by Sloman, Morris; Lobo, Jorge; Lupu, Emil

DOI: 10.1023/A:1011381100805
Print publication date: 6/1/2001
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DOI: 10.1023/A:1017388511496
Print publication date: 6/1/2001
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by Ho, L. Lawrence

DOI: 10.1023/A:1011323327425
Print publication date: 6/1/2001
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by Calo, Seraphin B.; Kar, Gautam

DOI: 10.1023/A:1011371210587
Print publication date: 6/1/2001
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by Sivabalan, M.; Mouftah, H. T.

Link-state routing protocols are being increasingly used in modern communications networks. A salient feature of this class of routing protocols is that network connectivity and state information of all links are available to nodes for making routing decision. Two main components of a link-state routing protocol are an update mechanism and a routing algorithm. These components must be properly designed for efficient routing. Various alternatives are possible for each of these components leading to different scenarios for routing protocol. In this paper, we quantitatively examine the impact of these alternatives on network performance using call-by-call simulations. Our design objective is to reduce call blocking ratio without significantly increasing routing overhead. We also present a new signaling scheme that can be used in conjunction with link-state protocols. We show that, if properly designed, this scheme can enhance the network performance.

DOI: 10.1023/A:1011319226517
Print publication date: 6/1/2001
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by Schulze, B.; Madeira, E. R. M.; Ropelatto, P.; Vasconcellos, F.

This paper explores the mobility paradigm in the monitoring management of open distributed systems. A pool of monitoring mobile agents is defined to explore the managed environment based on a successive approach to potential problems. The implementation is performed using an open distributed environment based on CORBA objects. The use of mobile agents adds flexibility to the management task and the merge with static agents allows the scalability of the monitoring management.

DOI: 10.1023/A:1011367109678
Print publication date: 6/1/2001
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by Chao, C. S.; Yang, D. L.; Liu, A. C.

The increasing importance of computer networks in this information age demands a high level of network availability and reliability. As we become more dependent on networks in our so-called cyber-world, network faults and downtime become very costly. Sometimes, a slight fault may cause critical disruptions or remediless damages to the network while the network manager is lost among a large amount of alarm messages. Therefore, the development of a practical and effective system for network fault diagnosis becomes an imperative and critical task. In this paper, we develop a hierarchical domain-oriented reasoning mechanism suitable for the delegated management architecture. It is based on the causality graph of a refined network fault propagation model as a result of our empirical study. An automated fault diagnosis system called Alarm Correlation View (or ACView) for isolating network faults in a multi-domain environment is proposed according to the hierarchical reasoning mechanism. This diagnosis system not only provides the process of automated alarm collection and correlation, but also serves the function of efficient fault localization and identification. Furthermore, an alarm-to-fault mapping strategy is used to enhance the fault reasoning capability for uncertain network fault propagation.

DOI: 10.1023/A:1011315125608
Print publication date: 6/1/2001
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by Ho, L. Lawrence; Cavuto, David J.; Papavassiliou, Symeon; Zawadzki, Anthony G.

Adaptive algorithms for real-time and proactive detection of network/service anomalies, i.e., soft performance degradations, in transaction-oriented wide area networks (WANs) have been developed. These algorithms (i) adaptively sample and aggregate raw transaction records to compute service-class based traffic intensities, in which potential network anomalies are highlighted; (ii) construct dynamic and service-class based performance thresholds for detecting network and service anomalies; and (iii) perform service-class based and real-time network anomaly detection. These anomaly detection algorithms are implemented as a real-time software system called TRISTAN (
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otification), which is deployed in the AT&T Transaction Access Services (TAS) network. The TAS network is a commercially important, high volume (millions of transactions per day), multiple service classes (tens), hybrid telecom and data WAN that services transaction traffic such as credit card transactions in the US and neighboring countries. TRISTAN is demonstrated to be capable of automatically and adaptively detecting network/service anomalies and correctly identifying the corresponding “guilty” service classes in TAS. TRISTAN can detect network/service faults that elude detection by the traditional alarm-based network monitoring systems.

DOI: 10.1023/A:1011311024699
Print publication date: 6/1/2001
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by Buttò, Milena; Naldi, Maurizio; Neri, Andrea

Network Traffic Management includes all the procedures set up for recognizing and solving traffic anomalies, i.e., any mismatching situation between traffic demand and network capacity that leads to an impairment in network performances. The resolution of traffic anomalies has generally received considerably more attention than the recognition phase. In this paper a diagnostic tool, based on the use of fuzzy logic, is proposed to recognize traffic anomalies (overloads and failures) on the basis of measurements currently available on commercial switches. The tool is composed of five separate inferential blocks, arranged over three hierarchical levels. The probability of correct diagnosis in the two opposite cases of no anomaly and moderate anomaly, evaluated by simulation, is shown to be over 97% for nodes and high usage trunk groups and over 90% for final trunk groups.

DOI: 10.1023/A:1011363008770
Print publication date: 6/1/2001
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by Lizambri, Todd; Wakid, Shukri; Duran, Fernando

DOI: 10.1023/A:1011363907861
Print publication date: 6/1/2001
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