A survey on intelligent computation offloading and pricing strategy in UAV-Enabled MEC network: Challenges and research directions

Authors

  • Asrar Ahmed Baktayan Sana'a University, Yemen
  • Ibrahim Ahmed Al-Baltah Sana'a University, Yemen

DOI:

https://doi.org/10.37868/sei.v4i2.id179

Abstract

The lack of resource constraints for edge servers makes it difficult to simultaneously perform a large number of Mobile Devices’ (MDs) requests. The Mobile Network Operator (MNO) must then select how to delegate MD queries to its Mobile Edge Computing (MEC) server in order to maximize the overall benefit of admitted requests with varying latency needs. Unmanned Aerial Vehicles (UAVs) and Artificial Intelligent (AI) can increase MNO performance because of their flexibility in deployment, high mobility of UAV, and efficiency of AI algorithms. There is a trade-off between the cost incurred by the MD and the profit received by the MNO. Intelligent computing offloading to UAV-enabled MEC, on the other hand, is a promising way to bridge the gap between MDs' limited processing resources, as well as the intelligent algorithms that are utilized for computation offloading in the UAV-MEC network and the high computing demands of upcoming applications. This study looks at some of the research on the benefits of computation offloading process in the UAV-MEC network, as well as the intelligent models that are utilized for computation offloading in the UAV-MEC network. In addition, this article examines several intelligent pricing techniques in different structures in the UAV-MEC network. Finally, this work highlights some important open research issues and future research directions of Artificial Intelligent (AI) in computation offloading and applying intelligent pricing strategies in the UAV-MEC network.

Author Biographies

Asrar Ahmed Baktayan, Sana'a University, Yemen

Asrar Ahmed Baktayan received her BSc degree in electronics and telecommunication from Aden University, Yemen, in 2006. She started working for Yemen Mobile-Telecommunication Operator in 2008 as a telecommunication traffic engineer in the core network department and has been working there until now. She is a graduate student of the Master of Information Technology (Networking and Distributed Systems) at Sana'a University. Her research interests are in wireless communication, mobility management, MEC, network slicing, and UAV in 5G networks.

Ibrahim Ahmed Al-Baltah, Sana'a University, Yemen

Ibrahim Ahmed Al-Baltah is an Associate Professor in the Department of Information Technology at Sana’a University, where he has been a faculty member since 2015. He is currently the Head of the Information Technology department. He received his BSc in Statistics and Computer Science (2007) from the University of Gezira, Sudan, his MSc in Software Engineering (2009), and his Ph.D. in Software Engineering (2014) from the University of Putra Malaysia. He has published several papers in highly reputable journals. He is a reviewer in some reputed international journals. His research interests are in green software engineering, resilience software engineering, cognitive software engineering, the semantic web, the semantic web of things, and semantic data fusion.

Published

2022-12-16

How to Cite

[1]
A. A. Baktayan and I. A. Al-Baltah, “A survey on intelligent computation offloading and pricing strategy in UAV-Enabled MEC network: Challenges and research directions”, Sustainable Engineering and Innovation, vol. 4, no. 2, pp. 156-190, Dec. 2022.

Issue

Section

Articles