Congestion Management Using K-Means for Mobile Edge Computing 5G System

The congestion management mechanism is essential to manage the explosive evolution of data traffic associated with advanced applications and services in the 5G system. As a result, we suggest a novel methodology to manage congestion for mobile edge computing in the 5G system. Furthermore, the proposed model enhances delay, energy consumption, and throughput. The enhanced random early detection strategy and the K-means approach are used in the suggested model to execute this. Also, a virtual list is realized to maintain packet information and suit more packets. The proposed model is realized in NS2 green cloud simulator. In comparison with the traditional cloud model and the fog computing model, the simulation results confirm that the proposed model reduces delay, boosts throughput, and decreases energy consumption.