Dynamic Web Services Selection Using a Hidden Markov Model

In a service oriented architecture based on web services exists the possibility of failures occurring at the time a transaction between web services runs. These failures are undesired because they reduce the system's performance. Self-healing systems are based on the model of the human body to restore it from an unhealthy state to a healthy one. These self-healing systems represent a good option for handling failures in a system based on web services. However, self-healing systems could improve their performance by adding a mechanism than selects the most suitable web services to perform certain functions. Moreover the diagnosis module of the self healing system would benefit by reducing the failures situations caused by anomalous web services. In this paper we propose to reduce the number of system's failures by employing a hidden Markov model that assist in the selection of web services through the use a QoS-based model. By reducing the number of failures this mechanism would support the diagnosis module of a self-healing system.