Telecommunications Network Planning and Maintenance

Telecommunications network operators are on a constant challenge to provide new services which require ubiquitous broadband access. In an attempt to do so, they are faced with many problems such as the network coverage or providing the guaranteed Quality of Service (QoS). Network planning is a multi-objective optimization problem which involves clustering the area of interest by minimizing a cost function which includes relevant parameters, such as installation cost, distance between user and base station, supported traffic, quality of received signal, etc. On the other hand, service assurance deals with the disorders that occur in hardware or software of the managed network. This paper presents a large number of multicriteria techniques that have been developed to deal with different kinds of problems regarding network planning and service assurance. The state of the art presented will help the reader to develop a broader understanding of the problems in the domain

AI Solutions for MDS: Artificial Intelligence Techniques for Misuse Detection and Localisation in Telecommunication Environments

This report considers the application of Articial Intelligence (AI) techniques to the problem of misuse detection and misuse localisation within telecommunications environments. A broad survey of techniques is provided, that covers inter alia rule based systems, model-based systems, case based reasoning, pattern matching, clustering and feature extraction, articial neural networks, genetic algorithms, arti cial immune systems, agent based systems, data mining and a variety of hybrid approaches. The report then considers the central issue of event correlation, that is at the heart of many misuse detection and localisation systems. The notion of being able to infer misuse by the correlation of individual temporally distributed events within a multiple data stream environment is explored, and a range of techniques, covering model based approaches, `programmed' AI and machine learning paradigms. It is found that, in general, correlation is best achieved via rule based approaches, but that these suffer from a number of drawbacks, such as the difculty of developing and maintaining an appropriate knowledge base, and the lack of ability to generalise from known misuses to new unseen misuses. Two distinct approaches are evident. One attempts to encode knowledge of known misuses, typically within rules, and use this to screen events. This approach cannot generally detect misuses for which it has not been programmed, i.e. it is prone to issuing false negatives. The other attempts to `learn' the features of event patterns that constitute normal behaviour, and, by observing patterns that do not match expected behaviour, detect when a misuse has occurred. This approach is prone to issuing false positives, i.e. inferring misuse from innocent patterns of behaviour that the system was not trained to recognise. Contemporary approaches are seen to favour hybridisation, often combining detection or localisation mechanisms for both abnormal and normal behaviour, the former to capture known cases of misuse, the latter to capture unknown cases. In some systems, these mechanisms even work together to update each other to increase detection rates and lower false positive rates. It is concluded that hybridisation offers the most promising future direction, but that a rule or state based component is likely to remain, being the most natural approach to the correlation of complex events. The challenge, then, is to mitigate the weaknesses of canonical programmed systems such that learning, generalisation and adaptation are more readily facilitated

Security risk assessment and protection in the chemical and process industry

This article describes a security risk assessment and protection methodology that was developed for use in the chemical- and process industry in Belgium. The approach of the method follows a risk-based approach that follows desing principles for chemical safety. That approach is beneficial for workers in the chemical industry because they recognize the steps in this model from familiar safety models .The model combines the rings-of-protection approach with generic security practices including: management and procedures, security technology (e.g. CCTV, fences, and access control), and human interactions (pro-active as well as re-active). The method is illustrated in a case-study where a practical protection plan was developed for an existing chemical company. This chapter demonstrates that the method is useful for similar chemical- and process industrial activities far beyond the Belgian borders, as well as for cross-industrial security protection. This chapter offers an insight into how the chemical sector protects itself on the one hand, and an insight into how security risk management can be practiced on the other hand

Una nueva capa de protección a través de súper alarmas con capacidad de diagnóstico

An alarm management methodology can be proposed as a discrete event sequence recognition problem where time patterns are used to identify the process safe condition, especially in the start-up and shutdown stages. Industrial plants, particularly in the petrochemical, energy, and chemical sectors, require a combined approach of all the events that can result in a catastrophic accident. This document introduces a new layer of protection (super-alarm) for industrial processes based on a diagnostic stage. Alarms and actions of the standard operating procedure are considered discrete events involved in sequences, where the diagnostic stage corresponds to the recognition of a special situation when these sequences occur. This is meant to provide operators with pertinent information regarding the normal or abnormal situations induced by the flow of alarms. Chronicles Based Alarm Management (CBAM) is the methodology used to build the chronicles that will permit to generate the super-alarms furthermore, a case study of the petrochemical sector using CBAM is presented to build the chronicles of the normal startup, abnormal start-up, and normal shutdown scenarios. Finally, the scenario validation is performed for an abnormal start-up, showing how a super-alarm is generated.Se puede formular una metodología de gestión de alarmas como un problema de reconocimiento de secuencia de eventos discretos en el que se utilizan patrones de tiempo para identificar la condición segura del proceso, especialmente en las etapas de arranque y parada de planta. Las plantas industriales, particularmente en las industrias petroquímica, energética y química, requieren una administración combinada de todos los eventos que pueden producir un accidente catastrófico. En este documento, se introduce una nueva capa de protección (súper alarma) a los procesos industriales basados en una etapa de diagnóstico. Las alarmas y las acciones estándar del procedimiento operativo son asumidas como eventos discretos involucrados en las secuencias, luego la etapa de diagnóstico corresponde al reconocimiento de la situación cuando ocurren estas secuencias. Esto proporciona a los operadores información pertinente sobre las situaciones normales o anormales inducidas por el flujo de alarmas. La gestión de alarmas basadas en crónicas (CBAM) es la metodología utilizada en este artículo para construir las crónicas que permitirán generar las super alarmas, además, se presenta un caso de estudio del sector petroquímico que usa CBAM para construir las crónicas de los escenarios de un arranque normal, un arranque anormal y un apagado normal. Finalmente, la validación del escenario se realiza para un arranque anormal, mostrando cómo se genera una súper alarma

Performance Measurement Systems, Competitive Priorities, and Advanced Manufacturing Technologies: Some Evidence from the Aeronautical Sector

Purpose – When acquiring advanced manufacturing technologies (AMT), the greatest caution should be taken regarding the performance measurement system to be used: the decision regarding new investments should not be conditioned by the excessive use of financial indicators to the detriment of the strategic objectives that motivated the investments. It is intended to analyze the aeronautical sector, for which the purchase of AMT is qualifying criteria, with two intentions: first, to identify the performance measurement systems that are used, and second, to test their correspondence with the objectives that motivated the investments. Design/methodology/approach – A survey of the 20 plants in the population was conducted via a postal questionnaire plus a structured interview. The unit of analysis has been maintained through the triangulation of data sources. Findings – The findings suggest that both financial and non-financial indicators are used, with the latter gaining predominance over the former on some occasions, even though there is no clear correspondence between strategy and the measurement of performance. In the light of the findings, the question of what inspires a company’s performance measurement system is still open, especially in those cases where there is no explicit strategy. With regard to practical implications, what seems to be indispensable is an improvement in the determination of the critical variables that should be used to measure performance. Research limitations/implications – Being valuable for academics and practitioners, this contribution relies, rather, on the possibility of a logical extrapolation to circumstances where the findings might apply, and researchers can judge whether the particular findings would be valid. Originality/value – Provides new evidence on the adaptation of the make-up and combination of the type of performance measures currently used by plants in the aeronautical industry, one of the sectors in which technological innovation is of the utmost importance.Publicad