Quality of Service Support in PowerLine Communication networks

Colloque avec actes et comité de lecture. internationale.International audiencePLC (PowerLine Communication) is becoming an interesting last mile solution for both in-home and access applications, this mainly due to its ubiquity and continually growing bit rate. However what is its capability to provide QoS guarantees for real-time applications is still an open problem. In this paper, we first analyse the real-time QoS supporting of the two main PLC MAC protocols, then address the performance problem of TCP Westwood over PLC by simulation. This simulation study revealed the impact of the packet loss rate on TCP performance. We also discuss the importance of coordinating TCP's RTT estimation with the ARQ of the underlying PLC MAC protocol

Measuring Research Contributions of Prof. Anurag Kumar: A Scientometric Analysis

The present study aims to measure the contributions of Prof. Anurag Kumar, who served as the Director at the Indian Institute of Science (IISc) in Bengaluru between August 2014 to July 2020. He has contributed 181 publications during his 36 years of career. He has published his majority of publications 171 (94.48%) in collaboration; most active collaborators with Prof. Anurag Kumar are Altman E. with (17) publications, Kuri Joy (15), Anand (14), and Singh (12). His highest Collaboration Coefficient found is 0.73 in 2013, and the highest Modified Collaboration Coefficient is 1.33 in the year 2018. The highest degree of collaboration observed for Prof. Anurag Kumar was 1.00. The highest Collaborative Index of Prof. Anurag found is 4.75 in the year 2016. His publications received 2595 citations so far, with 14.3 citations for each publication and an average citation of 72.08 per year. He has produced most of his publications in the field of computer science (45.9%). He preferred conference papers as his communication channel, where he published 100 (55.24%) papers out of 181. Prof. Anurag Kumar has contributed the highest (62) publication between 2005-2010, and he has published his first publication at the age of 30

Modeling TCP Throughput: an Elaborated Large-Deviations-Based Model and its Empirical Validation *

Abstract In today's Internet, a large part of the traffic is carried using the TCP transport protocol. Characterization of the variations of TCP traffic is thus a major challenge, both for resource provisioning and Quality of Service purposes. However, most existing models are limited to the prediction of the (almost-sure) mean TCP throughput and are unable to characterize deviations from this value. In this paper, we propose a method to describe the deviations of a long TCP flow's throughput from its almost-sure mean value. This method relies on an ergodic large-deviations result, which was recently proved to hold on almost every single realization for a large class of stochastic processes. Applying this result to a Markov chain modeling the congestion window's evolution of a long-lived TCP flow, we show that it is practically possible to quantify and to statistically bound the throughput's variations at different scales of interest for applications. Our Markov-chain model can take into account various network conditions and we demonstrate the accuracy of our method's prediction in different situations using simulations, experiments and real-world Internet traffic. In particular, in the classical case of Bernoulli losses, we demonstrate: i) the consistency of our method with the widely-used square-root formula predicting the almost-sure mean throughput, and ii) its ability to additionally predict finer properties reflecting the traffic variability at different scales

TCP performance over end-to-end rate control and stochastic available capacity

Motivated by TCP over end-to-end ABR, we study the performance of adaptive window congestion control, when it operates over an explicit feedback rate-control mechanism, in a situation in which the bandwidth available to the elastic traffic is stochastically time varying. It is assumed that the sender and receiver of the adaptive window protocol are colocated with the rate-control endpoints. The objective of the study is to understand if the interaction of the rate-control loop and the window-control loop is beneficial for end-to-end throughput, and how the parameters of the problem (propagation delay, bottleneck buffers, and rate of variation of the available bottleneck bandwidth) affect the performance.The available bottleneck bandwidth is modeled as a two-state Markov chain. We develop an analysis that explicitly models the bottleneck buffers, the delayed explicit rate feedback, and TCP's adaptive window mechanism. The analysis, however, applies only when the variations in the available bandwidth occur over periods larger than the round-trip delay. For fast variations of the bottleneck bandwidth, we provide results from a simulation on a TCP testbed that uses Linux TCP code, and a simulation/emulation of the network model inside the Linux kernel.We find that, over end-to-end ABR, the performance of TCP improves significantly if the network bottleneck bandwidth variations are slow as compared to the round-trip propagation delay. Further, we find that TCP over ABR is relatively insensitive to bottleneck buffer size. These results are for a short-term average link capacity feedback at the ABR level (INSTCAP). We use the testbed to study EFFCAP feedback, which is motivated by the notion of the effective capacity of the bottleneck link. We find that EFFCAP feedback is adaptive to the rate of bandwidth variations at the bottleneck link, and thus yields good performance (as compared to INSTCAP) over a wide range of the rate of bottleneck bandwidth variation. Finally, we study if TCP over ABR, with EFFCAP feedback, provides throughput fairness even if the connections have different round-trip propagation delays

The window distribution of multiple TCPs with random loss queues

In this paper, we consider the case of multiple ideal and persistent TCP flows (flows that are assumed to be performing idealized congestion avoidance) interacting with queue management algorithms that perform random drop-based buffer management. Our objective is to determine the stationary congestion window distribution of each of the TCP flows whenthe router port implements algorithms like RED (Random Early Detection)or ERD (Early Random Drop). We first present an analyticaltechnique to obtain the 'mean' queue occupancy and the 'mean' of the individual TCP windows. Armed with this estimate of the means, wethen derive the window distribution of each individual TCPconnection. Extensive simulation experiments indicate that, under a wide variety of operating conditions, our analytical method is quite accurate in predicting the 'mean' as well asthe distributions. The derivation of the individual distributions is based upon a numerical analysis presented which considers the case of a single TCP flow subject to variable state-dependent packet loss

Predicting Bottleneck Bandwidth Sharing by Generalized TCP Flows

The paper presents a technique for computing the individual throughputs and the average queue occupancy when multiple TCP connections share a single bottleneck buffer. The bottleneck buffer is assumed to perform congestion feedback via randomized packet marking or drops. We first present a fixed point-based analytical technique to compute the mean congestion window sizes, the mean queue occupancy and the individual throughputs when the TCP flows perform idealized congestion avoidance. We subsequently extend the technique to analyze the case where TCP flows perform generalized congestion avoidance and demonstrate the use of this technique under the Assured Service model, where each flow is assured a minimum traffic rate. Simulations are used to demonstrate the accuracy of this technique for relatively low values of packet dropping probability and a much wider range of packet marking probability