No abstract

No abstract

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.

No abstract

The verification of Configuration Management (CM) changes is an important step in the operation of a Self-Organizing Network (SON). In order to perform its tasks, a verification mechanism makes use of an observation and a correction time window. In the first window it assesses the impact of deployed CM changes by monitoring the network's Performance Management (PM) data. Furthermore, it partitions the network in one or more verification areas, detects anomalies within them, and generates CM undo requests, each having the purpose to set CM parameters to some previous state. In the second window it deploys those requests to the network.However, two or more verification areas might be overlapping and share anomalous cells. As a consequence, we have verification collisions preventing two or more generated CM undo requests to be deployed at same time. Thereby, the verification mechanism might not be able to deploy all generated CM undo actions for the given correction window. In this paper, we propose a method that makes use of constraint optimization techniques to identify which requests can be merged together in order to meet the time requirement. We achieve our goal by using constraint softening based on so-called performance rating values of the requests. We evaluate our method in two different scenarios. First, we highlight the need for handling verification collisions by observing CM and PM data of a real Long Term Evolution (LTE) network. Second, a simulation study shows the ability of our method to keep the network performance at a high level.