Efficient, Dynamic Coordination of Request Batches in C-SON Systems

Romeikat, Raphael; Sanneck, Henning; Bandh, Tobias

doi:10.1109/vtcspring.2013.6692533

Cited by 15 publications

(4 citation statements)

References 5 publications

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“…The SON coordinator performs pre-action coordination by employing the batch coordination concept with dynamic priorities, as defined in [15]. Each SON function instance has an assigned bucket and dynamic priority.…”

Section: B Simulation Basedmentioning

confidence: 99%

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

Tsvetkov

Sanneck

Carle

2015

2015 IFIP/IEEE International Symposium on Integrated Network Management (IM)

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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.

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Section: B Simulation Basedmentioning

confidence: 99%

“…In addition, the idea of verifying a CM change triggered by a SON function instance and rolling it back based on certain rules has been introduced in [15]. Such rules, however, are defined with regard to SON coordination, i.e., only the priorities of the SON function instances are taken into consideration.…”

Section: Related Workmentioning

confidence: 99%

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

Tsvetkov

Sanneck

Carle

2015

2015 IFIP/IEEE International Symposium on Integrated Network Management (IM)

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“…The concept of pre-action SON coordination [1], [14] can be considered as an alternative approach to the concept we have introduced. It can be seen as a pessimistic strategy that defines rules used to detect and resolve known conflicts between running SON functions.…”

Section: Related Workmentioning

confidence: 99%

A Constraint Optimization-Based Resolution of Verification Collisions in Self-Organizing Networks

Tsvetkov

Carle

Frenzel

et al. 2014

2015 IEEE Global Communications Conference (GLOBECOM)

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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.

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“…Especially, when several SON function instances and human operators are operating independently in parallel. For this reason, policy-based pre-action coordination is applied to avoid known conflicts between SON function instances [3,12]. Such conflicts may include, for example, two SON function instances changing the same CM parameters (lost update problem) or one function influencing the input data of another (race condition), causing it to base its decisions on invalid data.…”

Section: Introductionmentioning

confidence: 99%

Network Element Stability Aware Method for Verifying Configuration Changes in Mobile Communication Networks

Ali-Tolppa

Tsvetkov

2016

Management and Security in the Age of Hyperconnectivity

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Efficient, Dynamic Coordination of Request Batches in C-SON Systems

Cited by 15 publications

References 5 publications

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

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

A Constraint Optimization-Based Resolution of Verification Collisions in Self-Organizing Networks

Network Element Stability Aware Method for Verifying Configuration Changes in Mobile Communication Networks

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