communications & data

Pg 1 of xxAGI www agi com

Communications & Data

Dave Finkleman

Pg 2 of 40AGI www agi com

Overview

• Introduction to Mobile ad-hoc Networking– OSI Layers– Routing– Disruptive Phenomena

• Model Selection– Physical Layer– Link, Network, and Transport Layers

• Missile Defense communication example• Conclusion


Mobile ad-hoc networking (MANET)

• Self-organizing networks of – Dynamically mobile elements– With equal technical ability– Independent of fixed infrastructure or centralized control

• General characteristics– Dynamic and often unpredictable network tolopogy– Variable capacity, often congested, bandwidth limited links– Energy and power constrained– Low physical security


Desirable capabilities

• Scalable– From few widely distributed elements through

multitudes of dense, randomly mobile elements– 802.11 is not scalable (10 nodes, 300 meters)– Bluetooth is neither scalable nor true MANET

• Master-slave relationship• 100 meter range


Desirable capabilities

• Mobile elements with static infrastructure (cellular, WAN, LAN) and fixed infrastructure networks (Internet)

• Spectrum of route discovery and route maintenance schemes

• Data link layer operation with a variety of embedded network and transport layer protocols


OSI framework: MANET

• Open Systems Interconnect (OSI)

• Physical layer (the environment)– Environment must be able to support communications– Channel loss (obstructions, atmospherics)– Interference– Mechanical and physical incompatibilities

• Data link layer (the road map)– Must establish pathways within the communications medium – Make physical links consistent (MAC)


OSI framework: MANET

• Network layer (the route)– Must accommodate changes in topology and discover

routes (IP)

• Transport layer (the traveler following the route)– Must match delay and dropout characteristics to

sustain reliable communication

• Application layer – Must be able to handle frequent and unanticipated

disconnections (HLA)


Routing focus

• Minimizing routing overhead• Control packets consume bandwidth

• Minimizing delays– Links break and make randomly, interrupting ongoing

communication

• Optimizing paths– Many approaches sacrifice route optimization in order

to diminish overhead and delays

High altitude platforms can address all of these concerns


Routing focus

• Preventing loops– Keeping route discovery from looping back on itself

• Minimizing computational effort and storage– Route discovery and maintenance require complex logic and

significant router memory

• Scaling– Bandwidth and overhead can be totally consumed by internal

route discovery and maintenance – Especially if every node maintains real time routing tables for

every other node

High altitude platforms can address all of these concerns


Routing issues

• Location-dependent carrier sensing– Carrier sensing performed at transmitter - most influenced by

phenomena near receiver

– Hidden terminals:

• Node out of range of sender but within range of receiver

• Communication between the receiver & hidden node burdens channel

– Exposed terminals:

• Node within range of sender / out of range of receiver

• Transmissions from exposed node deceive sender

– Channel is occupied


Routing issues

• Poor collision detection• Incoming signals weaker than transmissions• Acknowledgements (or lack of), latent

– Potentially leading to unnecessary retransmission


Hidden terminal

ATL Composite Control


Exposed terminal



Mitigating routing issues

• Link layer protocol approaches– Proactive: regularly scheduled route discovery– Reactive: route discovery in response to link loss

• Architectural approaches– Flat: all nodes equal– Hierarchical: some nodes elected or designated for special

functionality

• Hybrid approaches– Some proactive, some reactive– Some flat, some hierarchical


Fixed & ad-hoc routing

• Fixed networks: exploit static routing tables– Distance vector: “shortest” path– Link state: avoid contention and broken links

Bellman-Ford: In any graph there exists a spanning tree, a set of

arcs that visits every node exactly once


Fixed & ad-hoc routing

• ad-hoc network analogies– Distance vector

• ad-hoc on demand distance vector (AODV) (reactive/flat)• Dynamic source routing (DSR) (reactive/flat)

– Link state• Optimized link state routing (OLSR) (proactive/flat)

Ad-hoc networks require a richer routing scheme


High altitude platform advantages

• Ability to reach widely distributed inter-cluster nodes

• No hidden or exposed nodes– Potentially all hybrid inter-cluster nodes visible

• Ability to assist geographically aided intra-cluster routing– GPS enabling such as cell phones use, for example,

potentially half duplex may be sufficient


High-altitude platform advantages

• Availability of sufficient power and processing – Accommodates techniques whose overhead or energy

requirements would swamp most mobile nodes

MANET characteristics are not compromised, since

The platform is not acting as a central controller


Measures of performance

• Network size (number of nodes)• Network density• Network capacity• Connectivity structure (number of neighbors)• Mobility pattern (speed, range, …)• Link bandwidth• Traffic pattern (packet size, type of traffic, …)• Link characteristics (bidirectional, unidirectional)• Transmission medium (single vs multi-channel)


Modeling and simulation

• OPNET-STK Example

• Simulation configuration– Clusters

• Land Vehicles with TBRPF and WRP (few, modest mobility)• Aircraft Cluster with AODV and DSR (few, high mobility

– Inter-Cluster• Enabled by HAA• Realizations with ZRP and DREAM for comparison

• Tradeoffs– Efficiency (hop count) and other measures of performance– Compare combinations of two element alternatives above


M&S selection criteria

1. Represent at least four lower OSI layers (1-4)

2. Represent discrete events

3. Represent highly non-linear complex systems• Capable of broad statistical analysis and Monte Carlo

4. Represent wireless interface from emission through propagation to reception • Encompasses antenna placement & characteristics,

refraction, diffraction, absorption, & scattering



5.Represent mission environment including mobility characteristics of potential nodes & other matters affecting data exchange

6.Represent diversity of land, sea, air, near-space, space nodes & platforms

7.Generate or accept data traffic from missile defense mission & other subscribers



8. Flexibility and Scalability• Expansion to arbitrary numbers of distributed, nodes• open and modular software design

9. Ease of use for the purpose intended

10.Cost-modeling & simulation must fit the resources allocated to project


Major modeling candidates

• Network Simulation/Parallel-Distributed Network Sim: Discrete event simulator targeted at networking research (public domain)

• Dynamic Network Emulation Backplane Project: Brings multiple network simulators together in single experiment

• GloMoSim/Parsec: Scaleable, discrete event, network simulation. Library for the Parallel Simulation Environment for Complex Systems (PARSEC) parallel, discrete event, simulation language (public domain)



• QualNet: Derived from GloMoSim. Well-supported & maintained COTS product

• SSF (Scalable Simulation Framework): Includes SSF Network Models (SSFNet), with "open-source Java models of protocols, network elements, & assorted support classes for realistic multi-protocol, multi-domain Internet modeling & simulation

• Dartmouth SSF (DaSSF): Process-oriented, conservatively synchronized parallel simulator

http://www.ssfnet.org/exchangePage.html



• OMNet++: Component-based, simulation package suitable for traffic modeling, protocol analysis & evaluating complex software systems.

• OPNET: Leading commercial network simulator, including "library of detailed protocol and application models. Widely used to diagnose performance of real-world networks & adjust or reconfigure them.

• MLDesigner (MLD): Integrated platform for modeling & analyzing architecture, function & performance of high- level system designs


Physical layer modeling

• Real world events require more than descriptions of interconnects

• Models & simulations of physics & dynamics of executing missions evolve actions that enable “event driven” network models & simulations

• Only two enterprises support the needs of this effort well: – FreeFlyer, produced by AI Solutions,

• COTS suite that supports the entire specific mission operations lifecycles

– Satellite ToolKit (STK), produced by Analytical Graphics, Inc• STK can evaluate complex in-view relationships among dynamic

space, air, land and sea objects instantiated in great physical detail


Co-simulation, hardware in the loop,advanced waveforms

STK-OPNET

Co-simulation

STK-OPNET

Object exchange

OPNET,

OPNET Modeler

STK,STK-COMM

STK-V0, STAMP (MFT)

Analysis approach

Dynamic Comm Paths,Latency, LOS,

Doppler Histories Aggregated latencies &network performance

Dynamic Comm Paths,Latency, LOS,

Doppler Histories

Application of ExistingMobile Ad-Hoc Networking

Techniques

New or advancedrouting, network discovery,

protocols & latency- tolerant techniques


ICO CommSat

Representative mission geometry, sensors & links

Full Duplex Comms withInterceptors in Flight

High Altitude Airship


Initial Defensive Operations (IDO)


Active links with interceptor


Raw accesses to interceptor


Doppler histories & free space losses

• Approx. 30 db less path loss than to lowest accessible commsat• More favorable physical geometry than to geo comsats• More manageable two-way doppler variations


OPNET analysis

• Modulation scheme driven by Doppler dynamics• Network discovery & routing driven by node

mobility & nomadicity• Protocols driven by required latency, reliability &

security• Implementation driven by device envelope, power

generation & thermal management, mechanics or electronics of beam formation & steering


OPNET: Interceptor communications

• “Wired” links

• Protocol tailoring

• Node processing & buffering

• Error correction schemes

• Network performance capability vs. realized


OPNET: Interceptor communications


Missile defense comms



Conclusion

• STK facilitates analysis of modern mobile ad-hoc networking– “Mobile Networking with Strong Physical Layer Interactions”

• Physical phenomena occur on time scales comparable to, or less than, network transactions

– Hypervelocity vehicles (including satellites)– Interplanetary missions

• STK matched with “wired” network simulations – Event-driven– Physical-world “frozen” during network transactions (OPNET)

• Efficiently and uniquely suited for wireless, mobile, ad-hoc networks – We have demonstrated significance of intimate interactions

among lower-four OSI layers


Summary

• Introduction to mobile, ad-hoc, networking– OSI layers– Routing– Disruptive phenomena

• Model selection– Physical layer– Link, network & transport layers

• Missile defense communication example• Conclusion

Pg 41 of xxAGI www agi com

BACKUPS


Flat routing comparisons

N : # of nodes in the networke : # of communication pairs in the network


Hierarchical routing comparison

N : # of nodes in the networke : # of communication pairs in the network

M : average # of nodes in a clusterH : # of logical levels

L : average # of nodes in a logical group

G : # of logical groups in the network


Location-assistedrouting comparisons

• N = # of nodes in the network

• e = # of communication pairs in the network

• M = Average # of nodes in a cluster

communications & data

Documents