Energy-efficient task offloading strategy in mobile edge computing for resource-intensive mobile applications

• Published in: Digital communications and networks Vol. 8; no. 6; pp. 1048 - 1058
• Main Authors: Mahenge, Michael Pendo John, Li, Chunlin, Sanga, Camilius A.
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.12.2022; Department of Informatics and Information Technology,Sokoine University of Agriculture,Morogoro,3038,Tanzania; School of Computer Science and Technology,Wuhan University of Technology,Wuhan,Hubei,430063,China%School of Computer Science and Technology,Wuhan University of Technology,Wuhan,Hubei,430063,China%Department of Informatics and Information Technology,Sokoine University of Agriculture,Morogoro,3038,Tanzania; KeAi Communications Co., Ltd
• Subjects: Communication networks; Mobile edge computing; Particle swarm optimization; Quality of experience; Task offloading; Quality of experience; Communication networks; Particle swarm optimization; Mobile edge computing; Task offloading

Mobile Edge Computing (MEC) has been considered a promising solution that can address capacity and performance challenges in legacy systems such as Mobile Cloud Computing (MCC). In particular, such challenges include intolerable delay, congestion in the core network, insufficient Quality of Experien...