This survey paper describes the significant literature survey of Sustainable Smart Cities
(SSC), Machine Learning (ML), Data Mining (DM), datasets, feature extraction and selection …

Smart city networks involve many applications that impose specific Quality of Service (QoS)
requirements, thus representing a challenging scenario for network management. Solutions …

Traffic classification with accuracy is of prime importance in network activities such as
security monitoring, traffic engineering, fault detection, accounting of network usage, billing …

This paper examines the use of deep recurrent neural networks to classify traffic patterns in
smart cities. We propose a novel approach to traffic pattern classification based on deep …

Substantial recent efforts have been made on the application of Machine Learning (ML)
techniques to flow statistical features for traffic classification. However, the classification …

Given the limitations of traditional classification methods based on port number and payload
inspection, a large number of studies have focused on developing classification approaches …

Network traffic classification is a significant and problematic aspect of network resource
management arising from an investigation of network developments, planning, and design …

Traffic classification is considered an important research area due to the increasing demand
in network users. It not only effectively improve the network service identifications and …

The rapid growth of current computer networks and their applications has made network
traffic classification more important. The latest approach in this field is the use of deep …

Nowadays Internet does not provide an exchange of information between applications and
networks, which may results in poor application performance. Concepts such as application …