Design and Simulation of a Hybrid Architecture for Edge Computing in 5G and Beyond

Edge Computing in 5G and Beyond is a promising solution for ultra-low latency applications (e.g., Autonomous Vehicle, Augmented Reality, and Remote Surgery), which have an extraordinarily low tolerance for delay and require fast data processing for a very high volume of data. The requirements of delay-sensitive applications (e.g., Low latency, proximity, and Location/Context-awareness) cannot be satisfied by Cloud Computing due to the high latency between User Equipment and Cloud. Nevertheless, Edge Computing in 5G and beyond can promise ultra-high-speed data processing thanks to the placement of computation capabilities closer to endpoint devices, where 5G encourages the speed rate that is 10 times faster than 4G LTE-Advanced. This paper deeply investigates Edge Computing in 5G and characterizes it based on the requirements of ultra-low latency applications. As a contribution, we propose a hybrid architecture that takes advantage of novel and sustainable technologies (e.g., D2D communication, Massive MIMO, SDN, and NFV) and has major features such as scalability, reliability, and ultra-low latency support. The proposed architecture is evaluated based on agent-based simulations demonstrating that our proposal can satisfy requirements and has the ability to respond to high volume demands with low latency.

Automated summary

Edge Computing in 5G and beyond offers a promising solution for ultra-low latency applications by placing computation capabilities closer to endpoint devices, enabling ultra-high-speed data processing. The proposed hybrid architecture utilizes novel and sustainable technologies to provide scalability, reliability, and support for ultra-low latency. Agent-based simulations demonstrate the architecture's ability to meet requirements and respond to high volume demands with low latency.