5,965 research outputs found
Endpoint-transparent Multipath Transport with Software-defined Networks
Multipath forwarding consists of using multiple paths simultaneously to
transport data over the network. While most such techniques require endpoint
modifications, we investigate how multipath forwarding can be done inside the
network, transparently to endpoint hosts. With such a network-centric approach,
packet reordering becomes a critical issue as it may cause critical performance
degradation.
We present a Software Defined Network architecture which automatically sets
up multipath forwarding, including solutions for reordering and performance
improvement, both at the sending side through multipath scheduling algorithms,
and the receiver side, by resequencing out-of-order packets in a dedicated
in-network buffer.
We implemented a prototype with commonly available technology and evaluated
it in both emulated and real networks. Our results show consistent throughput
improvements, thanks to the use of aggregated path capacity. We give
comparisons to Multipath TCP, where we show our approach can achieve a similar
performance while offering the advantage of endpoint transparency
LTE Spectrum Sharing Research Testbed: Integrated Hardware, Software, Network and Data
This paper presents Virginia Tech's wireless testbed supporting research on
long-term evolution (LTE) signaling and radio frequency (RF) spectrum
coexistence. LTE is continuously refined and new features released. As the
communications contexts for LTE expand, new research problems arise and include
operation in harsh RF signaling environments and coexistence with other radios.
Our testbed provides an integrated research tool for investigating these and
other research problems; it allows analyzing the severity of the problem,
designing and rapidly prototyping solutions, and assessing them with
standard-compliant equipment and test procedures. The modular testbed
integrates general-purpose software-defined radio hardware, LTE-specific test
equipment, RF components, free open-source and commercial LTE software, a
configurable RF network and recorded radar waveform samples. It supports RF
channel emulated and over-the-air radiated modes. The testbed can be remotely
accessed and configured. An RF switching network allows for designing many
different experiments that can involve a variety of real and virtual radios
with support for multiple-input multiple-output (MIMO) antenna operation. We
present the testbed, the research it has enabled and some valuable lessons that
we learned and that may help designing, developing, and operating future
wireless testbeds.Comment: In Proceeding of the 10th ACM International Workshop on Wireless
Network Testbeds, Experimental Evaluation & Characterization (WiNTECH),
Snowbird, Utah, October 201
W-NINE: a two-stage emulation platform for mobile and wireless systems
More and more applications and protocols are now running on wireless networks. Testing the implementation of such applications and protocols is a real challenge as the position of the mobile terminals and environmental effects strongly affect the overall performance. Network emulation is often perceived as a good trade-off between experiments on operational wireless networks and discrete-event simulations on Opnet or ns-2. However, ensuring repeatability and realism in network emulation while taking into account mobility in a wireless environment is very difficult. This paper proposes a network emulation platform, called W-NINE, based on off-line computations preceding online pattern-based traffic shaping. The underlying concepts of repeatability, dynamicity, accuracy and realism are defined in the emulation context. Two different simple case studies illustrate the validity of our approach with respect to these concepts
Network emulation focusing on QoS-Oriented satellite communication
This chapter proposes network emulation basics and a complete case study of QoS-oriented Satellite Communication
Modeling the Internet of Things: a simulation perspective
This paper deals with the problem of properly simulating the Internet of
Things (IoT). Simulating an IoT allows evaluating strategies that can be
employed to deploy smart services over different kinds of territories. However,
the heterogeneity of scenarios seriously complicates this task. This imposes
the use of sophisticated modeling and simulation techniques. We discuss novel
approaches for the provision of scalable simulation scenarios, that enable the
real-time execution of massively populated IoT environments. Attention is given
to novel hybrid and multi-level simulation techniques that, when combined with
agent-based, adaptive Parallel and Distributed Simulation (PADS) approaches,
can provide means to perform highly detailed simulations on demand. To support
this claim, we detail a use case concerned with the simulation of vehicular
transportation systems.Comment: Proceedings of the IEEE 2017 International Conference on High
Performance Computing and Simulation (HPCS 2017
Emulating opportunistic networks with KauNet Triggers
In opportunistic networks the availability of an end-to-end path is no longer required. Instead opportunistic networks may take advantage of temporary connectivity opportunities.
Opportunistic networks present a demanding environment for network emulation as the traditional emulation setup, where application/transport endpoints only send and receive packets from the network following a black box approach,
is no longer applicable. Opportunistic networking protocols
and applications additionally need to react to the dynamics of the underlying network beyond what is conveyed through the exchange of packets.
In order to support IP-level emulation evaluations of applications and protocols that react to lower layer events, we have proposed the use of emulation triggers. Emulation triggers can emulate arbitrary cross-layer feedback and can be synchronized with other emulation effects. After introducing the design and implementation of
triggers in the KauNet emulator, we describe the integration of triggers with the DTN2 reference implementation and illustrate how the functionality can be used to emulate a classical DTN data-mule scenario
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