Quantizing Radio Link Data Rates to Create Ever-Changing Network Conditions in Tactical Networks

Quantizing Radio Link Data Rates to Create Ever-changing Network Conditions in Tactical Networks

10.36227/techrxiv.12894785 ◽

2020 ◽

Author(s):

Roberto Rigolin F. Lopes ◽

Johannes Loevenich ◽

Paulo H. Rettore ◽

Sharath M. Eswarappa ◽

Peter Sevenich

Keyword(s):

Field Experiments ◽

Time Window ◽

Data Rate ◽

Radio Link ◽

Data Rates ◽

Data Flows ◽

Packet Latency ◽

Tactical Networks ◽

Link Data ◽

And Control

Several sources of randomness can change the radio link data rate at the edge of tactical networks. Simulations and field experiments define these sources of randomness indirectly by choosing the mobility pattern, communication technology, number of nodes, terrain, obstacles and so on. Therefore, the distribution of change in the network conditions is unknown until the experiment is executed. We start with the hypothesis that a model can quantize the network conditions, using a set of states updated within a time window, to define and control the distribution of change in the link data rate before the experiment is executed. The goal is to quantify how much variation in the link data rate a tactical system can handle and how long it takes to resume IP data-flows after link disconnections. Our model includes functions to combine patterns of change together, transforming one pattern into another, jumping between patterns, and creating loops among different patterns of change. We use exemplary patterns to show how the change in the data rate impacts other link metrics, such as latency and jitter. Our hypothesis is verified with experiments using VHF radios over different patterns of change created by our model. We compute the inter-packet latency of three types of IP data-flows (broadcast, unicast and overlay) to highlight the time to resume data-flows after long link disconnections. The experimental results also support the discussion on the advantages and limitations of our model, which was designed to test tactical systems using military radios.

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Quantizing Radio Link Data Rates to Create Ever-changing Network Conditions in Tactical Networks

10.36227/techrxiv.12894785.v1 ◽

2020 ◽

Author(s):

Roberto Rigolin F. Lopes ◽

Johannes Loevenich ◽

Paulo H. Rettore ◽

Sharath M. Eswarappa ◽

Peter Sevenich

Keyword(s):

Field Experiments ◽

Time Window ◽

Data Rate ◽

Radio Link ◽

Data Rates ◽

Data Flows ◽

Packet Latency ◽

Tactical Networks ◽

Link Data ◽

And Control

Several sources of randomness can change the radio link data rate at the edge of tactical networks. Simulations and field experiments define these sources of randomness indirectly by choosing the mobility pattern, communication technology, number of nodes, terrain, obstacles and so on. Therefore, the distribution of change in the network conditions is unknown until the experiment is executed. We start with the hypothesis that a model can quantize the network conditions, using a set of states updated within a time window, to define and control the distribution of change in the link data rate before the experiment is executed. The goal is to quantify how much variation in the link data rate a tactical system can handle and how long it takes to resume IP data-flows after link disconnections. Our model includes functions to combine patterns of change together, transforming one pattern into another, jumping between patterns, and creating loops among different patterns of change. We use exemplary patterns to show how the change in the data rate impacts other link metrics, such as latency and jitter. Our hypothesis is verified with experiments using VHF radios over different patterns of change created by our model. We compute the inter-packet latency of three types of IP data-flows (broadcast, unicast and overlay) to highlight the time to resume data-flows after long link disconnections. The experimental results also support the discussion on the advantages and limitations of our model, which was designed to test tactical systems using military radios.

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Evaluation of IEEE802.15.4g for Environmental Observations

Sensors ◽

10.3390/s18103468 ◽

2018 ◽

Vol 18 (10) ◽

pp. 3468 ◽

Cited By ~ 10

Author(s):

Jonathan Muñoz ◽

Tengfei Chang ◽

Xavier Vilajosana ◽

Thomas Watteyne

Keyword(s):

Low Power ◽

Orthogonal Frequency Division Multiplexing ◽

Urban Environments ◽

Radio Link ◽

Phase Shift Keying ◽

Smart Meters ◽

Data Rates ◽

Reliable Communications ◽

Shift Keying ◽

Smart Agriculture

IEEE802.15.4g is a low-power wireless standard initially designed for Smart Utility Networks, i.e., for connecting smart meters. IEEE802.15.4g operates at sub-GHz frequencies to offer 2–3× longer communication range compared to its 2.4 GHz counterpart. Although the standard offers 3 PHYs (Frequncy Shift Keying, Orthogonal Frequency Division Multiplexing and Offset-Quadrature Phase Shift Keying) with numerous configurations, 2-FSK at 50 kbps is the mandatory and most prevalent radio setting used. This article looks at whether IEEE802.15.4g can be used to provide connectivity for outdoor deployments. We conduct range measurements using the totality of the standard (all modulations with all further parametrization) in the 863–870 MHz band, within four scenarios which we believe cover most low-power wireless outdoor applications: line of sight, smart agriculture, urban canyon, and smart metering. We show that there are radio settings that outperform the “2-FSK at 50 kbps” base setting in terms of range, throughput and reliability. Results show that highly reliable communications with data rates up to 800 kbps can be achieved in urban environments at 540 m between nodes, and the longest useful radio link is obtained at 779 m. We discuss how IEEE802.15.4g can be used for outdoor operation, and reduce the number of repeater nodes that need to be placed compared to a 2.4 GHz solution.

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An adaptive radio link protocol with enhanced data rates for GSM evolution

IEEE Personal Communications ◽

10.1109/98.752788 ◽

1999 ◽

Vol 6 (1) ◽

pp. 54-64 ◽

Cited By ~ 39

Author(s):

R. van Nobelen ◽

N. Seshadri ◽

J. Whitehead ◽

S. Timiri

Keyword(s):

Radio Link ◽

Data Rates ◽

Radio Link Protocol

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Maximizing the Probability of Message Delivery over Ever-changing Communication Scenarios in Tactical Networks

10.36227/techrxiv.13437710 ◽

2020 ◽

Author(s):

Johannes Loevenich ◽

Roberto Rigolin F. Lopes ◽

Paulo H. Rettore ◽

Sharath M. Eswarappa ◽

Peter Sevenich

Keyword(s):

Packet Loss ◽

Data Rate ◽

Transport Protocol ◽

Message Delivery ◽

Optimal Parameters ◽

User Data ◽

Tactical Networks ◽

Link Data ◽

Store And Forward ◽

Ip Packets

This letter introduces a stochastic model to maximize the probability of message delivery over ever-changing communication scenarios in tactical networks. Our model improves modern tactical systems implementing store-and-forward mechanisms organized in a hierarchy of layers for messages, IP packets and radios. The goal is to compute close to optimal parameters for a transport protocol by computing the optimum redundancy for the user data-flow to overcome packet loss during changes in the link data rate, including disconnections. Experiments in a VHF network illustrate the numerical results from our model using messages with different sizes over two patterns of data rate change.

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Maximizing the Probability of Message Delivery over Ever-changing Communication Scenarios in Tactical Networks

10.36227/techrxiv.13437710.v1 ◽

2020 ◽

Author(s):

Johannes Loevenich ◽

Roberto Rigolin F. Lopes ◽

Paulo H. Rettore ◽

Sharath M. Eswarappa ◽

Peter Sevenich

Keyword(s):

Packet Loss ◽

Data Rate ◽

Transport Protocol ◽

Message Delivery ◽

Optimal Parameters ◽

User Data ◽

Tactical Networks ◽

Link Data ◽

Store And Forward ◽

Ip Packets

This letter introduces a stochastic model to maximize the probability of message delivery over ever-changing communication scenarios in tactical networks. Our model improves modern tactical systems implementing store-and-forward mechanisms organized in a hierarchy of layers for messages, IP packets and radios. The goal is to compute close to optimal parameters for a transport protocol by computing the optimum redundancy for the user data-flow to overcome packet loss during changes in the link data rate, including disconnections. Experiments in a VHF network illustrate the numerical results from our model using messages with different sizes over two patterns of data rate change.

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Deploying CPU-Intensive Applications on MEC in NFV Systems: The Immersive Video Use Case

Computers ◽

10.3390/computers7040055 ◽

2018 ◽

Vol 7 (4) ◽

pp. 55 ◽

Cited By ~ 9

Author(s):

Giorgio Cattaneo ◽

Fabio Giust ◽

Claudio Meani ◽

Daniele Munaretto ◽

Pietro Paglierani

Keyword(s):

High Performance ◽

End Users ◽

Network Function Virtualization ◽

Radio Link ◽

Management Level ◽

Network Function ◽

High Data ◽

Data Rates ◽

Multi Access ◽

Over The Top

Multi-access Edge Computing (MEC) will be a technology pillar of forthcoming 5G networks. Nonetheless, there is a great interest in also deploying MEC solutions in current 4G infrastructures. MEC enables data processing in proximity to end users. Thus, latency can be minimized, high data rates locally achieved, and real-time information about radio link status or consumer geographical position exploited to develop high-value services. To consolidate network elements and edge applications on the same virtualization infrastructure, network operators aim to combine MEC with Network Function Virtualization (NFV). However, MEC in NFV integration is not fully established yet: in fact, various architectural issues are currently open, even at standardization level. This paper describes a novel MEC in an NFV system which successfully combines, at management level, MEC functional blocks with an NFV Orchestrator, and can neutrally support any “over the top” Mobile Edge application with minimal integration effort. A specific ME app combined with an end-user app for the provision of immersive video services is presented. To provide low latency, CPU-intensive services to end users, the proposed architecture exploits High-Performance Computing resources embedded in the edge infrastructure. Experimental results showing the effectiveness of the proposed architecture are reported and discussed.

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