Group cooperation in network operations and management

Urban rail transit operations have changed from a single line to a multiline network. The network operations have undergone quantitative and qualitative changes, and operations management is facing rapid internal and external changes. Using the Guangzhou Metro network operation practices as a case study, this paper first systematically analyzes the features of the operation scale, the proportion of urban mass transit, the surge in public demand, the security of the operational service capacity, reforms to the operation governance structure, the high-speed expansion of staff, and the development of knowledge and skills in urban mass transit networks. The paper then proposes several responses to the challenges that such networks face; for example, this paper proposes creating an innovative network operations management system, strengthening the management foundation, creating plans to promote operation capacity, enhancing security risk management and equipment quality management, developing a crisis public relations response, and applying information technology. In addition, this paper systematically describes countermeasures for multiline network operations, such as developing a management mechanism for network operations, actively cultivating staff skills, creating innovative transport organization models to enhance operational capacity, establishing a production service assessment system to continuously improve the level of transportation service, establishing a quantifiable safety assessment system and equipment quality index model, strengthening quality controls for security and equipment, extensively using information technology to ensure the health of the urban mass transit network operation, and implementing sustainable development measures.

Faced with growing fierce competitive pressure on all fronts and market saturation, traditional telecommunication operators are now struggling to find the breakthrough approach by which they may successfully reshape their role from network service providers to multimedia service providers. They are re-examining their voice-centric business models and deploying next-generation networks (NGN) for QoS-guaranteed delivery of multimedia quadruple play services (QPSs). To cost effectively realize these paradigm shifts, the existing ;stability-oriented; network operations and management infrastructure and processes should be migrated into ;service-oriented; and ;business-driven; network operations and management within the context of today's multimedia and converged business environments. In this article, I'd like to introduce Network Operations and Management 2.0 (NOM 2.0), which is an innovative next generation operations and management paradigm for telephone company business agility and customer value creation. KT recently proposed Telco 2.0 [1], a new role and business model in the IP world to create customer value. NOM 2.0 is a key component needed to realize the Telco 2.0 goals. Telcos need to transform their operations and management framework into a human-centric and highly intelligent and automated one, and become the market leader by providing an agile operation and management framework within ever-changing operations and business environments. I will describe what NOM 2.0 is and how it is being realized in my company, KT.

Federated network operations become more and more important and the central challenge for Future Internet testbeds around the world. Federated network operations on Future Internet need to meet at least two conditions based on the general definition of federation [1]. First, multiple distributed network domains agree upon standards of network operations. Second, internal network operation of each domain is autonomous under its own control. Under the fundamental requirements, this paper presents a framework that federates and operates the autonomous distributed networks (ADNs) in the perspective of virtual network operations and end-user oriented network management on end-to-end network slices. In addition, we propose a virtual federated network (VFN) environment as a common federation interface between ADNs, associated with three key functionalities such as core network resource schema and representation, operational data exchanges, and end-to-end federated network operations. The performance consideration of this scheme includes the fast convergence of state updates on each ADN through VFN interface, as well as reliable and scalable operational dataset management of the federated Future Internet testbeds.

This paper addresses network management and operations issues for WDM networks. New WDM components, such as the optical spectrum analyzer, P(/spl lambda/), inexpensive WDM multiplexers with flat passband, and optical amplifiers with uniform gain, will be important technologies to enable cost effective and robust operation of WDM networks.

Different airport performance review studies identify aircraft turnaround as the major driver of departure delays that affect efficient airport and air traffic management (ATM) network operation. To mitigate such inefficiencies, reliable information sharing between all involved stakeholders as well as between them and the network manager is necessary. Analysing in depth the current environment and building on the airport collaborative decision-making concept, the ‘Turnaround Integration in Trajectory and Network’ (TITAN) project proposes an advanced concept of operations to identify improvement opportunities in the information flows between the various stakeholders as well as the potential influence of external processes still to be considered and to integrate the aircraft turnaround process into the aircraft business trajectory and the ATM network. After its successful validation, the proposed concept was realised by developing a decision-support tool that was subject to a cost-benefit analysis. It defined a service-oriented architecture that enhances sharing of a more predictive common awareness of all relevant influences on aircraft turnaround as a means of facilitating more predictable and intelligent decision making to mitigate turnaround delays and ameliorate airport performance. Considerations about how to integrate the project output into the existing ATM system and manage the transition to a future TITAN environment were also made. The project output is summarised in this paper.

A variety of Web-based applications, mobile apps, and other over the top data services with affordable 3G/4G enabled smart devices are major factors for enormous increase in heterogeneous data traffic at enterprise and mobile networks. This creates challenges regarding traffic management and requires traffic-aware intelligent network management to deliver sustained quality of experience for subscribers. Deep packet inspection and analysis (DPIA) provides base platform for development of traffic-aware intelligent network management and security systems. However, computationally complex DPIA-related packet processing for high speed data traffic makes these systems expensive. Furthermore, conventionally these traffic-aware network management and security systems are deployed in enterprise networks with independent and dedicated DPIA-related processing resources and require multiple copies of passively provisioned high speed data from network, while performing similar DPIA operations over the same data again and again. This duplicate deployment of expensive software and hardware resources for DPIA processing eventually results in higher capital expenditures as well as operational expenditures for network operators. We have proposed a novel service-oriented framework for heterogeneous deep packet inspection and analysis (SoDPI) that simultaneously provides diversified DPIA services to multiple client applications for network management and security operations in high-speed networks. Proposed framework provides flexible and comprehensive API-based service interface for client applications to register required DPIA services. SoDPI framework implementation is based on commodity hardware and deploys shared set of DPIA-related packet processing components, requiring only single copy of passive data provisioned from network. Experimental evaluations show that novel SoDPI framework requires considerably reduced amount of software and hardware resources to fulfill heterogeneous DPIA packet processing requirements for multiple client applications in comparison with conventional network management and security applications with dedicated DPIA components. This results in lower cost impacts for network operators with more network manageability.

Purpose – This paper examines the influence of network operational digitalization and network operational automation on sustainable operations, with operational efficiency as a mediating variable. The study was conducted at PT XYZ, a telecommunications company in Indonesia, employing a quantitative approach through a survey of 161 respondents working in network operational units. Methodology/approach – The research instrument was developed based on indicators of digitalization, automation, operational efficiency, and sustainable operations. Data collected were analyzed using Structural Equation Modeling with Partial Least Square (SEM-PLS) through SmartPLS software. Findings – The results reveal that both digitalization and automation of network operations significantly influence operational efficiency. Furthermore, operational efficiency plays a mediating role in linking digitalization and automation to sustainable operations. The study also identifies a significant direct effect of network operational digitalization on sustainable operations. However, network operational automation does not yet demonstrate a direct influence on sustainability outcomes. These findings suggest that while automation contributes to efficiency, its role in sustainability is still evolving, reflecting the staged maturity of technological adoption within the telecommunications industry. Originality/Value – Theoretically, this study contributes to the development of an integrative model connecting digital transformation and sustainable operations in the telecommunications sector. Empirically, it highlights the unique asymmetry between digitalization and automation in driving sustainability, which has been underexplored in prior research. Practically, the results provide valuable insights for company management in formulating effective strategies to enhance digitalization and automation-based network operation systems as a foundation for long-term sustainable operations.

The 2nd IEEE Workshop on Autonomic Communications and Network Management (ACNM 2008, http://www.nw.neclab.eu/acnm08) was held in Salvador-Brazil, April 11, 2008 in conjunction with the IEEE/IFIP Network Operations & Management Symposium (NOMS 2008). It followed the success of the previous meeting, ACNM 2007 (http://www.nw.neclab.eu/acnm07), held in Munich together with the IFIP/IEEE International Symposium on Integrated Network Management (IM 2007). The purpose of ACNM 2008 was to present and to discuss new theories, mechanisms, and applications of Autonomic Communication—a new paradigm for forthcoming networks—in the fixed as well as the mobile worlds. The focus of ACNM is on intelligent communication, network control and management paradigms based on smart network and service elements that are capable of automatically configuring and organizing themselves. Autonomic networks will be able to sense their environment to perceive changes, to understand the meaning of these changes, and to react in an intelligent manner

While worms and their propagation have been a major security threat over the past years, causing major financial losses and down times for many enterprises connected to the Internet, we will argue in this paper that valuable lessons can be learned from them and that network management, which is the activity supposed to prevent them, can actually benefit from their use. We focus on five lessons learned from current malware that can benefit to the network management community. For each topic, we analyse how it is been addressed in standard management frameworks, we identify their limits and describe how current malware already provides efficient solutions to these limits. We illustrate our claim through a case study on a realistic application of worm based network management, which is currently developed in our group.

Measuring the instability of IP prefixes in BGP is critical for network operation and management. In particular, identifying and investigating the most active prefixes assist in detecting, analyzing, and understanding network problems. The traditional metric to assess the activeness of a prefix is the quantity of BGP update. However, this metric may be strongly affected by monitor-local events: the large amount of updates for a highly active prefix may be caused by an event with rather limited impact area. To cope with the issue, we propose a two-dimensional method: in addition to the traditional metric, Update Quantity (UQ), we introduce Update Visibility (UV). The key idea is that we mark a prefix as a ‘Highly Active Prefix’ only when the large number of updates for it are widely observable. We define five types of active prefixes and propose a measurement method. We apply the method to 947 GB updates; the measurement results show that the two-dimensional method provides a more comprehensive picture of the highly active prefixes in the Internet than traditional single-metric schemes, and provides insights into network operations.

Stochastic two-stage reliability-based Security Constrained Unit Commitment in smart grid environment

We investigate opportunistic transmissions in a time-slotted wireless network, emphasizing constraints arising from finite durations allocated to various network operations and the availability of energy for these operations. Each time frame (time slot) comprises three sub-frames: sensing, reporting, and either transmission or energy harvesting based on the presence or absence of the primary user. We assume a fixed duration for the transmission sub-frame within each time frame. Utilizing a time division multiple access (TDMA) protocol, we manage local sensing data reporting within each time frame; consequently, the reporting time is contingent on the number of users. As a result, with the total time allocated for sensing and reporting being fixed, a trade-off arises between the number of collaborating users and the number of samples. Additionally, energy limitations and causality lead to two scenarios for wireless network operation: energy-deficit and energy-surplus regimes. To address this complexity, we formulate an optimization problem aimed at maximizing overall network throughput while considering constraints imposed by finite durations for various network operations and energy availability. We provide analytical evidence of the convexity of the optimization problem in both energy-deficit and energy-surplus scenarios. Furthermore, we propose two algorithms designed to achieve optimal throughput for each scenario. The accuracy of our analyses is validated through Monte Carlo simulations. Numerical results demonstrate the effectiveness of our proposed approach.

An intelligent network operator (INO), working as an artificial entity intelligence (AI) model, has been detailed and analyzed in this paper and involves an innovative approach, which is merging computer networks and artificial neural networks (ANNs). The operator first scans the network's state information into embedding vectors for matching embedding vectors of different types of information at each point of the network's operation. The fact that the operator has successfully cleared all testing phases with a 100% accuracy rate is mitigating the risks during the operation. Furthermore, extending the identification and resolution of major training losses is also introduced as a novel technique to maximize the overall efficiency of the operator's training process. A specific sealed computer network simulator has been designed to facilitate a teaching and testing environment. It also serves as a simulator that allows data collection, training, and testing procedures to be automated. This essay outlines succinctly the principal advancements used in this study through the use of the novel methodologies employed in the design, development and testing of the AI-based network operator. Both of these contributions are very important for the area and indicate that there exists the potential to improve network operations and training and testing frameworks through the application of AI.

The use of nonlinear analysis in network management and communication signal processing is a revolutionary strategy that is redefining contemporary networking paradigms. The goal of this project is to improve communication systems' resilience, efficiency, and agility by integrating cutting-edge nonlinear techniques. This study investigates the complex relationship between signal processing and network management using nonlinear analysis techniques in order to meet the growing needs of modern networks. Nonlinear approaches provide dynamic signal processing methods, enabling in-the-moment modifications that maximise data transfer under variable network circumstances. Prioritising data streams is made easier by this integration, which also improves network speed and efficiently allocates resources to guarantee Quality of Service (QoS). The study explores the complexities of interdisciplinary ideas, using the concepts of nonlinear analysis to comprehend phase transitions, emergent network architectures, and networks' inherent ability to self-organize. By deciphering the complexity of network behaviours and their evolution, this understanding aids in the creation of more effective management techniques. However, there are difficulties with computing complexity, interoperability, and skill adaption when using nonlinear analysis in network management. To properly utilise nonlinear approaches for network management and communication signal processing optimisation, these obstacles must be overcome. The research is important because it may lead to game-changing advancements in communication systems by introducing cutting-edge ways that go beyond the constraints of conventional, linear methods. The findings show potential for more effective and secure communication systems, which can meet the increasing needs of modern networking.

The ETSI's Zero touch network and Service Management (ZSM) framework is a prominent initiative to tame the envisioned complexity in operating and managing 5G and beyond networks. To this end, the ZSM framework promotes the shift toward full Automation of Network and Service Management and Operation (ANSMO) by leveraging the flexibility of SDN/NFV technologies along with Artificial Intelligence, combined with the portability and reusability of model-driven, open interfaces. Besides its benefits, each leveraged enabler will bring its own security threats, which should be carefully tackled to make the ANSMO vision a reality. This paper introduces the ZSM's potential attack surface and recommends possible mitigation measures along with some research directions to safeguard ZSM system security.