Increase the Efficiency of Deploying Application Instances in Edge Environment

To enhance the efficiency of deploying application instances on edge servers, this paper proposes a greedy algorithm (KEAD-P) that utilizes prioritized queues (heap). The algorithm initially generates an index of the available servers and an empty list to store the selected servers. It then calculates the coverage benefit of each available server, which in turn determines the ACRB (Coverage-Robustness Increase Benefit) of each server. Based on the results of the calculation, the algorithm constructs a priority queue (heap) that prioritizes the servers with the highest ACRB. Finally, the algorithm selects servers by continuously cycling until the number of application instances is within the budget limit K. The experimental results indicate that KEAD-P algorithm can significantly reduce service deployment time while maintaining high-quality service benefits compared to the BEAD-o algorithm, thereby enhancing the efficiency of service deployment.