3,717 research outputs found
QoE-Based Low-Delay Live Streaming Using Throughput Predictions
Recently, HTTP-based adaptive streaming has become the de facto standard for
video streaming over the Internet. It allows clients to dynamically adapt media
characteristics to network conditions in order to ensure a high quality of
experience, that is, minimize playback interruptions, while maximizing video
quality at a reasonable level of quality changes. In the case of live
streaming, this task becomes particularly challenging due to the latency
constraints. The challenge further increases if a client uses a wireless
network, where the throughput is subject to considerable fluctuations.
Consequently, live streams often exhibit latencies of up to 30 seconds. In the
present work, we introduce an adaptation algorithm for HTTP-based live
streaming called LOLYPOP (Low-Latency Prediction-Based Adaptation) that is
designed to operate with a transport latency of few seconds. To reach this
goal, LOLYPOP leverages TCP throughput predictions on multiple time scales,
from 1 to 10 seconds, along with an estimate of the prediction error
distribution. In addition to satisfying the latency constraint, the algorithm
heuristically maximizes the quality of experience by maximizing the average
video quality as a function of the number of skipped segments and quality
transitions. In order to select an efficient prediction method, we studied the
performance of several time series prediction methods in IEEE 802.11 wireless
access networks. We evaluated LOLYPOP under a large set of experimental
conditions limiting the transport latency to 3 seconds, against a
state-of-the-art adaptation algorithm from the literature, called FESTIVE. We
observed that the average video quality is by up to a factor of 3 higher than
with FESTIVE. We also observed that LOLYPOP is able to reach a broader region
in the quality of experience space, and thus it is better adjustable to the
user profile or service provider requirements.Comment: Technical Report TKN-16-001, Telecommunication Networks Group,
Technische Universitaet Berlin. This TR updated TR TKN-15-00
Accurate non-intrusive residual bandwidth estimation in WMNs
The multi-access scheme of 802.11 wireless networks imposes difficulties in achieving predictable service quality in multi-hop networks. In such networks, the residual capacity of wireless links should be estimated for resource allocation services such as flow admission control. In this paper, we propose an accurate and non-intrusive method to estimate the residual bandwidth of an 802.11 link. Inputs from neighboring network activity measurements and from a basic collision detection mechanism are fed to the analytical model so that the proposed algorithm calculates the maximum allowable traffic level for this link. We evaluate the efficiency of the method via OPNET simulations, and show that the percent estimation error is significantly lower than two other prominent estimation methods, bounded only between 2.5-7.5%. We also demonstrate that flow admission control is successfully achieved in a realistic WMN scenario. Flow control through our proposed algorithm keeps the unsatisfied traffic demand bounded and at a negligibly low level, which is less than an order of magnitude of the other two methods
Is Our Model for Contention Resolution Wrong?
Randomized binary exponential backoff (BEB) is a popular algorithm for
coordinating access to a shared channel. With an operational history exceeding
four decades, BEB is currently an important component of several wireless
standards. Despite this track record, prior theoretical results indicate that
under bursty traffic (1) BEB yields poor makespan and (2) superior algorithms
are possible. To date, the degree to which these findings manifest in practice
has not been resolved.
To address this issue, we examine one of the strongest cases against BEB:
packets that simultaneously begin contending for the wireless channel. Using
Network Simulator 3, we compare against more recent algorithms that are
inspired by BEB, but whose makespan guarantees are superior. Surprisingly, we
discover that these newer algorithms significantly underperform. Through
further investigation, we identify as the culprit a flawed but common
abstraction regarding the cost of collisions. Our experimental results are
complemented by analytical arguments that the number of collisions -- and not
solely makespan -- is an important metric to optimize. We believe that these
findings have implications for the design of contention-resolution algorithms.Comment: Accepted to the 29th ACM Symposium on Parallelism in Algorithms and
Architectures (SPAA 2017
Approaching Optimal Centralized Scheduling with CSMA-based Random Access over Fading Channels
Carrier Sense Multiple Access (CSMA) based distributed algorithms can attain
the largest capacity region as the centralized Max-Weight policy does. Despite
their capability of achieving throughput-optimality, these algorithms can
either incur large delay and have large complexity or only operate over
non-fading channels. In this letter, by assuming arbitrary back-off time we
first propose a fully distributed randomized algorithm whose performance can be
pushed to the performance of the centralized Max-Weight policy not only in
terms of throughput but also in terms of delay for completely-connected
interference networks with fading channels. Then, inspired by the proposed
algorithm we introduce an implementable distributed algorithm for practical
networks with a reservation scheme. We show that the proposed practical
algorithm can still achieve the performance of the centralized Max-Weight
policy.Comment: accepted to IEEE Communications Letter
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
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