Table 8.

Comparison of existing papers in SDN.

Studies	Year	Area Discussed	Methods Used
Akyildiz et al. [247]	2014	Flow management, fault tolerance, topology update.	Supervised and unsupervised learning for traffic engineering
Xie et al. [248]	2017	Routing optimization, QoS, resource management security	Supervised and unsupervised learning for traffic engineering
Matlou et al. [249]	2017	SDN, wireless sensor networks	Supervised, reinforcement, and unsupervised learning
Jose et al. [250]	2017	Traffic classification and security	Comprehensive study on security and traffic using traditional and formal methods
Sultana et al. [251]	2018	Intrusion detection	Deep and unsupervised learning for IDS
Cui et al. [252]	2018	Traffic profiling	Different supervised and unsupervised learning methods
Loung et al. [253]	2018	Network function virtualization and QoS	Using machine learning and mathematical methods
Kreutz et al. [254]	2014	Comprehensive survey on SDN core concepts	General discussion based on the traditional and Openflow concepts
Wang et al. [255]	2015	Heterogeneous networks	AI-based techniques
Jamshidi et al. [256]	2016	Cybersecurity intrusion detection	Supervised learning and unsupervised learning
Mohammed at al. [257]	2019	Traffic classification and prediction	Supervised, reinforcement, and unsupervised learning
Tam et al. [258]	2018	Security in network	Machine and deep learning for security
Amin et al. [259]	2018	General concepts of hybrid SDN and terminologies	Categorization of hybrid SDN based on different technical models
Priyadarsini et al. [260]	2021	A comprehensive state-of-the-art progress report on specific topics of SDN	Classifications of traffic management, load balance, network safety, and controller placement