Research On The Fluid Flow Model For Self-similar Networks Traffic And AQM Algorithms

Congestion control in TCP (Transmission Control Protocol) is the basis for theInternet steady operation. The TCP protocol congestion control has been a focusedresearch area of the Internet, which is attracting many scholars. Due to dramaticallyincreasing network traffic and quality of service (QoS) requirements for a variety ofreal-time traffic, it is difficult to meet with the network requirements, dependingsolely on end-to-end congestion control. In fact, in a complex and heterogeneousnetwork environment, it is unpractical to keep compatible congestion controlscheme in end-to-end systems for all users. Control of routers and other intermediatenetwork devices must be involved in order to enhance the effect of congestioncontrol. It is at the router where congestions occur actually; therefore it ismeaningful to conduct queue management mechanism at the router. With earlycongestion predicting and active packet dropping, active queue management (AQM)mechanisms could enforce the congestion control and avoid the deadlock and theglobal synchronization. This is the so-called IP congestion control. IP congestioncontrol mechanism is a current research focal point. In this research, the explicitcongestion control mechanism with routers involved is also classified as an IPcongestion control mechanism.The study of the self-similarity of network traffic overthrows the basicassumption that the network traffic is with short-range dependence. As the result ofmore remarkable burstiness of traffic, more congestion occurred frequently andaggravatingly. It is destined to make the analysis of statistical characteristics of thenetwork traffic and the performance of the router queuing, and the set of the buffersize at the router, different from the original assumptions. The introduction ofself-similar model is not only bound to bring new challenges to congestion controlwhich is inherently complex, but also new solutions.The round-trip time (RTT) is the prerequisite to effectively operate congestioncontrol mechanism followed the rhythm step by step. The imprecision of theestimation for the network delay also plays a primary role while network congestionmechanism occasionally fails. Therefore it is necessary to model the RTTrespectively to be a constant, a common function, a stochastic process and suchdifferent mathematical formats. By mathematical analysis, in this research theimpact of the RTT is analyzed against congestion control mechanisms in networks.Further, an explicit congestion control algorithm named as QDCN is proposed basedon network queuing delay. In this algorithm, the router queue length is monitored,and then the queuing delay is obtained to update RTT in real-time. By explicit notice sent by the router，the source end decided to change the congestion window in orderto avoid congestion.Further, the SFPID-RED and QDCN perform gradationally, which do perfectlyat a constant rate network service before. However, the delay is not the primarycauses of the performance degradation. In fact, the self-similarity of network traffic(burstiness) leads to the failure of these algorithms while the delay jitter is just amanifestation. Therefore, a self-Similar-Traffic-based RED algorithm named asSTRED is proposed. In this algorithm, time slots are adopted as the operating unit toreduce the workload of calculation and the updating rate of the network parameters.The self-similarity coefficient (Hurst coefficient) is estimated based on time slots toobserve and record values, and the packet drop probability in the RED algorithm isadjusted based on several relative functions in order to enhance the adaptability toself-similar network traffic and to achieve the congestion control under this traffic.However, the continuous academic debates are carried on about whether thenetwork traffic performes Poisson characteristics (short-range dependence, SRD) orself-similar fractal (long-range dependence, LRD). Although there is a large numberof measuring experiments in kinds of networks so that the conclusion is obtainedwhich networks are self-similar. However, there are also evidences that Poissoncharacteristics still exist. Network traffic models have experienced a SRD, LRD,multi-fractal evolved evolution, and now show a tendency back to SRD. In fact,both SRD and LRD characteristics of networks traffic are coexisted. Hence, in thisresearch a new type of Lévy stochastic process is proposed based on networks withself-similarity and TCP/AQM fluid flow model. Meanwhile, a TCP/AQM fluid flowmodel with wave particle duality is also established, which can describe theself-similarity in networks and the characteristic of a packet driver (SRD) at thesame time. This model tried to unify the two theories on the characteristics of thenetwork traffic, and further to understand the nature of the model with duality,which builds up the foundation for the algorithm design of congestion control infuture based on the self-similar network.In summary, this research mainly focused on the network congestion problem,analyzed a widely applied network traffic model named as TCP/AQM fluid flowmodel. Based on this analysis combined with characteristics of self-similar networks,a series of research approach has been proposed.