1,865 research outputs found
TCP in 5G mmWave Networks: Link Level Retransmissions and MP-TCP
MmWave communications, one of the cornerstones of future 5G mobile networks,
are characterized at the same time by a potential multi-gigabit capacity and by
a very dynamic channel, sensitive to blockage, wide fluctuations in the
received signal quality, and possibly also sudden link disruption. While the
performance of physical and MAC layer schemes that address these issues has
been thoroughly investigated in the literature, the complex interactions
between mmWave links and transport layer protocols such as TCP are still
relatively unexplored. This paper uses the ns-3 mmWave module, with its channel
model based on real measurements in New York City, to analyze the performance
of the Linux TCP/IP stack (i) with and without link-layer retransmissions,
showing that they are fundamental to reach a high TCP throughput on mmWave
links and (ii) with Multipath TCP (MP-TCP) over multiple LTE and mmWave links,
illustrating which are the throughput-optimal combinations of secondary paths
and congestion control algorithms in different conditions.Comment: 6 pages, 11 figures, accepted for presentation at the 2017 IEEE
Conference on Computer Communications Workshops (INFOCOM WKSHPS
Predicting expected TCP throughput using genetic algorithm
Predicting the expected throughput of TCP is important for several aspects such as e.g. determining handover criteria for future multihomed mobile nodes or determining the expected throughput of a given MPTCP subflow for load-balancing reasons. However, this is challenging due to time varying behavior of the underlying network characteristics. In this paper, we present a genetic-algorithm-based prediction model for estimating TCP throughput values. Our approach tries to find the best matching combination of mathematical functions that approximate a given time series that accounts for the TCP throughput samples using genetic algorithm. Based on collected historical datapoints about measured TCP throughput samples, our algorithm estimates expected throughput over time. We evaluate the quality of the prediction using different selection and diversity strategies for creating new chromosomes. Also, we explore the use of different fitness functions in order to evaluate the goodness of a chromosome. The goal is to show how different tuning on the genetic algorithm may have an impact on the prediction. Using extensive simulations over several TCP throughput traces, we find that the genetic algorithm successfully finds reasonable matching mathematical functions that allow to describe the TCP sampled throughput values with good fidelity. We also explore the effectiveness of predicting time series throughput samples for a given prediction horizon and estimate the prediction error and confidence.Peer ReviewedPostprint (author's final draft
A novel multipath-transmission supported software defined wireless network architecture
The inflexible management and operation of today\u27s wireless access networks cannot meet the increasingly growing specific requirements, such as high mobility and throughput, service differentiation, and high-level programmability. In this paper, we put forward a novel multipath-transmission supported software-defined wireless network architecture (MP-SDWN), with the aim of achieving seamless handover, throughput enhancement, and flow-level wireless transmission control as well as programmable interfaces. In particular, this research addresses the following issues: 1) for high mobility and throughput, multi-connection virtual access point is proposed to enable multiple transmission paths simultaneously over a set of access points for users and 2) wireless flow transmission rules and programmable interfaces are implemented into mac80211 subsystem to enable service differentiation and flow-level wireless transmission control. Moreover, the efficiency and flexibility of MP-SDWN are demonstrated in the performance evaluations conducted on a 802.11 based-testbed, and the experimental results show that compared to regular WiFi, our proposed MP-SDWN architecture achieves seamless handover and multifold throughput improvement, and supports flow-level wireless transmission control for different applications
Sub-Nanosecond Time of Flight on Commercial Wi-Fi Cards
Time-of-flight, i.e., the time incurred by a signal to travel from
transmitter to receiver, is perhaps the most intuitive way to measure distances
using wireless signals. It is used in major positioning systems such as GPS,
RADAR, and SONAR. However, attempts at using time-of-flight for indoor
localization have failed to deliver acceptable accuracy due to fundamental
limitations in measuring time on Wi-Fi and other RF consumer technologies.
While the research community has developed alternatives for RF-based indoor
localization that do not require time-of-flight, those approaches have their
own limitations that hamper their use in practice. In particular, many existing
approaches need receivers with large antenna arrays while commercial Wi-Fi
nodes have two or three antennas. Other systems require fingerprinting the
environment to create signal maps. More fundamentally, none of these methods
support indoor positioning between a pair of Wi-Fi devices
without~third~party~support.
In this paper, we present a set of algorithms that measure the time-of-flight
to sub-nanosecond accuracy on commercial Wi-Fi cards. We implement these
algorithms and demonstrate a system that achieves accurate device-to-device
localization, i.e. enables a pair of Wi-Fi devices to locate each other without
any support from the infrastructure, not even the location of the access
points.Comment: 14 page
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