Hybrid Mesh Networking for Distributed Operations

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Hybrid Mesh Networking for Distributed Operations LT M.S. Maupin, USN OpTech East Tokyo, Japan 01 December 2015

Transcript of Hybrid Mesh Networking for Distributed Operations

Page 1: Hybrid Mesh Networking for Distributed Operations

Hybrid Mesh Networking forDistributed Operations

LT M.S. Maupin, USN

OpTech EastTokyo, Japan

01 December 2015

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Overview

• Distributed Operations– Motivation– Dispersed littoral operations– Distributed mesh network operations

• Mesh Networking– Network topologies– Fundamentals– Technologies

• Field Experimentation– NMIOTC Crete 2015– SF Bay 2015

• Tactical Implications– Enhancing distributed ops

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Motivation: Distributed Operations

• Give operational commanders options to employ navalforces in any anti-access/area-denial (A2/AD)environment.– Improve offensive capabilities– Develop new CONOPs, doctrine and tactics– Seek out innovative methods for employing forces

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Distributed operations are a complex operating model requiringinnovative approaches to Command and Control (C2).

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Distributed Littoral Operations

• Littorals are among the most challenging and complexenvironments for disaggregated or dispersed operations– Inherently joint/combined– Congested RF spectrum– Diverse terrain features– Dense commercial and maritime traffic

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Distributed Mesh Network Operations

GW

GIG

GW

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Hybrid Mesh Networks

• Leverage existing infrastructure toenable reachback– GIG access through shore 4G/cellular

networks or legacy satcom systems– Mesh-network-over-IP WAN to seamlessly

connect distributed operating elementsacross geographic areas

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• Highly mobile, high-bandwidth data, video and voicecommunications

• Self-forming, self-healing, scalable peer-to-peer networks• Connectivity across disparate networks

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Network Topologies

Wireless Mesh Network (WMN) are multi-hop peer-to-peer wireless network in whichnodes connect with redundant interconnections and cooperate with one another toroute packets.

Full mesh: each node isdirectly connected to allother nodes.

Partial mesh: not allnodes are directlyconnected.

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Layer 2 Connectivity

• The entire wirelessmesh cloud becomesone (giant) ethernetswitch– Perfect for short-term and

opportunistic/delay-tolerant networks

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InternetInternet

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Mesh Network Modeling

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Technologies - Wave Relay

Man Portable Units (Quad Radio & MPU4)Peer-to-Peer MANET

• Proprietary Wave Relay Layer 2 Routing• Simultaneously support voice, video streaming, IP data, PLI

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WR Frequency Range WR Output Power907-922 MHz 27dBm/500mW

2312-2507 MHz 28dBm/600mW2412-2462 MHz 28dBm/600mW

5180-5320, 5500-5700, 5745-5825 MHz 28dBm/600mW2312-2507 MHz 33dBm/2W*1352-1387 MHz 27dBm/500mW4400-4800 MHz 25dBm/320mW4800-4985 MHz 26dBm/400mW

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Technologies - TrellisWare

TW-225 CheetahNet MiniInfrastructure-less MANET

• Dynamic Network Architecture at MAC layer and above• Barrage Network Relay• Simultaneously support voice, video streaming, IP data, PLI

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Technologies - Harris

Highband Networking Radio(HNRv2)

ATH or OTM mesh networking• Dynamic Network Architecture at MAC

layer and above• 802.11g OFDM physical layer• Black or colorless ad-hoc network

backbone• ATO

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Recent NPS Research

• CENETIX– WMD-ISR– MIO and SSE operations

• Crete 2015– MIO/CWMD SA sharing in littorals

• SF Bay 2015– CWMD SA sharing and C2 in littorals– Mesh network management decision support

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NMIOTC Crete 2015

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SF Bay 2015

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SF Bay 2015 - CodeMettle

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• CodeMettle Network Service Orchestrator– Unified network management dashboard

• Experiment support– Centralized awareness and management

• Geo-Positioning• IP traffic performance• Visualize dynamic tactical mesh topologies

– High-level results• Detect tactical network failure in real time• Analyze application failure to hardware vs network

– Post-experiment• Provide historical experiment events for research

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SF Bay 2015 - CodeMettle

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Geographic Traffic

Network latency (low indicatedserver issue not network)

Nodes

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CENETIX Backbone: Node health, traffic and quality

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Live geo-tracking withmouse over health and

signal

Traffic utilizationby node

Node neighbor andsignal quality

Node details

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Tactical Mesh: Geo-Position, IP traffic, Radio quality

SF Bay 2015 - CodeMettle

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Enhancing Distributed Littoral Operations

• Rapid deployability• Quick adaptation to dynamic environment• Tactical-level resilient connectivity for localized battlespace

awareness• Lower probability of interception/detection

– Directional antennas– “Smart” physical layer (e.g. beam-steering,

transmit power optimization, etc.)• Improve interoperability

– Ship-to-shore movement– Surface Action Group operations– Allies and partners

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Enhancing Distributed Littoral Operations (cont)

• Strengthen mesh using deployable sensor networks andunmanned systems (UxVs)

• Improve UxV C2 ecosystem– Robust control and data links– Expand network with UxV nodes

• Reduce reliance on overhead assets– Soft GPS trilateration in denied environments

• Flexibility to integrate legacy and next-generation networkingconcepts (e.g. optronics, projectile-based networks, cubesat,etc.)

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Questions

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Backup Slides

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MIO-JIFX 2014 BT Experimentation

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Network Management

• Monitor the “health” ofthe network

• Determine whenintervention is required

• Detect problems– Equipment failures (often

hidden by the self-repairfeature of the network)

– Intruders• Manage the system

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Network-on-Target 2006

Bordetsky, A. and Bourakov, E. (2006) Network on Target: Remotely Configured Adaptive Tactical Networks. 11th International Command and ControlResearch and Technology Symposium (ICCRTS), June 20-22, 2006, San Diego, CA. Naval Postgraduate School.12/4/2015 25

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CAVR 2008

Figure 3: Track Plot from Collaborative MIO Experiment

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Grid Y (East) [meters]

Grid

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Path Plot from 02/07/08 at 09:13:02

WaypointsSeaFox TrackTarget EstimateBegin ScanEagle TargetingStart PointScanEagle SPOI

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SeaFox

Center for Autonomous Vehicle Research (2006) Network on Target: Remotely Configured Adaptive Tactical Networks. 11th International Command andControl Research and Technology Symposium (ICCRTS), June 20-22, 2006, San Diego, CA. Naval Postgraduate School.12/4/2015 26

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Abstraction

• Users + routers = nodes• Nodes have two functions:

– Generate/terminate traffic– Route traffic for other nodes

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Gateway

1

InternetInternet

Gateway 2

+ =

Gateway

1

InternetInternet

Gateway 2

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Routing – Cross-Layer Design

• Routing – Physical– Link quality feedback is

shown often to help inselecting stable, highbandwidth, low errorrate routes.

– Fading signal strengthcan signal a link aboutto fail → preemptiveroute requests.

– Cross-layer designessential for systemswith smart antennas.

• Routing – MAC– Feedback on link loads

can avoid congestedlinks → enables loadbalancing.

– Channel assignmentand routing depend oneach other.

– MAC detection of newneighbors and failedroutes may significantlyimprove performanceat routing layer.

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Routing – Cross-Layer Design (cont)

• Routing – Transport• Choosing routes with

low error rates mayimprove TCPthroughput.

• Especially importantwhen multiple routesare used

• Freezing TCP when aroute fails.

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• Routing – Application• Especially with respect of

satisfying QoSconstraints

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