Abstract: Utilizing smart mobile devices for entertainment, education, and social networking has grown recently. Even though mobile applications are getting more sophisticated and resource-intensive, the computing power of mobile devices is still constrained. Mobile phone applications can perform better by shifting parts of their functions to cloud servers. However, because the cloud is frequently positioned far from mobile phone users, there may be a significant and unpredictable delay in the data transfer between users and the cloud. It is crucial for mobile applications since customers value rapid responses greatly. Users of mobile phones can get close-up access to information technology and cloud computing services thanks to mobile edge computing. In this article, the main goal is to use an artificial bee colony meta-innovative algorithm to solve the problem of placing edge servers in mobile edge computing. Moreover, load balancing between servers is one of the challenges discussed in this article. To deal with this issue, determination the locations of the servers using considering the distribution of workload between servers as a cost function in the artificial bee colony algorithm is a focused issue in this study. The results of the proposed method are compared with the load balancing criteria. The results of K-means compared to the clustering method show the superiority of the proposed method with regard to the loading criteria compared to this clustering method.

Bing Zhou, Bei Lu and Zhigang Zhang, “Placement of Edge Servers in Mobile Cloud Computing using Artificial Bee Colony Algorithm” International Journal of Advanced Computer Science and Applications(IJACSA), 14(2), 2023. http://dx.doi.org/10.14569/IJACSA.2023.0140273

@article{Zhou2023,
title = {Placement of Edge Servers in Mobile Cloud Computing using Artificial Bee Colony Algorithm},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.0140273},
url = {http://dx.doi.org/10.14569/IJACSA.2023.0140273},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {2},
author = {Bing Zhou and Bei Lu and Zhigang Zhang}
}