Abstract—Self-organizing networks (SON) are nowadays considered a very important asset for mobile network providers since automatic solutions for fault diagnosis, network management, configuration and healing are of vital importance for managing complexity of such networks. The first step of a self-organizing network is the self-awareness which is achieved when the system is aware of its own functional state, like its load status, the existence of any failure or any security incident etc. Usually this is performed by a monitoring system and through metrics of system variables which indicate system’s state. Any deviation from acceptable levels that may cause any degradation to Quality of Service (QoS), provided by the system, may be considered as fault and is usually reported through alarms. The current paper will present a self-diagnosis framework for recognition of mobile network services failures which consist the first step for developing a survivable, robust, and reliable system. The focus of the presented proposal will be on signaling of Control Plane and User Plane of mobile systems and as a case study 4G LTE mobile network will be used for presenting examples of application of the proposed framework. The current paper is extended version of our paper with title “Fault Prediction Model for Node Selection Function of Mobile Networks” which will be presented to 9th International Conference on Information Communication and Management, and it is part of our research which focusses on methods for building Survivable and Reliable mobile networks.
Index Terms—Self-organizing networks, self-diagnosis, mobile networks, network monitoring.
Maria Mykoniati and Konstantinos Lambrinoudakis are with the University of Piraeus, 80, M. Karaoli & A. Dimitriou St, 18534 Piraeus, Greece (e-mail: mmykoniati@gmail.com, clam@unipi.gr).
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Cite:Maria Mykoniati and Costas Lambrinoudakis, "Self-diagnosis Framework for Mobile Network Services," Journal of Advances in Computer Networks vol. 7, no. 2, pp. 30-37, 2019.
