2,772 research outputs found
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
NETQOS policy management architecture for flexible QOS provisioning in Future Internet
This paper is focussed on the NETQOS architecture for automated QoS policy provisioning, which can be used in Future Internet scenarios by the different actors (i.e. network operators, service providers, and users) for flexible QoS configuration over combinations of mobile, fixed, sensor and broadcast networks. The NETQOS policy management architecture opens the possibility to specify QoS policies on a "business" level using ontology descriptions and policy management interfaces, which are specific to the actors. The business level policy specifications are translated by the NETQOS system into intermediate and operational QoS policies for automated QoS configuration at the managed heterogeneous network and transport entities. NETQOS allows QoS policy specification and dependency analysis considering Service Level Agreements (SLAs) between the actors, as well as automated policy provisioning and adaptation. The interaction of the NETQOS components is based on a common po licy repository. The particular focus of the paper is aimed to discuss ontology and actor oriented QoS policy specification and configuration for heterogeneous networks, as well as NETQOS QoS policy management interfaces at business level and automated translation of business QoS policies to intermediate and operational policy level
Big Data Analytics for QoS Prediction Through Probabilistic Model Checking
As competitiveness increases, being able to guaranting QoS of delivered
services is key for business success. It is thus of paramount importance the
ability to continuously monitor the workflow providing a service and to timely
recognize breaches in the agreed QoS level. The ideal condition would be the
possibility to anticipate, thus predict, a breach and operate to avoid it, or
at least to mitigate its effects. In this paper we propose a model checking
based approach to predict QoS of a formally described process. The continous
model checking is enabled by the usage of a parametrized model of the monitored
system, where the actual value of parameters is continuously evaluated and
updated by means of big data tools. The paper also describes a prototype
implementation of the approach and shows its usage in a case study.Comment: EDCC-2014, BIG4CIP-2014, Big Data Analytics, QoS Prediction, Model
Checking, SLA compliance monitorin
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