An optimized service broker routing policy based on differential evolution algorithm in fog/cloud environment

A cloud service provider (CP) offers computing resources with their own interface type and pricing policies besides other services such as storage on a pay-per-use model. Client’s requests should be processed in an appropriate CP datacenters in a trade-off relation between price and performance. The appropriate choice of a CP datacenters is the responsibility of the cloud-based service broker routing policy which acts as an intermediate between the users and the CP’s datacenters. However, due to the distribution nature of the CP’s datacenters, these datacenters can be overloaded with the increasing number of users and their requests being served at the same time if the datacenters are unwisely chosen. Therefore, choosing the appropriate datacenter is significant to the overall performance of the cloud computing systems. This paper aims to propose an optimized service broker routing policy based on different parameters that aims to achieve minimum processing time, minimum response time and minimum cost through employing a searching algorithm to search for the optimal solution from a possible solution space. A simulation-based deployment of the proposed algorithm along with a comparison study with other known algorithms form the field, confirms the ability of the proposed algorithm to minimize the load on service provider datacenters with minimum processing time, response time and overall cost.