Abstract
As the data rate and area capacity are enormously increased with the advent of 5G wireless communication, the network latency becomes a severe issue in a 5G network. Since there are various types of terminals in a 5G network such as vehicles, medical devices, robots, drones, and various sensors which perform complex tasks interacting with other devices dynamically, there is a need to handle heavy computing resource intensive operations. Placing a multiaccess edge computing (MEC) server at the base station, which is located at the edge, can be one of the solutions to it. The application running on the MEC platform needs a specific simulation technique to analyze complex systems inside the MEC network. We proposed and implemented a simulation as a service (SIMaaS) for the MEC platform, which is to offload the simulation using a Cloud infrastructure based on the concept of computation offloading. In the case study, the Monte-Carlo simulations are conducted using the proposed SIMaaS to select the optimal highway tollgate where vehicles are allowed to enter. It shows how clients of the MEC platform use SIMaaS to obtain certain goals.
Highlights
With the advent of the 5G wireless communication service, the aggregate data rate and area capacity have been increased up to 1000 times compared to the existing 4G LTE network and the latency has been decreased to 1 ms [1, 2]
We assumed that the service rate (μ) of the processors follows exponential distribution of 1200 units per hour for electronic toll collection system (ETCS) and 257 units per hour for toll collection system (TCS)
autonomous vehicles (AVs) solely enters the tollgate specified by the multiaccess edge computing (MEC) server, while MV can enter another tollgate arbitrarily without following the decision made by the MEC server
Summary
With the advent of the 5G wireless communication service, the aggregate data rate and area capacity have been increased up to 1000 times compared to the existing 4G LTE network and the latency has been decreased to 1 ms [1, 2]. In order to effectively provide ultrareliable and low latency communication (URLLC) in the 5G network, a multiaccess edge computing (MEC) server, installed at the base station, becomes a very crucial technology to handle user’s requests in real time. As wireless network technology develops, more research is being done on how to effectively utilize the Cloud platform. Computation offloading technology has been developed in which user equipment (UE) connects to other platforms to utilize resources because complex tasks could not be performed in the device due to resource problems such as low computing power and weak energy [6]. The information collected from the connected heterogeneous terminals can be used to analyze complex systems, and social internet of things (SIoT) becomes a reality which have not been possible in the LTE network before. This paper proposed the environment since no research has previously been conducted on the MEC platform to provide simulations with a common feature
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