997 research outputs found
Q-AIMD: A Congestion Aware Video Quality Control Mechanism
Following the constant increase of the multimedia traffic, it seems necessary to allow transport protocols to be aware of the video quality of the transmitted flows rather than the throughput. This paper proposes a novel transport mechanism adapted to video flows. Our proposal, called Q-AIMD for video quality AIMD (Additive Increase Multiplicative Decrease), enables fairness in video quality while transmitting multiple video flows. Targeting video quality fairness allows improving the overall video quality for all transmitted flows, especially when the transmitted videos provide various types of content with different spatial resolutions. In addition, Q-AIMD mitigates the occurrence of network congestion events, and dissolves the congestion whenever it occurs by decreasing the video quality and hence the bitrate. Using different video quality metrics, Q-AIMD is evaluated with different video contents and spatial resolutions. Simulation results show that Q-AIMD allows an improved overall video quality among the multiple transmitted video flows compared to a throughput-based congestion control by decreasing significantly the quality discrepancy between them
Evaluation Study for Delay and Link Utilization with the New-Additive Increase Multiplicative Decrease Congestion Avoidance and Control Algorithm
As the Internet becomes increasingly heterogeneous, the issue of congestion
avoidance and control becomes ever more important. And the queue length,
end-to-end delays and link utilization is some of the important things in term
of congestion avoidance and control mechanisms. In this work we continue to
study the performances of the New-AIMD (Additive Increase Multiplicative
Decrease) mechanism as one of the core protocols for TCP congestion avoidance
and control algorithm, we want to evaluate the effect of using the AIMD
algorithm after developing it to find a new approach, as we called it the
New-AIMD algorithm to measure the Queue length, delay and bottleneck link
utilization, and use the NCTUns simulator to get the results after make the
modification for the mechanism. And we will use the Droptail mechanism as the
active queue management mechanism (AQM) in the bottleneck router. After
implementation of our new approach with different number of flows, we expect
the delay will less when we measure the delay dependent on the throughput for
all the system, and also we expect to get end-to-end delay less. And we will
measure the second type of delay a (queuing delay), as we shown in the figure 1
bellow. Also we will measure the bottleneck link utilization, and we expect to
get high utilization for bottleneck link with using this mechanism, and avoid
the collisions in the link
Distributed Rate Allocation Policies for Multi-Homed Video Streaming over Heterogeneous Access Networks
We consider the problem of rate allocation among multiple simultaneous video
streams sharing multiple heterogeneous access networks. We develop and evaluate
an analytical framework for optimal rate allocation based on observed available
bit rate (ABR) and round-trip time (RTT) over each access network and video
distortion-rate (DR) characteristics. The rate allocation is formulated as a
convex optimization problem that minimizes the total expected distortion of all
video streams. We present a distributed approximation of its solution and
compare its performance against H-infinity optimal control and two heuristic
schemes based on TCP-style additive-increase-multiplicative decrease (AIMD)
principles. The various rate allocation schemes are evaluated in simulations of
multiple high-definition (HD) video streams sharing multiple access networks.
Our results demonstrate that, in comparison with heuristic AIMD-based schemes,
both media-aware allocation and H-infinity optimal control benefit from
proactive congestion avoidance and reduce the average packet loss rate from 45%
to below 2%. Improvement in average received video quality ranges between 1.5
to 10.7 dB in PSNR for various background traffic loads and video playout
deadlines. Media-aware allocation further exploits its knowledge of the video
DR characteristics to achieve a more balanced video quality among all streams.Comment: 12 pages, 22 figure
STAIR: Practical AIMD Multirate Congestion Control
Existing approaches for multirate multicast congestion control are either friendly to TCP only over large time scales or introduce unfortunate side effects, such as significant control traffic, wasted bandwidth, or the need for modifications to existing routers. We advocate a layered multicast approach in which steady-state receiver reception rates emulate the classical TCP sawtooth derived from additive-increase, multiplicative decrease (AIMD) principles. Our approach introduces the concept of dynamic stair layers to simulate various rates of additive increase for receivers with heterogeneous round-trip times (RTTs), facilitated by a minimal amount of IGMP control traffic. We employ a mix of cumulative and non-cumulative layering to minimize the amount of excess bandwidth consumed by receivers operating asynchronously behind a shared bottleneck. We integrate these techniques together into a congestion control scheme called STAIR which is amenable to those multicast applications which can make effective use of arbitrary and time-varying subscription levels.National Science Foundation (CAREER ANI-0093296, ANI-9986397
Design and analysis for TCP-friendly window-based congestion control
The current congestion control mechanisms for the Internet date back to the early 1980’s and were
primarily designed to stop congestion collapse with the typical traffic of that era. In recent years the
amount of traffic generated by real-time multimedia applications has substantially increased, and the
existing congestion control often does not opt to those types of applications. By this reason, the Internet
can be fall into a uncontrolled system such that the overall throughput oscillates too much by a single
flow which in turn can lead a poor application performance. Apart from the network level concerns,
those types of applications greatly care of end-to-end delay and smoother throughput in which the
conventional congestion control schemes do not suit. In this research, we will investigate improving the
state of congestion control for real-time and interactive multimedia applications. The focus of this work
is to provide fairness among applications using different types of congestion control mechanisms to get
a better link utilization, and to achieve smoother and predictable throughput with suitable end-to-end
packet delay
Smart Procurement of Naturally Generated Energy (SPONGE) for Plug-in Hybrid Electric Buses
We discuss a recently introduced ECO-driving concept known as SPONGE in the
context of Plug-in Hybrid Electric Buses (PHEB)'s.Examples are given to
illustrate the benefits of this approach to ECO-driving. Finally, distributed
algorithms to realise SPONGE are discussed, paying attention to the privacy
implications of the underlying optimisation problems.Comment: This paper is recently submitted to the IEEE Transactions on
Automation Science and Engineerin
Reducing Congestion Effects by Multipath Routing in Wireless Networks
We propose a solution to improve fairness and increasethroughput in wireless networks with location information.Our approach consists of a multipath routing protocol, BiasedGeographical Routing (BGR), and two congestion controlalgorithms, In-Network Packet Scatter (IPS) and End-to-EndPacket Scatter (EPS), which leverage BGR to avoid the congestedareas of the network. BGR achieves good performancewhile incurring a communication overhead of just 1 byte perdata packet, and has a computational complexity similar togreedy geographic routing. IPS alleviates transient congestion bysplitting traffic immediately before the congested areas. In contrast,EPS alleviates long term congestion by splitting the flow atthe source, and performing rate control. EPS selects the pathsdynamically, and uses a less aggressive congestion controlmechanism on non-greedy paths to improve energy efficiency.Simulation and experimental results show that our solutionachieves its objectives. Extensive ns-2 simulations show that oursolution improves both fairness and throughput as compared tosingle path greedy routing. Our solution reduces the variance ofthroughput across all flows by 35%, reduction which is mainlyachieved by increasing throughput of long-range flows witharound 70%. Furthermore, overall network throughput increasesby approximately 10%. Experimental results on a 50-node testbed are consistent with our simulation results, suggestingthat BGR is effective in practice
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