Mobile Information Systems

In-Network Cloudization Techniques and Applications in the Social Internet of Things Paradigm


Publishing date
01 Oct 2021
Status
Closed
Submission deadline
11 Jun 2021

Lead Editor

1Sejong University, Seoul, Republic of Korea

2Kongju National University, Cheonan, Republic of Korea

3University of Information Technology VNU-HCM, Ho Chi Minh City, Vietnam

4Ho Chi Minh National Academy of Politics, Hanoi, Vietnam

5Chung-Ang University, Seoul, Republic of Korea

This issue is now closed for submissions.
More articles will be published in the near future.

In-Network Cloudization Techniques and Applications in the Social Internet of Things Paradigm

This issue is now closed for submissions.
More articles will be published in the near future.

Description

There has been an explosive growth of multimedia computing, communication, and applications since the successful commercialisation of broadband mobile networks such as 4G and 5G. Multimedia data are considered an important part of modern social networking applications where user behaviours are content sharing and streaming to the network. In this context, media big data offers tremendous opportunities for social services, such as recommendations, advertisements, personal assistants, surveillance, games, and smart places. However, since the data are produced by a vast variety of user devices (e.g., mobile phones, wearable devices, cameras, etc.) in the emerging social Internet of things paradigm, the heterogeneity and massiveness of the data force the networks to be more powerful in terms of communication and computation as well as service availability. Over the past decade, cloud-based solutions have been proposed as promising approaches to this end.

However, cloud computing infrastructure suffers from high latency issues that cannot be acceptable for time-sensitive social services. Fortunately, cloudization that moves computing capability from the cloud to the edge of the network, resulting in mobile edge computing technology, might provide appropriate solutions, especially in terms of low latency and context awareness. Despite these advantages, edge-based social media computing techniques and applications must deal with several issues in the context of social media big data eras, such as data heterogeneity, data massiveness, social relationships, and security requirements. Several potential approaches have been studied, applying artificial intelligence, game theory, bio-inspired algorithms, and mathematical optimisation.

The aim of this Special Issue is to collate original and high-quality research articles that discuss the edge-based social media computing techniques and applications. Review articles discussing the current state of the art are also welcomed.

Potential topics include but are not limited to the following:

  • AI-based computing techniques and applications
  • Edge-based social media network architecture and models
  • Mobile social multimedia computing and analysis
  • Mobile caching policy for social multimedia services
  • Availability and reliability of in-network media computing
  • Context-aware media computing algorithms and frameworks
  • Social network security and policy
  • Trust and privacy in social media computing
Mobile Information Systems
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Acceptance rate52%
Submission to final decision46 days
Acceptance to publication25 days
CiteScore2.300
Journal Citation Indicator0.420
Impact Factor1.863
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Article of the Year Award: Outstanding research contributions of 2021, as selected by our Chief Editors. Read the winning articles.