@article{(Open Science Index):https://publications.waset.org/pdf/10012971,
	  title     = {AI-Based Approaches for Task Offloading, ‎Resource ‎Allocation and Service Placement of ‎IoT Applications: State of the Art},
	  author    = {Fatima Z. Cherhabil and  Mammar Sedrati and  Sonia-Sabrina Bendib‎},
	  country	= {},
	  institution	= {},
	  abstract     = {In order to support the continued growth, critical latency of ‎IoT ‎applications and ‎various obstacles of traditional data centers, ‎Mobile Edge ‎Computing (MEC) has ‎emerged as a promising solution that extends the cloud data-processing and decision-making to edge devices. ‎By adopting a MEC structure, IoT applications could be executed ‎locally, on ‎an edge server, different fog nodes or distant cloud ‎data centers. However, we are ‎often ‎faced with wanting to optimize conflicting criteria such as ‎minimizing energy ‎consumption of limited local capabilities (in terms of CPU, RAM, storage, bandwidth) of mobile edge ‎devices and trying to ‎keep ‎high performance (reducing ‎response time, increasing throughput and service availability) ‎at the same ‎time‎. Achieving one goal may affect the other making Task Offloading (TO), ‎Resource Allocation (RA) and Service Placement (SP) complex ‎processes. ‎It is a nontrivial multi-objective optimization ‎problem ‎to study the trade-off between conflicting criteria. ‎The paper provides a survey on different TO, SP and RA recent Multi-‎Objective Optimization (MOO) approaches used in edge computing environments, particularly Artificial Intelligent (AI) ones, to satisfy various objectives, constraints and dynamic conditions related to IoT applications‎.},
	    journal   = {International Journal of Information and Communication Engineering},
	  volume    = {17},
	  number    = {2},
	  year      = {2023},
	  pages     = {137 - 143},
	  ee        = {https://publications.waset.org/pdf/10012971},
	  url   	= {https://publications.waset.org/vol/194},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 194, 2023},
	}