YOU COULD REGISTER ON-LINE VIA www.lrg.ufsc.br/~lanoms99.
***** IEEE LANOMS99 - TUTORIALS *****
TUTORIAL 1.1 - The technological and Economic Effects of the Deregulation
of the Global Telecommunications Industry upon the Application
of the Principles of Network Management
By Keith von Mecklenburg (St. Andrews University, Scotland)
Auditorium#1 - Dec 05 - 09:00 - 12:30
TUTORIAL 1.2 - Neural Networks and Distributed Algorithms for Network
Management
By Jayantha Herath (St. Cloud State University, USA), and
By Susantha Herath (Aizu University, Japan)
Auditorium#2 - Dec 05 - 09:00 - 12:30
TUTORIAL 2.1 - New Global Solutions of Event Correlation based on
Distributed infrastructure
By Gabriel Jakobson (GTE, USA)
Auditorium#1 - Dec 05 - 14:00 - 17:30
TUTORIAL 2.2 - Network Management with SNMP: The Manager-Agent and
Distributed Paradigms
By Elias P. Duarte Jr. (Federal University of Parana, Brazil)
Auditorium#2 - Dec 05 - 14:00 - 17:30
***** IEEE LANOMS99 - TUTORIALS ABSTRACS *****
TUTORIAL 1.1 - The Technological and Economic Effects of the Deregulation
of the Global Telecommunications Industry upon the Application of the
Principles of Network Management
Deregulation has increased the level of competition within National and
International Telecommunications Industries, as State firms (e.g. Deutsche
Telekom) and those private firms that dominate the telecoms market ( e.g.
the Bell Companies and BT) within national jurisdictions, have to consider
the lowering of line access charges to meet that competitive situation.
It means that all firms, incumbents and new entrants, have to be focussed
on the level of fixed and variable costs. Instead of being able to design and
implement technological network systems with little regard to costs, the
pressure is upon management to find the most effective technological
solution which will also meet the measure of the lowest fixed and variable
costs.
The tutorial will therefore advance a new set of network management
principles to meet the new and developing market competitive situation.
Network Management will seek to develop operational models which satisfy the
conflicting demands of the best technological and the best economic models
of effective Network Management.
TUTORIAL 1.2 - Neural Networks and Distributed algorithms for Network
Management
This tutorial provides an overview to network management issues in high
performance distributed computing which promises wide range of new
computationally intensive applications such as intelligent agents, data
mining, computing at remote sites across wide variety of networks
including the web. Network management and development of such applications
and tools are neither easy nor quick because of the heterogeneous nature
of the distributed systems. The problem becomes much difficult because of
the service needs of distributed computations to be considered in the
design and implementation process. Such needs include locating resources,
allocating resources, communication protocols, security, accessibility,
files, faults, memories and control. Network management is crucial to
achieving highest performance from a dynamically changing distributed
computing environment.
This tutorial addresses the importance of applying learning techniques to
distributed algorithms for network management. After providing an overview
of centralized, hierarchical and distributed management models, protocols
and architectures it will introduce the importance of integrating learning
algorithms to the distributed algorithms. It will describe neural network
based computations as one out of many learning techniques available for
such applications. The focus will be to examine the integration of
learning techniques to distributed algorithms for network management. This
tutorial will also overview the recent activities and issues in the areas
of communication protocols, synchronization algorithms for clocks,
elections and deadlock handling, scheduling and fault tolerance of
distributed processes and processors, sharing and replication management
of distributed file systems and distributed shared memories.
>From this tutorial you will learn network management models, neural
network algorithms and distributed algorithms for network management.
TUTORIAL 2.1 - New Global Solutions of Event Correlation based on
Distributed infrastructure
Audience: This is an introductory/intermediate level tutorial. The intended
audience includes network/service managers and technical operations support
professionals interested in learning new advanced methods of fault,
performance.
Abstract: Event correlation is a widely accepted technology for managing the
complexity of modern telecommunication and data networks. Specific
correlation applications have been developed to manage switched, SS7,
wireless, ATM, SONET, IP, and other networks. All major players in the
network management arena have either developed their own, usually
embedded event correlation procedures, or have used event correlation
products such as InCharge, NerveCenter, ILOG, ART-Enterprise, RTWorks,
NetExpert, and G2. Various approaches to event correlation exist,
including rule-, case-, and model-based reasoning, finite Major network
operations support functions, based on real-time event correlation have
emerged, including reduction of event flow by context-sensitive event
filtering, fault management by fault diagnostics, localization, root
cause identification and generation of corrective actions, and status
reporting of complex multi-level hierarchical networks by semantic
generalization of Despite the progress in the development of event
correlation systems, there is a need to re-evaluate the current event
correlation solutions and define new directions. It is important to
broaden the utility of event correlation to other aspects of network
management, such as performance, configuration, testing, security, and
service quality management. Most importantly, the technology should be
extended to perform cross-correlation between different domains, e.g.
cross-correlation This tutorial is divided into three parts. In the first
introductory part we will review the tasks, objectives, major
technologies and products of existing solutions of event correlation. In
the second part, we will introduce the concept, architectural
framework, and components of a distributed global event correlation
solution. In the third part we will illustrate how the concepts and
architectural framework were implemented in a particular system GRACE,
developed at GTE Laboratories. We will discuss the use of CORBA, Java,
XML, SWING, Jacc and other technologies in GRACE, and illustrate the use
of event correlation ith practical network management examples.
TUTORIAL 2.2 - Network Management with SNMP: The Manager-Agent and
Distributed Paradigms
[Abstract]
This tutorial starts with an introduction to the SNMP network management
framework, describing its main components, including the SMI, MIB's,
agents, management applications and the protocol itself. Following this
introduction, the distributed paradigm for network management is examined,
as well as different approaches for its deployment using SNMP. Case
studies are presented, including the Routing Proxy, the Delegado MIB
and the implementation of distributed system-level diagnosis using
SNMP. Finally, an overview of the IETF's DisMan MIB's is presented.
[Audience]
This is an introdutory/intermediate tutorial. The intended audience
includes network managers and technical professionals interested in
learning about SNMP and how it can be used both a manager-agent and a
distributed management paradigm.
***** IEEE LANOMS99 - TUTORIALS REGISTRATION FORM ****
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