27,016 research outputs found
Distributed QoS Guarantees for Realtime Traffic in Ad Hoc Networks
In this paper, we propose a new cross-layer framework, named QPART ( QoS br>rotocol for Adhoc Realtime Traffic), which provides QoS guarantees to real-time multimedia applications for wireless ad hoc networks. By adapting the contention window sizes at the MAC layer, QPART schedules packets of flows according to their unique QoS requirements. QPART implements priority-based admission control and conflict resolution to ensure that the requirements of admitted realtime flows is smaller than the network capacity. The novelty of QPART is that it is robust to mobility and variances in channel capacity and imposes no control message overhead on the network
Experimental Evaluation of Large Scale WiFi Multicast Rate Control
WiFi multicast to very large groups has gained attention as a solution for
multimedia delivery in crowded areas. Yet, most recently proposed schemes do
not provide performance guarantees and none have been tested at scale. To
address the issue of providing high multicast throughput with performance
guarantees, we present the design and experimental evaluation of the Multicast
Dynamic Rate Adaptation (MuDRA) algorithm. MuDRA balances fast adaptation to
channel conditions and stability, which is essential for multimedia
applications. MuDRA relies on feedback from some nodes collected via a
light-weight protocol and dynamically adjusts the rate adaptation response
time. Our experimental evaluation of MuDRA on the ORBIT testbed with over 150
nodes shows that MuDRA outperforms other schemes and supports high throughput
multicast flows to hundreds of receivers while meeting quality requirements.
MuDRA can support multiple high quality video streams, where 90% of the nodes
report excellent or very good video quality
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
CapEst: A Measurement-based Approach to Estimating Link Capacity in Wireless Networks
Estimating link capacity in a wireless network is a complex task because the
available capacity at a link is a function of not only the current arrival rate
at that link, but also of the arrival rate at links which interfere with that
link as well as of the nature of interference between these links. Models which
accurately characterize this dependence are either too computationally complex
to be useful or lack accuracy. Further, they have a high implementation
overhead and make restrictive assumptions, which makes them inapplicable to
real networks.
In this paper, we propose CapEst, a general, simple yet accurate,
measurement-based approach to estimating link capacity in a wireless network.
To be computationally light, CapEst allows inaccuracy in estimation; however,
using measurements, it can correct this inaccuracy in an iterative fashion and
converge to the correct estimate. Our evaluation shows that CapEst always
converged to within 5% of the correct value in less than 18 iterations. CapEst
is model-independent, hence, is applicable to any MAC/PHY layer and works with
auto-rate adaptation. Moreover, it has a low implementation overhead, can be
used with any application which requires an estimate of residual capacity on a
wireless link and can be implemented completely at the network layer without
any support from the underlying chipset
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