Accession Number : ADA293767
Title : Proactive Monitoring of Performance in Stochastic Communication Networks.
Descriptive Note : Master's thesis,
Corporate Author : AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OH SCHOOL OF ENGINEERING
Personal Author(s) : Van Hove, John C.
PDF Url : ADA293767
Report Date : MAR 1994
Pagination or Media Count : 192
Abstract : This research proposes several models for placing bounds on the expected values of some dynamic performance measures for computer communication networks with failing components. These models provide an understanding of expected network performance that is useful in the process of proactive performance monitoring and also in defining level of service agreements with network users. There were three objectives for this research. The first objective was to extend some existing models of steady-state stochastic network performance to a dynamic network flow representation in order to capture the dynamic nature of proactive monitoring. The second objective was to convert the extended absolute performance models to relative performance models that are dependent on the utilization level of the network. This was accomplished by converting a maximum network flow model for throughput to a minimum cost flow model with a constant level of source to sink network flow. The final objective was to demonstrate a methodology for validating the proposed models against an operational communication network. This was accomplished by collecting actual vector time-series performance data, using the models to estimate a similar data set, and performing some multivariate analysis with the two data sets.
Descriptors : *STOCHASTIC PROCESSES, *MONITORING, *COMMUNICATIONS NETWORKS, *COMPUTER NETWORKS, DATA BASES, STEADY STATE, COMPUTER COMMUNICATIONS, MODELS, NETWORKS, DYNAMICS, MULTIVARIATE ANALYSIS, TIME SERIES ANALYSIS, THESES, ESTIMATES, COST MODELS, VECTOR ANALYSIS, FLOW, UTILIZATION, NETWORK FLOWS.
Subject Categories : Computer Systems
Distribution Statement : APPROVED FOR PUBLIC RELEASE