A graph coloring approach for scheduling undo actions in self-organizing networks

In a mobile Self-Organizing Network (SON) a coordinator is necessary to avoid the execution of conflicting SON function instances. Typically, such a coordinator bases its decision to accept or reject a network parameter change request on a rule set that considers only known conflicts. Moreover, it does not observe the impact of approved changes on the network. For this reason, SON verification approaches have been specified to assess the impact of deployed configuration changes and identify those that are causing an undesired network behavior. Similarly to anomaly detection techniques, a SON verification mechanism has a mathematical model that specifies how the network behavior should look like and defines any behavior that significantly deviates form the expectations as abnormal. Furthermore, the outcome is a corrective action, also called an undo action, that sets network parameters to some previous configuration. The question that often remains unanswered is how conflicting undo actions should be scheduled. A SON coordinator does not have the knowledge to resolve them and may, therefore, prevent such from being deployed. In this paper we present a scheduling approach of such undo actions that uses minimum graph coloring in order to identify the sets of cells whose configuration can be safely rolled back. Our evaluation is split in two parts. In the first part we highlight the importance of our approach by observing a real Long Term Evolution (LTE) network. The second part is based on simulation data in which we show the ability of our method to keep the performance of the network at a high level.