Enterprise Workload Management through Ant Colony Optimization
Sami J. Habib, Paulvanna Nayaki Marimuthu, Naser Al-Ibrahim · 2014
Lately, the business enterprise networks (BEN) are expected to support more online applications than what are initially designed for, due to the competitive nature of the business nowadays. The business applications are known to generate sudden increase in traffic workload, which poses challenges in providing guaranteed service to all the new and old clients. Thus, the network administrators are faced with many challenges in how to smartly manage BEN with the available resources and at the same time maintain satisfactory returns on the business. Over-provisioning of resources may not be a feasible solution, and thus, BEN can be improved by re-synthesizing the existing infrastructure by localizing the workflow. At the duration of the sudden increase in the workflow within BEN, we view the infrastructure as a fully connected graph and the aim is to convert the fully connected graph into a connected one by re-grouping the clients into new clusters. We have formulated the conversion problem as an optimization problem with an objective function to maximize the local traffic within the new clusters; moreover, we have utilized Ant Colony Optimization (ACO) to find the suitable conversion. The simulation results show that re-synthesizing a typical BEN comprising of 100 clients with a heavy traffic of 7.54 TB into a set of 5 clusters reduces the backbone traffic by 18%.