Modeling, Analysis and Impact of a Long Transitory Phase in Random Access Protocols

In random access protocols, the service rate depends on the number of stations with a packet buffered for transmission. We demonstrate via numerical analysis that this state-dependent rate along with the consideration of Poisson traffic and infinite (or large enough to be considered infinite) buffer size may cause a high-throughput and extremely long (in the order of hours) transitory phase when traffic arrivals are right above the stability limit. We also perform an experimental evaluation to provide further insight into the characterisation of this transitory phase of the network by analysing statistical properties of its duration. The identification of the presence as well as the characterisation of this behaviour is crucial to avoid misprediction, which has a significant potential impact on network performance and optimisation. Furthermore, we discuss practical implications of this finding and propose a distributed and low-complexity mechanism to keep the network operating in the high-throughput phase.Comment: 13 pages, 10 figures, Submitted to IEEE/ACM Transactions on Networkin

Packetized-voice/data integrated transmission on a token passing ring local area network

This paper investigates the performance of a token passing ring network with packetized-voice/data mixed traffic through extensive simulations. Both data and voice users are modeled in the simulations. Data users produce bursty traffic. Voice traffic is modeled as having alternating talkspurts and silences, with generation of voice packets at a constant rate during talkspurts and no packet generation during silence periods.The network performance measures obtained include: the distribution of transmission delays for voice packets, the average transmission delay and loss probabilities for voice packets, the number of voice users allowed on a network while satisfying the real-time constraints of speech, and the average transmission delay for data packets.Token passing ring local area networks are shown to effectively handle both voice and data traffic. The effects of system parameters (e.g., voice packet length, talkspurt/silence lengths, data traffic intensity, and limited versus exhaustive service disciplines) on network performance are discussed

Modelling and stability of FAST TCP

We introduce a discrete-time model of FAST TCP that fully captures the effect of self-clocking and compare it with the traditional continuous-time model. While the continuous-time model predicts instability for homogeneous sources sharing a single link when feedback delay is large, experiments suggest otherwise. Using the discrete-time model, we prove that FAST TCP is locally asymptotically stable in general networks when all sources have a common round-trip feedback delay, no matter how large the delay is. We also prove global stability for a single bottleneck link in the absence of feedback delay. The techniques developed here are new and applicable to other protocols

An Improved Link Model for Window Flow Control and Its Application to FAST TCP

This paper presents a link model which captures the queue dynamics in response to a change in a transmission control protocol (TCP) source's congestion window. By considering both self-clocking and the link integrator effect, the model generalizes existing models and is shown to be more accurate by both open loop and closed loop packet level simulations. It reduces to the known static link model when flows' round trip delays are identical, and approximates the standard integrator link model when there is significant cross traffic. We apply this model to the stability analysis of fast active queue management scalable TCP (FAST TCP) including its filter dynamics. Under this model, the FAST control law is linearly stable for a single bottleneck link with an arbitrary distribution of round trip delays. This result resolves the notable discrepancy between empirical observations and previous theoretical predictions. The analysis highlights the critical role of self-clocking in TCP stability, and the proof technique is new and less conservative than existing ones

Congestion Control for Network-Aware Telehaptic Communication

Telehaptic applications involve delay-sensitive multimedia communication between remote locations with distinct Quality of Service (QoS) requirements for different media components. These QoS constraints pose a variety of challenges, especially when the communication occurs over a shared network, with unknown and time-varying cross-traffic. In this work, we propose a transport layer congestion control protocol for telehaptic applications operating over shared networks, termed as dynamic packetization module (DPM). DPM is a lossless, network-aware protocol which tunes the telehaptic packetization rate based on the level of congestion in the network. To monitor the network congestion, we devise a novel network feedback module, which communicates the end-to-end delays encountered by the telehaptic packets to the respective transmitters with negligible overhead. Via extensive simulations, we show that DPM meets the QoS requirements of telehaptic applications over a wide range of network cross-traffic conditions. We also report qualitative results of a real-time telepottery experiment with several human subjects, which reveal that DPM preserves the quality of telehaptic activity even under heavily congested network scenarios. Finally, we compare the performance of DPM with several previously proposed telehaptic communication protocols and demonstrate that DPM outperforms these protocols.Comment: 25 pages, 19 figure

Conditional limit theorems for regulated fractional Brownian motion

We consider a stationary fluid queue with fractional Brownian motion input. Conditional on the workload at time zero being greater than a large value $b$, we provide the limiting distribution for the amount of time that the workload process spends above level $b$ over the busy cycle straddling the origin, as $b\to\infty$. Our results can be interpreted as showing that long delays occur in large clumps of size of order $b^{2-1/H}$. The conditional limit result involves a finer scaling of the queueing process than fluid analysis, thereby departing from previous related literature.Comment: Published in at http://dx.doi.org/10.1214/09-AAP605 the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org

Resource dimensioning through buffer sampling

Link dimensioning, i.e., selecting a (minimal) link capacity such that the users’ performance requirements are met, is a crucial component of network design. It requires insight into the interrelationship among the traffic offered (in terms of the mean offered load , but also its fluctuation around the mean, i.e., ‘burstiness’), the envisioned performance level, and the capacity needed. We first derive, for different performance criteria, theoretical dimensioning formulas that estimate the required capacity $c$ as a function of the input traffic and the performance target. For the special case of Gaussian input traffic, these formulas reduce to $c = M + \alpha V$, where directly relates to the performance requirement (as agreed upon in a service level agreement) and $V$ reflects the burstiness (at the timescale of interest). We also observe that Gaussianity applies for virtually all realistic scenarios; notably, already for a relatively low aggregation level, the Gaussianity assumption is justified.\ud As estimating $M$ is relatively straightforward, the remaining open issue concerns the estimation of $V$. We argue that particularly if corresponds to small time-scales, it may be inaccurate to estimate it directly from the traffic traces. Therefore, we propose an indirect method that samples the buffer content, estimates the buffer content distribution, and ‘inverts’ this to the variance. We validate the inversion through extensive numerical experiments (using a sizeable collection of traffic traces from various representative locations); the resulting estimate of $V$ is then inserted in the dimensioning formula. These experiments show that both the inversion and the dimensioning formula are remarkably accurate