Study On Upper Bound Models Of Performance In Self-Similar Network With Network Calculus

Network teletraffic is the foundation of all network researches, not only it canreflect the quality of network performance directly, but also it can be used forexpressing the behavior characteristic of network dynamics in some degree. For a longtime, people pay more attentions to continuously studying network performance basedon teletraffic. As the development of network technology and the arrival of informationsociety, Internet, as well as all kinds of high speed networks gradually has alreadyformed one open, complex giant system. Following with that, network teletraffic hasexploded, and its inherent characteristic has changed, which causes that the researcheson network performance based on teletrafflc become more and more important. As onekind of main statistical characteristic of high speed network teletraffic, Self-Similarityhas the influence on network performance. Therefore, to make a model of networkperformance based on self-similar teletraffie has the profound significance for thedevelopment of high-speed networks.So far, network performance based on teletraffic or self-similar teletraffic has beenresearched separately, aiming at the network performance or the self-similar networklonely, lacking in studying network performance based on self-similar teletraffic. Inaddition, more researchers pay attentions to analyzing and modeling the self-similarteletraffic of high-speed networks, lacking for thorough research in the aspect ofself-similar network control. In order to improve the performance of self-similarnetwork, it is important to study how to implement the control of Quality of Service(QoS) of self-similar network, so that it can avoid self-similar network congestion.Considering the influence of self-similarity on network performance, the model ofnetwork performance is studied synthetically and systemically based on self-similarteletraffic using network calculus in this paper. The main work and contributions arepresented in the following aspects:(1)To adapt to control self-similar teletraffic, the mathematical model of thefractal regulator (or fractal shaper) and the performance model of it with networkcalculus are proposed.On the researches of controlling self-similar teletrattic control, an overview of thecurrent major works on this field are presented, and then, on the basis of these currentresearch results, using network calculus theory, a general mathematical model of the fractal regulator for controlling self-similar teletraffic is proposed. The relationshipsbetween the output properties of the lossless fractal regulator and the loss fractalregulator and the self-similar parameter of the input traffic and the shaper curve and theshapers are derived. The performance of two kinds of the fractal regulator is analyzed,such as, queue length and delay. At last, the influences of the introduction of the fractalregulator on the end-to-end delay, the packets lost totals and the average lost rate arediscussed. These works and results of the analyses have practical significance for theevaluation of the control strategy of self-similar teletraffic and the configuration of theparameter of the fractal regulator parameter, as well as, provide the foundation for theresearch of the network performance based on self-similar teletraffic.(2) Using network calculus, the statistical and deterministic models of the upperbounds on the performance of General Processor Sharing (GPS), based on the fractalregulator with self-similar teletraffic input, are proposed.On the researches of the performance of the network single-node with self-similarteletraffic input, an overview of the current main works on the GPS system is presented.Based on the research results, the self-similar teletraffic on the ingress of the GPSsystem is reshaped and regulated by the fractal regulator, and the models of thestatistical and deterministic upper bounds on the performance of the GPS system withthe self-similar teletraffic input are proposed. These models include the statistical anddeterministic upper bounds on queue length, on delay, and the deterministic upperbounds on effective bandwidth and on delay jitter of the GPS system. Numericalexamples and results are presented to demonstrate that, the models of the statistical anddeterministic upper bounds on the performance of the GPS system based on the fractalregulators can reflect the self-similar characteristic of the self-similar teletraffic; theGPS system based on the fractal regulators fairly assigned its available outputbandwidth for each flow, and isolates from different flows.(3) Using network calculus, the deterministic upper bounds on end-to-end delay ofthe network system with self-similar teletraffic input are derived.On the researches of bounds on end-to-end delay of the network with theself-similar teletraffic input, the upper bounds on end-to-end delay in guaranteed servicewith network calculus are studied. The deterministic upper bounds on the ideaend-to-end delay as well as the approximate end-to-end delay, which used the GPSdispatcher and the fractal regulators as the node model, are derived. Numerical examples and results indicate that, the deterministic upper bounds on end-to-end delaythe system with self-similar teletraffic input increase along with the self-similarparameter reducing. This is advantageous to the improvement of the performance drop,which is owed to that the higher degree of the self-similarity of network teletraffic, thelonger delay.(4)Using network calculus, a performance model in guaranteed service isproposed.On the researches of performance models in guaranteed service, a generalperformance model in guaranteed service is proposed. On the basis of edge-corenetwork model, and using the arrival curve and the service curve, a two level schedulingmodel of the network node is proposed, and the upper bounds on queue length, delay,end-to-end delay, end-to-end delay jitter, and effective bandwidth of the performancemodel are derived. Numerical examples and results demonstrate that, the performancemodel in guaranteed service with network calculus provides a reference for the activecontrol, the scheduling strategy and the management of the guaranteed service networksproviding for QoS.