The emerging of diversified new telecommunications technologies leads to a continuous change of telecom networks. Consequently, the operations support systems of telecommunications operators are facing structure adjus...The emerging of diversified new telecommunications technologies leads to a continuous change of telecom networks. Consequently, the operations support systems of telecommunications operators are facing structure adjustments as well as new systems construction. In this situation, new generation operations support systems standards are urgently required. Several standardization organizations have made substantial progress in the study of the new generation standards, such as ITU' s study on Next Generation Network (NGN) management, TMF's on New Generation Operations Systems and Software (NGOSS) and CCSA's on network management standards. However, the existing operations support systems face the challenges of architecture improvement, change of the focus of operations support, orientation of customers' demands and technology evolution.展开更多
The modern history of management systems is almost the same as the history of modern management science. Implicit management systems have been in existence for many 100s of years. ISO has paid attention to the issue o...The modern history of management systems is almost the same as the history of modern management science. Implicit management systems have been in existence for many 100s of years. ISO has paid attention to the issue of the integrated management systems since the ISO 9000 family standards for quality management systems (QMS) and ISO 14000 series standards for environment management syste(EMS) were published. ISO/TAG(Technical Advisory Group)12 was formed by the ISO/TM(Technical Management Board) in early 1997 with the mandate to achieve greater compatibility between the relevant ISO/TC 176 and ISO/TC 207 standards in the field of management systems, auditing, terms and definitions. The report was submitted to TMB by TAG 12 in 1999.展开更多
Broadcasting gateway equipment generally uses a method of simply switching to a spare input stream when a failure occurs in a main input stream.However,when the transmission environment is unstable,problems such as re...Broadcasting gateway equipment generally uses a method of simply switching to a spare input stream when a failure occurs in a main input stream.However,when the transmission environment is unstable,problems such as reduction in the lifespan of equipment due to frequent switching and interruption,delay,and stoppage of services may occur.Therefore,applying a machine learning(ML)method,which is possible to automatically judge and classify network-related service anomaly,and switch multi-input signals without dropping or changing signals by predicting or quickly determining the time of error occurrence for smooth stream switching when there are problems such as transmission errors,is required.In this paper,we propose an intelligent packet switching method based on the ML method of classification,which is one of the supervised learning methods,that presents the risk level of abnormal multi-stream occurring in broadcasting gateway equipment based on data.Furthermore,we subdivide the risk levels obtained from classification techniques into probabilities and then derive vectorized representative values for each attribute value of the collected input data and continuously update them.The obtained reference vector value is used for switching judgment through the cosine similarity value between input data obtained when a dangerous situation occurs.In the broadcasting gateway equipment to which the proposed method is applied,it is possible to perform more stable and smarter switching than before by solving problems of reliability and broadcasting accidents of the equipment and can maintain stable video streaming as well.展开更多
文摘The emerging of diversified new telecommunications technologies leads to a continuous change of telecom networks. Consequently, the operations support systems of telecommunications operators are facing structure adjustments as well as new systems construction. In this situation, new generation operations support systems standards are urgently required. Several standardization organizations have made substantial progress in the study of the new generation standards, such as ITU' s study on Next Generation Network (NGN) management, TMF's on New Generation Operations Systems and Software (NGOSS) and CCSA's on network management standards. However, the existing operations support systems face the challenges of architecture improvement, change of the focus of operations support, orientation of customers' demands and technology evolution.
文摘The modern history of management systems is almost the same as the history of modern management science. Implicit management systems have been in existence for many 100s of years. ISO has paid attention to the issue of the integrated management systems since the ISO 9000 family standards for quality management systems (QMS) and ISO 14000 series standards for environment management syste(EMS) were published. ISO/TAG(Technical Advisory Group)12 was formed by the ISO/TM(Technical Management Board) in early 1997 with the mandate to achieve greater compatibility between the relevant ISO/TC 176 and ISO/TC 207 standards in the field of management systems, auditing, terms and definitions. The report was submitted to TMB by TAG 12 in 1999.
基金This work was supported by a research grant from Seoul Women’s University(2023-0183).
文摘Broadcasting gateway equipment generally uses a method of simply switching to a spare input stream when a failure occurs in a main input stream.However,when the transmission environment is unstable,problems such as reduction in the lifespan of equipment due to frequent switching and interruption,delay,and stoppage of services may occur.Therefore,applying a machine learning(ML)method,which is possible to automatically judge and classify network-related service anomaly,and switch multi-input signals without dropping or changing signals by predicting or quickly determining the time of error occurrence for smooth stream switching when there are problems such as transmission errors,is required.In this paper,we propose an intelligent packet switching method based on the ML method of classification,which is one of the supervised learning methods,that presents the risk level of abnormal multi-stream occurring in broadcasting gateway equipment based on data.Furthermore,we subdivide the risk levels obtained from classification techniques into probabilities and then derive vectorized representative values for each attribute value of the collected input data and continuously update them.The obtained reference vector value is used for switching judgment through the cosine similarity value between input data obtained when a dangerous situation occurs.In the broadcasting gateway equipment to which the proposed method is applied,it is possible to perform more stable and smarter switching than before by solving problems of reliability and broadcasting accidents of the equipment and can maintain stable video streaming as well.
