Implementing an agent based auction model on a cluster of reused workstations

Agent based models are often computationally intensive. Historically, the size and scope of agent based models has been limited by a lack of accessible high performance computing equipment. Clustering techniques allow for the creation of high performance computing environments at a relatively low cost. The low cost of clustering can be further reduced by utilising discarded computer workstations. In this paper, the authors evaluate the implementation of an agent-based model on a cluster of reused workstations. The workstations are reused PCs in a Linux based cluster and the authors concentrate on a Java based clustering and grid solution JavaParty. An existing agent based auction model is used to demonstrate the difference in performance, before and after the implementation of the model on a cluster. The authors compare the performance of the cluster implemented agent based auction model with the existing auction model and compare their execution times.