MR-BART: Multi-Rate Available Bandwidth Estimation in Real-Time

In this paper, we propose Multi-Rate Bandwidth Available in Real Time (MR-BART) to estimate the end-to-end Available Bandwidth (AB) of a network path. The proposed scheme is an extension of the Bandwidth Available in Real Time (BART) which employs multi-rate (MR) probe packet sequences with Kalman filtering. Comparing to BART, we show that the proposed method is more robust and converges faster than that of BART and achieves a more AB accurate estimation. Furthermore, we analyze the estimation error in MR-BART and obtain analytical formula and empirical expression for the AB estimation error based on the system parameters.Comment: 12 Pages (Two columns), 14 Figures, 4 Tables

SSthreshless Start: A Sender-Side TCP Intelligence for Long Fat Network

Measurement shows that 85% of TCP flows in the internet are short-lived flows that stay most of their operation in the TCP startup phase. However, many previous studies indicate that the traditional TCP Slow Start algorithm does not perform well, especially in long fat networks. Two obvious problems are known to impact the Slow Start performance, which are the blind initial setting of the Slow Start threshold and the aggressive increase of the probing rate during the startup phase regardless of the buffer sizes along the path. Current efforts focusing on tuning the Slow Start threshold and/or probing rate during the startup phase have not been considered very effective, which has prompted an investigation with a different approach. In this paper, we present a novel TCP startup method, called threshold-less slow start or SSthreshless Start, which does not need the Slow Start threshold to operate. Instead, SSthreshless Start uses the backlog status at bottleneck buffer to adaptively adjust probing rate which allows better seizing of the available bandwidth. Comparing to the traditional and other major modified startup methods, our simulation results show that SSthreshless Start achieves significant performance improvement during the startup phase. Moreover, SSthreshless Start scales well with a wide range of buffer size, propagation delay and network bandwidth. Besides, it shows excellent friendliness when operating simultaneously with the currently popular TCP NewReno connections.Comment: 25 pages, 10 figures, 7 table

FAST TCP: Motivation, Architecture, Algorithms, Performance

We describe FAST TCP, a new TCP congestion control algorithm for high-speed long-latency networks, from design to implementation. We highlight the approach taken by FAST TCP to address the four difficulties which the current TCP implementation has at large windows. We describe the architecture and summarize some of the algorithms implemented in our prototype. We characterize its equilibrium and stability properties. We evaluate it experimentally in terms of throughput, fairness, stability, and responsiveness

Congestion Control using FEC for Conversational Multimedia Communication

In this paper, we propose a new rate control algorithm for conversational multimedia flows. In our approach, along with Real-time Transport Protocol (RTP) media packets, we propose sending redundant packets to probe for available bandwidth. These redundant packets are Forward Error Correction (FEC) encoded RTP packets. A straightforward interpretation is that if no losses occur, the sender can increase the sending rate to include the FEC bit rate, and in the case of losses due to congestion the redundant packets help in recovering the lost packets. We also show that by varying the FEC bit rate, the sender is able to conservatively or aggressively probe for available bandwidth. We evaluate our FEC-based Rate Adaptation (FBRA) algorithm in a network simulator and in the real-world and compare it to other congestion control algorithms

EGOIST: Overlay Routing Using Selfish Neighbor Selection

A foundational issue underlying many overlay network applications ranging from routing to P2P file sharing is that of connectivity management, i.e., folding new arrivals into an existing overlay, and re-wiring to cope with changing network conditions. Previous work has considered the problem from two perspectives: devising practical heuristics for specific applications designed to work well in real deployments, and providing abstractions for the underlying problem that are analytically tractable, especially via game-theoretic analysis. In this paper, we unify these two thrusts by using insights gleaned from novel, realistic theoretic models in the design of Egoist – a prototype overlay routing system that we implemented, deployed, and evaluated on PlanetLab. Using measurements on PlanetLab and trace-based simulations, we demonstrate that Egoist's neighbor selection primitives significantly outperform existing heuristics on a variety of performance metrics, including delay, available bandwidth, and node utilization. Moreover, we demonstrate that Egoist is competitive with an optimal, but unscalable full-mesh approach, remains highly effective under significant churn, is robust to cheating, and incurs minimal overhead. Finally, we discuss some of the potential benefits Egoist may offer to applications.National Science Foundation (CISE/CSR 0720604, ENG/EFRI 0735974, CISE/CNS 0524477, CNS/NeTS 0520166, CNS/ITR 0205294; CISE/EIA RI 0202067; CAREER 04446522); European Commission (RIDS-011923