{"title":"A configuration management assessment method for SON verification","authors":"T. Tsvetkov, S. Nováczki, H. Sanneck, G. Carle","doi":"10.1109/ISWCS.2014.6933382","DOIUrl":null,"url":null,"abstract":"Over the last years the complexity of mobile communication networks has significantly increased. Therefore, Self-Organizing Network (SON) features have been introduced to automate the process of fault-remedying, configuring Network Elements (NEs), and optimizing their operation. Such features are typically implemented by SON functions which actively perform changes to Configuration Management (CM) parameters in order to achieve certain objectives. However, having such features also requires a mechanism that allows us to verify their actions. In case certain NEs experience an undesired behavior, we have to be able to determine whether it is caused by CM changes and, if so, identify the responsible ones for that to happen. In this paper we propose a novel CM change performance assessment method with dynamic scope management for automated CM undo decision making. Our method includes two key properties: the ability to determine the minimal set of cells that are possibly influenced by a certain CM change, and generate a recommendation to accept or reject it based on the observed network performance. Results from our real data evaluation show our method is able to detect anomalous network behavior and identify the responsible changes.","PeriodicalId":431852,"journal":{"name":"2014 11th International Symposium on Wireless Communications Systems (ISWCS)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 11th International Symposium on Wireless Communications Systems (ISWCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISWCS.2014.6933382","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 16
Abstract
Over the last years the complexity of mobile communication networks has significantly increased. Therefore, Self-Organizing Network (SON) features have been introduced to automate the process of fault-remedying, configuring Network Elements (NEs), and optimizing their operation. Such features are typically implemented by SON functions which actively perform changes to Configuration Management (CM) parameters in order to achieve certain objectives. However, having such features also requires a mechanism that allows us to verify their actions. In case certain NEs experience an undesired behavior, we have to be able to determine whether it is caused by CM changes and, if so, identify the responsible ones for that to happen. In this paper we propose a novel CM change performance assessment method with dynamic scope management for automated CM undo decision making. Our method includes two key properties: the ability to determine the minimal set of cells that are possibly influenced by a certain CM change, and generate a recommendation to accept or reject it based on the observed network performance. Results from our real data evaluation show our method is able to detect anomalous network behavior and identify the responsible changes.