Application placement and backup service in computer clustering in Software as a Service (SaaS) networks

• This paper studies a problem encountered in a SaaS network.
• The network provides reliable service to customers in case of a cluster failure.
• The problem is an interesting combinatorial problem related to several OR problems.
• The problem is complex and difficult to solve with a standard B&B algorithm.
• We proposed two effective algorithms to solve the problem.

This paper studies the reliable application placement problem encountered in computer clustering in Software as a Service (SaaS) networks. The problem involves deciding which software applications to install on each computer cluster of the provider and how to assign customers to the clusters in order to provide primary and backup service to customers in case of a cluster failure, while minimizing total cost. Given the complexity of the reliable application placement problem, we propose two algorithms to solve it. The first one is a probabilistic greedy algorithm and the second one is based on a reformulation of the problem where each cluster is to be assigned an application configuration from among all possible configurations or from a properly generated subset of configurations. Results of an extensive computational study show that the two algorithms are more effective than a standard branch-and-bound procedure based on the linear programming relaxation of the problem in solving problem instances with large sizes.