Abstract
As current data centers and servers are growing in size by orders of magnitude when needed, load balancing is a great concern in scalable computing systems, including mobile edge cloud computing environments. In mobile edge cloud computing systems, a mobile user can offload its tasks to nearby edge servers to support real-time applications. However, when users are located in a hot spot, several edge servers can be overloaded due to suddenly offloaded tasks from mobile users. In this paper, we present a load balancing algorithm for mobile devices in edge cloud computing environments. The proposed load balancing technique features an efficient complexity by a graph coloring-based implementation based on a genetic algorithm. The aim of the proposed load balancing algorithm is to distribute offloaded tasks to nearby edge servers in an efficient way. Performance results show that the proposed load balancing algorithm outperforms previous techniques and increases the average CPU usage of virtual machines, which indicates a high utilization of edge servers.
Highlights
Load balancing is a fundamental problem in distributed systems and cloud computing environments [1,2,3]
InProposed this section, load balancing we describe technique the proposed with graph load balancing coloring based technique with graph coloring genetic algorithm
Providing scalability to data centers and servers is of great concern and a few load balancing techniques have been suggested by previous studies in edge cloud computing environments
Summary
Load balancing is a fundamental problem in distributed systems and cloud computing environments [1,2,3]. We develop a load balancing technique in edge cloud computing environments with mobile devices. Thisalgorithm approach to approach [21,22,23] that is inspired by natural evolution and reflects the natural selection process, with implementing the proposed load balancing technique, we can achieve both low algorithm complexity a fitness function for individuals for producing the generation.
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