Volume 6, Issue 2, PP: 65-72, 2023 | Cite this article as | XML | | Html PDF
Alshimaa H. Ismail 1 * , Germien G. Sedhom 2 , Zainab H. Ali 3
Doi: https://doi.org/10.54216/IJWAC.060206
The most unique and important design considerations in 5G cloud computing are the delay, energy consumption, and throughput. Therefore, most recent studies focused on boosting delay and energy consumption, and throughput using edge computing. The active queue management-based green cloud model (AGCM) is one of the most recent green cloud models that decreases the delay and sustains a stable throughput. Also, Mobile edge computing (MEC) is an essential cloud computing model for mobile users to meet the continuous growth of data requests. Thus, we offer a handoff scenario between the AGCM and MEC to assess the possible benefits of such collaboration and enhance its effects on the fundamental cloud restrictions such as delay and throughput. Accordingly, the proposed algorithm is named Enhanced Active queue management-based green cloud model (EAGCM). The proposed EAGCM regards incorporation between Kmeans and AGCM. The simulation results indicate that the proposed EAGCM serves mobile users efficiently, enhances the throughput, and reduces latency compared to AGCM and the cloud for 5G systems.
Active Queue Management-Based Green Cloud Model (AGCM) , Mobile edge computing (MEC) , K-means , 5G.
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