## 1 Introduction  
The dramatic growth in communication technologies, specifically Fifth-Generation (5G), has obtained enormous interest due to its evolving generic services like massive machine-type communication, Ultrareliable and Low Latency Communication (URLLC), and enhanced mobile broadband [1, 2, 3]. Apart from this, it is one of the robust key enablers to realizing the so-called Tactile Internet, which provides to steer and control physical and virtual objects at a distance in real-time. The Tactile Internet is envisioned to enable human-to-machine communication where a human being can communicate with machines in a physical/virtual environment and experience haptic sensations (touch and forces) along with conventional audio-video traffic [4]. However, the strict requirements of Tactile Internet such as ultralow latency, ultrahigh reliability, high availability, and ultrasecurity remain open problems to enabling haptic communication over 5G. As per report Release 15 of the Third-Generation Partnership Project (3 GPP), the URLLC service provides the reliability of 99.9% for a data packet of size 32-byte with communication latency of 1 ms [5]. Tactile Internet demands a higher haptic data packet rate (1 kHz) and reliability greater than 99.9% under 1 ms latency. Therefore, the system design and architectural limitations of 5G technologies are not promising to realize haptic communication within 1 ms latency [6]. The sixth-generation (6G) systems with learnable network architecture address these challenges. In the literature, a number of studies present open systems interconnection stack layerwise analysis, identifying the requirements and challenges in each layer corresponding to next-generation emerging applications [6; 7]. The work in [8] explored the use cases and technical requirements of 6G systems. Similarly, the authors of [9] discussed the trade-off between computation, compression, bandwidth, and latency of the communication system, and the authors of [10] presented the Reinforcement-Learning (RL)-based resource allocation approaches for beyond 5G systems. The authors of [11] explored the zero-touch and network service management methods with a focus to enable the network to perform self-configuration and optimization based on application requirements. The authors present the network design, standard, and security aspects in the domain of zero-touch. The study in [12] revived the recent work on network security, privacy, and trust to realize the ultrasecure 6G communication network for emerging applications of 6G. In this work, we also present an overview of the 6G application along with security requirements. In order to achieve 1 ms latency, Software-Defined Networking (SDN) and Mobile Edge Computing (MEC) are utilized in the core network of 5G and beyond networks [13]. SDN provides the facility to separate the control and data plane in the communication network. The control plan is responsible for decision-making for network traffic while the data plan has a response to forwarding the traffic. The authors of the work [13] proposed an intelligent core network for smart applications of Tactile Internet. The authors utilized the SDN and MEC in a multitier way to the E2E latency requirements of Tactile Internet. The proposed model consists of three layers: a hardware resource layer, a software layer, and an application layer. The application layer link with the software layer via application programming interfaces. The hardware layer provides the MEC infrastructure in a multi-layer design to connect haptic devices. The last layer connects the remote application to interact with the operator. Similarly, the work in [14] explored technologies such as SDN and network function virtualizations (NFV) to realize Tactile Internet over mobile networks. The authors claim that integrating the SDN, NFV, and MEC is a promising solution to develop a general network infrastructure and support the Tactile Internet application.