State-dependent M/G/1 type queueing analysis for congestion control in data networks

We study a TCP-like linear-increase multiplicative-decrease flow control mechanism. We consider congestion signals that arrive in batches according to a Poisson process. We focus on the case when the transmission rate cannot exceed a certain maximum value. The distribution of the transmission rate in steady state as well as its moments are determined. Our model is particularly useful to study the behavior of TCP, the congestion control mechanism in the Internet. Burstiness of packet losses is captured by allowing congestion signals to arrive in batches. By a simple transformation, the problem can be reformulated in terms of an equivalent M/G/1 queue, where the transmission rate in the original model corresponds to the workload in the `dual' queue. The service times in the queueing model are not i.i.d., and they depend on the workload in the system

A L\'evy input fluid queue with input and workload regulation

We consider a queuing model with the workload evolving between consecutive i.i.d.\ exponential timers $\{e_q^{(i)}\}_{i=1,2,...}$ according to a spectrally positive L\'evy process $Y_i(t)$ that is reflected at zero, and where the environment $i$ equals 0 or 1. When the exponential clock $e_q^{(i)}$ ends, the workload, as well as the L\'evy input process, are modified; this modification may depend on the current value of the workload, the maximum and the minimum workload observed during the previous cycle, and the environment $i$ of the L\'evy input process itself during the previous cycle. We analyse the steady-state workload distribution for this model. The main theme of the analysis is the systematic application of non-trivial functionals, derived within the framework of fluctuation theory of L\'evy processes, to workload and queuing models

Bandwidth sharing with heterogeneous service requirements

We consider a system with two heterogeneous traffic classes. The users from both classes randomly generate service requests, one class having light-tailed properties, the other one exhibiting heavy-tailed characteristics. The heterogeneity in service requirements reflects the extreme variability in flow sizes observed in the Internet, with a vast majority of small transfers ('mice') and a limited number of exceptionally large flows ('elephants'). The active traffic flows share the available bandwidth in a Processor-Sharing (PS) fashion. The PS discipline has emerged as a natural paradigm for modeling the flow-level performance of bandwidth-sharing protocols like TCP. The number of simultaneously active traffic flows is limited by a threshold on the maximum system occupancy. We obtain the exact asymptotics of the transfer delays incurred by the users from the light-tailed class. The results show that the threshold mechanism significantly reduces the detrimen

Analysis of two competing TCP/IP connections

Many mathematical models exist for describing the behavior of TCP/IP under an exogenous loss process that does not depend on the window size. The goal of this paper is to present a mathematical analysis of two asymmetric competing TCP connections where loss probabilities are directly related to their instantaneous window size, and occur when the sum of throughputs attains a given level. We obtain bounds for the stationary throughput of each connection, as well as an exact expression for symmetric connections. This allows us to further study the fairness as a function of the different round trip times. We avoid the simplifying artificial synchronization assumption that has frequently been used in the past to study similar problems, according to which whenever one connection looses a packet, the other one looses a packet as well

State-dependent M/G/1 type queueing analysis for congestion control in data networks

We study in this paper a TCP-like linear-increase multiplicative -decrease flow control mechanism. We consider congestion signals that arrive in batches according to a Poisson process. We focus on the case when the transmission rate cannot exceed a certain maximum value. We write the Kolmogorov equations and we use Laplace Transforms to calculate the distribution of the transmission rate in the steady state as well as its moments. Our model is particularly useful to study the behavior of TCP, the congestion control mechanism in the Internet. By a simple transformation, the problem can be reformulated in terms of an equivalent M/G/1 queue, where the transmission rate in the original model corresponds to the workload in the `dual' queue. The service times in the queueing model are not i.i.d., and they depend on the workload in the system

State-dependent M/G/1 type queueing analysis for congestion control in data networks

We study in this paper a TCP-like linear-increase multiplicative -decrease flow control mechanism. We consider congestion signals that arrive in batches according to a Poisson process. We focus on the case when the transmission rate cannot exceed a certain maximum value. We write the Kolmogorov equations and we use Laplace Transforms to calculate the distribution of the transmission rate in the steady state as well as its moments. Our model is particularly useful to study the behavior of TCP, the congestion control mechanism in the Internet. By a simple transformation, the problem can be reformulated in terms of an equivalent M/G/1 queue, where the transmission rate in the original model corresponds to the workload in the `dual' queue. The service times in the queueing model are not i.i.d., and they depend on the workload in the system. Keywords---TCP congestion control, batch Poisson process, Kolmogorov equation, Laplace Transform. I