to:

Infrastructure and Networking

  • Networking protocols and architectures
  • Web protocols, standards, and development
  • Security and privacy

Middleware and Distributed Software Platforms

  • Middleware and distributed software platforms
  • Cloud, fog, and edge computing
  • Mobile, ubiquitous, pervasive, and context-aware computing

Applications and Services

  • Internet of Things
  • Big Data
  • Applications and services

Transversal Topic

  • Artificial Intelligence applied to Internet Services and Applications

Surveys that cut across the three layers above are equally welcome.

Selection process

We welcome submissions from worldwide authors of original, unpublished, and novel in-depth surveys related to the topics of interest. Submissions will be evaluated based on the comprehensiveness of the literature coverage, the depth of critical analysis, the clarity of the proposed taxonomy or organization, and the value of the identified open challenges and future directions.

Important dates

  • Submission deadline: 01 November 2026

Guest Editors

  • Eduardo Cerqueira (Federal University of Pará - Brazil)
    Google Scholar: https://scholar.google.com/citations?user=6Oexn7IAAAAJ
    Prof. Dr. Eduardo Cerqueira is a Full Professor at the Institute of Technology, Federal University of Pará, Brazil. Eduardo is an internationally recognized researcher computer networks, IoT, cloud/edge computing, 5G/6G, and machine learning. He has published patents and more than 300 papers in national and international journals, conferences, and workshops. He has also served as chair, guest editor, and committee member of many conferences, workshops, and journals.

  • Ivan Zyrianoff (University of Bologna - Taly)
    Google Scholar:  https://scholar.google.com.br/citations?user=0LPd3y4AAAAJ
    Ivan Zyrianoff received his B.S. degree in Computer Science and his M.S. degree in Information Engineering from the Federal University of ABC, Santo André, Brazil, in 2017 and 2019, respectively. He received his Ph.D. degree from the University of Bologna, Bologna, Italy, in 2024. He is an Adjunct Professor at the University of Bologna and a member of the IoT-Prism Lab. His current research interests include interoperability for the Internet of Things, edge computing and intelligence, and proactive caching.
  • Luís Henrique M. K. Costa (Federal University of Rio de Janeiro - Brazil)
    Google Scholar: https://scholar.google.com.br/citations?user=XVZw8bwAAAAJ
    Prof. Dr. Costa received his Eng. and M.Sc. degrees in electrical engineering from Universidade Federal do Rio de Janeiro (UFRJ), Brazil, and the Dr. degree from Université Pierre et Marie Curie (Paris 6), Paris, France, in 2001. Since August 2020, he is a full professor with Poli/COPPE/UFRJ. Luís has coordinated several national and international R&D projects, including France, Canada, Chile, and Argentina. He is a member of the Brazilian Computer Society (SBC) and the Association for Computing Machinery (ACM). He serves as Associate Editor for IEEE Communications Surveys & Tutorials since 2017. His major research interests are network routing, wireless and vehicular networks, and machine learning networking applications.