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Although networks are widespread today, their management remains difficult because of the complex heterogeneity of the environment (LAN, MAN, multi-manufacturer, multi-media, multi-domain). A variety of computational techniques are required and different points of view must be taken into account to achieve a complete network management system.Firstly, management information must be extracted from network components and manipulated by the integrator (proxy agent). Secondly, management data must be maintained in the Management Information Base and distributed to the various management applications. Thirdly, management applications must be provided for diverse objectives, including: the functional objective (performance, configuration, accounting, fault security); the responsibility objective (network element, network, services, business management); the organizational objective (server resources management); and the domain objective (public, private). A variety of tools (expert systems, blackboard, man/machine interface) must be designed to optimize the system responses. Fourthly, these points of view must be integrated in a global and distributed environment.This publication examines the benefits of advanced information processing techniques for different local network management problems and considers the current academic and industrial research being carried out. It provides a good overview of the area for specialists, students and the network-using public and aims to stimulate further progress in the designing of local network management.
This volume constitutes the proceedings of the Second International Conference on Intelligence in Broadband Services and Networks (IS&N '94), held in Aachen, Germany in September 1994. The book addresses the design of telecommunication services in the rapidly changing technological and regulatory environment. The 47 revised papers presented in the volume reflect work done under the CEC RACE project "Intelligence in Services and Networks" as well as individual research done independently. The volume is organized in 11 chapters, all introduced by surveys by the session chairpersons. Among the topics covered are: the context of IS&N, user interfaces, component models and service creation, TMN implementation, service management, and beyond IN.
In recent years we have witnessed the explosion of multimedia traffic on the Internet. The availability of high bandwidth connections together with the recent advances in high quality video and audio compression techniques have created a fertile ground for the growth of multimedia applications such as interactive video on demand, collaborative distance learning, and remote medical diagnosis. Furthermore, the availability of low bit rate video and audio applications (e.g., H.263 and G.728) and the proliferation of pervasive devices create a new demand for wireless multimedia communication systems. After a decade or more of research and development in multimedia networking, the research community has learned a number of lessons. First, increasing the capacity of the “best effort” networks and services does not provide an effective and permanent solution for offering a guaranteed Quality of Service (QoS). Second, the integration of service and network management is a key element in providing end to end service management. Third, management techniques for Internet multimedia services must be scalable and adaptive to guarantee QoS and maintain fairness with optimal network resource.
Acquiring Task-Based Knowledge and Specifications to Seek Time Evaluation
This two-volume set LNICST 301 -302 constitutes the post-conference proceedings of the Third EAI International Conference on Advanced Hybrid Information Processing, ADHIP 2019, held in Nanjing, China, in September 2019. The 101 papers presented were selected from 237 submissions and focus on hybrid big data processing. Since information processing has acted as an important research domain in science and technology today, it is now to develop deeper and wider use of hybrid information processing, especially information processing for big data. There are more remaining issues waiting for solving, such as classification and systemization of big data, objective tracking and behavior understanding in big multimedia data, encoding and compression of big data.