The intelligent network-changing the face of telecommunications

Robrock, II R.B.

doi:10.1109/5.64379

Cited by 59 publications

(5 citation statements)

References 27 publications

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“…It will perform various tasks according to pre-set policies and algorithms, such as: 1) Network monitoring and fault detection: Intelligent operators will regularly scan network traffic, monitor equipment operating status, and detect any abnormal conditions; 2) Traffic management: It can dynamically adjust the network according to the traffic load and optimize the data transmission path to ensure the efficient operation of the network; 3) Security protection: Intelligent operators will monitor network security vulnerabilities and attacks in real time and take necessary measures to protect network security; 4) Automated tasks: It can perform a variety of automated tasks to reduce the workload of administrators. ; 5) Performance optimization: Intelligent operators will provide optimization suggestions and adjustment plans based on network usage and performance indicators to improve the overall performance and stability of the network [2].…”

Section: System Architecturementioning

confidence: 99%

Integration of computer networks and artificial neural networks for an AI-based network operator

Wu,

Xu,

Zhang

et al. 2024

ACE

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This paper proposes an integrated approach combining computer networks and artificial neural networks to construct an intelligent network operator, functioning as an AI model. State information from computer networks is transformed into embedded vectors, enabling the operator to efficiently recognize different pieces of information and accurately output appropriate operations for the computer network at each step. The operator has undergone comprehensive testing, achieving a 100% accuracy rate, thus eliminating operational risks. Additionally, a simple computer network simulator is created and encapsulated into training and testing environment components, enabling automation of the data collection, training, and testing processes. This abstract outline the core contributions of the paper while highlighting the innovative methodology employed in the development and validation of the AI-based network operator.

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Section: System Architecturementioning

confidence: 99%

Integration of computer networks and artificial neural networks for an AI-based network operator

Wu,

Xu,

Zhang

et al. 2024

ACE

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“…Some services can be offered to customers, such as Voice over IP (VoIP), while others are used as components to build other services, such as IP packet transport. This approach is not new, and dates back to telephony services and the Intelligent Network [13] platform. More recently, in the IT world, service oriented architectures have emerged to deliver IT services [14].…”

Section: Everything Is a Servicementioning

confidence: 98%

Blueprint for an Autonomic Service Architecture

Farha¹,

Leon-Garcia²

International Conference on Autonomic and Autonomous Systems (ICAS'06)

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Next-generation service providers will offer an array of services and applications that is media-rich, personalized, and context-aware. In this future environment, new services and applications will be introduced, provisioned, operated, maintained, and retired at a pace that tracks changing customer requirements and demands. In order to be cost-effective, these services and applications need to be delivered over an all-IP infrastructure, which is autonomically managed to ensure their delivery at a satisfactory level for subscribed customers. In this paper, we propose a blueprint for a generic Autonomic Service Architecture (ASA) to address these challenges.

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“…Conventional telecommunication networks have evolved into an Intelligent Network [6] employing complex signalling systems among various network components in order to provide advanced and customizable services. The network is intelligent because it has the capabilities to route, screen, and forward calls based on various parameters such as time of day, day of week, caller's or callee's telephone number and/or location, and usersupplied specification etc.…”

Section: Conventional Telecommunication Networkmentioning

confidence: 99%

Signalling adaptors between distributed systems and telecommunication networks

Lin¹,

Chiang²

Proceedings. 18th International Conference on Distributed Computing Systems (Cat. No.98CB36183)

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The conventional telecommunication software components are mainly developed using message-passing as the underlying communication mechanisms. Recent standards on modern distributed systems, exemplified by CORBA and DCE, however, have converged to a new programming paradigm based on client/server architecture, objectoriented model, and Remote Procedure Calls (RPCs). In the near future, we envision the coexistence of conventional and CORBA or DCE-based telecommunication software components. As a result, protocol converters between the network components using message-oriented protocol and the ones using RPCs have become an important issue. This paper addresses how to interwork these two different communication paradigms using Signalling Adaptor (SA), which is a protocol converter for enabling seamless communications between message-based systems and object-oriented, RPC-based systems.

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The intelligent network-changing the face of telecommunications

Cited by 59 publications

References 27 publications

Integration of computer networks and artificial neural networks for an AI-based network operator

Integration of computer networks and artificial neural networks for an AI-based network operator

Blueprint for an Autonomic Service Architecture

Signalling adaptors between distributed systems and telecommunication networks

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