Guest Editor(s)
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- Prof. Dr. Shaohua Wan
- Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China, Shenzhen, Guangdong, China.
Website | E-mail
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- Prof. Dr. Liang Zhao
- School of Computer Science, Shenyang Aerospace University, Shenyang, Liaoning, China.
Website | E-mail
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- Prof. Dr. Thippa Reddy Gadekallu
- School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, India.
Website | E-mail
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- Prof. Dr. Sotirios K. Goudos
School of Physics, Aristotle University of Thessaloniki, Thessaloniki, Greece.
Website | E-mail
Special Issue Introduction
With the rapid development of mobile communications and the explosive usage of mobile devices (i.e., smart phones, laptops, tablets, etc.), the mobile Internet facilitates us with a pervasive and powerful platform to provide emerging applications. However, several mobile devices usually have limited computation capabilities and battery power. Migrating computational tasks from the distributed devices to the infrastructure-based cloud servers has the potential to address the aforementioned issues.
The cloud servers are located in the center of core network and far away from the users, which may cause delay fluctuation and additional transmission energy cost. Mobile Edge Computing (MEC) is an emerging paradigm, which pursues to provide better services by moving infrastructure-based cloud resources (computation, storage, bandwidth and etc.) to the edge of the network. MEC is rapidly becoming a key technology of 5G and beyond, achieving the key technical indicators of 5G business, such as ultra-low latency, ultra-high energy efficiency, and ultra-high reliability.
Obviously, when multiple smart devices upload tasks at the same time, they will inevitably compete with each other for both communication and computing resources Unreasonable resource allocation can result in a low data transmission rate and high delay. Thus, the designation of the task scheduling scheme has an important influence on the performance of the MEC system. Researchers are trying different optimization tools to minimize the latency and energy consumption as well as to maximize the performance of applications in MEC.
In addition, as pointed out above, the topic of topic of the computation offloading scheduling problem is not only important but also faces several challenges. This topic is very promising and will attract great interests from generalist and specialist readers, including researchers from academia and industry, mobile application developers as well as students who are engaged in this study.
This spacial issue welcome researchers from both academia and industry to provide their state-of-the-art technologies and ideas covering all aspects of Computing Offloading and applications in Mobile Edge Computing.
Topics of interest include, but are not limited to:
● Deep learning at the Computational Offloading in MEC;
● Light-weight learning for Intelligent Computational Offloading MEC;
● Theoretical modeling and performance analysis of resource optimization for Computational Offloading MEC;
● Joint cross-layer resource optimization for Computational Offloading MEC;
● Swarm intelligence algorithms for Computational Offloading MEC;
● Energy-aware Computational Offloading MEC planning for wireless networks and 5G and Beyond;
● New integration resource management architecture of cloud, and Computational Offloading MEC;
● Cross-layer service discovery and service recommendations for Computational Offloading MEC;
● Multi-user computation offloading for Computational Offloading MEC;
● Joint offloading and caching optimization for Computational Offloading MEC;
● Multi-edge-server collaboration for Computational Offloading MEC;
● Delay minimization service provision for Computational Offloading MEC;
● Cross-layer collaborative distributed systems for Computational Offloading MEC;
● Software-defined Computational Offloading MEC;
● Mobility management for Computational Offloading MEC;
● Security, privacy, and trust of Computational Offloading MEC;
● Cross-layer collaborative Computational Offloading MEC;
● Applications, such as smart city, smart grid, and intelligent transportation systems;
● Other green Computational Offloading MEC related topics.
Submission Deadline
20 May 2023
Journal of Smart Environments and Green Computing
