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Title

Enhanced Active Queue Management‑Based Green Cloud Model for 5G system using K-Means

  Alshimaa H. Ismail 1 * ,   Germien G. Sedhom 2 ,   Zainab H. Ali 3

1  Department of Communications and Electronics Engineering, Delta Higher Institute for Engineering and Technology, Talkha 35681, Egypt.
    (eng.alshimaahamdy@gmail.com)

2  Department of Communications and Electronics Engineering, Delta Higher Institute for Engineering and Technology, Talkha 35681, Egypt.
    (germien_ggs@yahoo.com)

3  Embedded Network Systems and Technology Department, Faculty of Artificial Intelligence, Kafrelsheikh University- Kafrelsheikh- Egypt
    (zainabhassan@ai.kfs.edu.e)


Doi   :   https://doi.org/10.54216/IJWAC.060206

Received: September 08, 2022 Accepted: November 25, 2022

Abstract :

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.

Keywords :

Active Queue Management-Based Green Cloud Model (AGCM); Mobile edge computing (MEC); K-means; 5G.

References :

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Cite this Article as :
Style #
MLA Alshimaa H. Ismail, Germien G. Sedhom, Zainab H. Ali. "Enhanced Active Queue Management‑Based Green Cloud Model for 5G system using K-Means." International Journal of Wireless and Ad Hoc Communication, Vol. 6, No. 2, 2023 ,PP. 65-72 (Doi   :  https://doi.org/10.54216/IJWAC.060206)
APA Alshimaa H. Ismail, Germien G. Sedhom, Zainab H. Ali. (2023). Enhanced Active Queue Management‑Based Green Cloud Model for 5G system using K-Means. Journal of International Journal of Wireless and Ad Hoc Communication, 6 ( 2 ), 65-72 (Doi   :  https://doi.org/10.54216/IJWAC.060206)
Chicago Alshimaa H. Ismail, Germien G. Sedhom, Zainab H. Ali. "Enhanced Active Queue Management‑Based Green Cloud Model for 5G system using K-Means." Journal of International Journal of Wireless and Ad Hoc Communication, 6 no. 2 (2023): 65-72 (Doi   :  https://doi.org/10.54216/IJWAC.060206)
Harvard Alshimaa H. Ismail, Germien G. Sedhom, Zainab H. Ali. (2023). Enhanced Active Queue Management‑Based Green Cloud Model for 5G system using K-Means. Journal of International Journal of Wireless and Ad Hoc Communication, 6 ( 2 ), 65-72 (Doi   :  https://doi.org/10.54216/IJWAC.060206)
Vancouver Alshimaa H. Ismail, Germien G. Sedhom, Zainab H. Ali. Enhanced Active Queue Management‑Based Green Cloud Model for 5G system using K-Means. Journal of International Journal of Wireless and Ad Hoc Communication, (2023); 6 ( 2 ): 65-72 (Doi   :  https://doi.org/10.54216/IJWAC.060206)
IEEE Alshimaa H. Ismail, Germien G. Sedhom, Zainab H. Ali, Enhanced Active Queue Management‑Based Green Cloud Model for 5G system using K-Means, Journal of International Journal of Wireless and Ad Hoc Communication, Vol. 6 , No. 2 , (2023) : 65-72 (Doi   :  https://doi.org/10.54216/IJWAC.060206)