{"title":"Mechanism of dynamic, impact-aware and context-aware orchestration of cognitive functions in 5G networks","authors":"R. Ravichandran, M. Moorthy, S. Seetharaman","doi":"10.1109/ANTS.2018.8710053","DOIUrl":null,"url":null,"abstract":"As networks grow in size, heterogeneity and complexity, automated management and end-to-end orchestration to maintain service-level agreements (SLAs) becomes essential. With the advent of 5G, network slicing adds another dimension to this challenge. Cognitive functions play a key role in autonomic orchestration, and as cognitive functions increase in number, variety and are increasingly distributed in order to play a more effective role. In such a scenario, effective end-to-end orchestration of the cognitive functions is vital to reap the full benefits of the available intelligence for automated operation. Existing work in orchestrating cognitive functions has limitations in scope and coverage, and addresses only certain aspects. We propose a dynamic, impact-aware and context-aware end-to-end orchestration of cognitive functions in the network, resulting in improved overall SLA adherence of all services and network slices, and improved operational efficiency by minimizing human intervention.","PeriodicalId":273443,"journal":{"name":"2018 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ANTS.2018.8710053","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
As networks grow in size, heterogeneity and complexity, automated management and end-to-end orchestration to maintain service-level agreements (SLAs) becomes essential. With the advent of 5G, network slicing adds another dimension to this challenge. Cognitive functions play a key role in autonomic orchestration, and as cognitive functions increase in number, variety and are increasingly distributed in order to play a more effective role. In such a scenario, effective end-to-end orchestration of the cognitive functions is vital to reap the full benefits of the available intelligence for automated operation. Existing work in orchestrating cognitive functions has limitations in scope and coverage, and addresses only certain aspects. We propose a dynamic, impact-aware and context-aware end-to-end orchestration of cognitive functions in the network, resulting in improved overall SLA adherence of all services and network slices, and improved operational efficiency by minimizing human intervention.