Communications & Data
Dave Finkleman
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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
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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
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Dynamic and often unpredictable network tolopogy
Variable capacity, often congested, bandwidth limited links
Energy and power constrained
Low physical security
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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
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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
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OSI framework: MANET
• Open Systems Interconnect (OSI)
• Physical layer (the environment)
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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)
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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)
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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
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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
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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
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Routing issues
• Poor collision detection
• Incoming signals weaker than transmissions
• Acknowledgements (or lack of), latent
– Potentially leading to unnecessary retransmission
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Hidden terminal
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Exposed terminal
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Exposed terminal
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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
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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
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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
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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
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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
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Measures of performance
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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)
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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
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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
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M&S selection criteria
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
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M&S selection criteria
8. Flexibility and Scalability
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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
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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)
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Major modeling candidates
• 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
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Major modeling candidates
• 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 highlevel system designs
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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
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Analysis approach
Dynamic Comm Paths,
Latency, LOS,
Doppler Histories
STK,STK-COMM
STK-V0, STAMP (MFT)
Aggregated latencies &
network performance
OPNET,
OPNET Modeler
Co-simulation,
hardware in the loop,
advanced waveforms
New or advanced
routing, network discovery,
protocols & latencytolerant techniques
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Application of Existing
Mobile Ad-Hoc Networking
Techniques
Dynamic Comm Paths,
Latency, LOS,
Doppler Histories
STK-OPNET
Object exchange
STK-OPNET
Co-simulation
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Representative mission geometry,
sensors & links
ICO CommSat
High Altitude Airship
Full Duplex Comms with
Interceptors in Flight
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Initial Defensive Operations (IDO)
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Active links with interceptor
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Raw accesses to interceptor
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Doppler histories & free space
losses
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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
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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
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OPNET: Interceptor communications
• “Wired” links
• Protocol tailoring
• Node processing &
buffering
• Error correction schemes
• Network performance
capability vs. realized
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OPNET: Interceptor communications
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Missile defense comms
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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
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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
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BACKUPS
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Flat routing comparisons
N : # of nodes in the network
e : # of communication pairs in the network
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Hierarchical routing comparison
N : # of nodes in the network
M : average # of nodes in a cluster
e : # of communication pairs in the network
H : # of logical levels
L : average # of nodes in a logical group
G : # of logical groups in the network
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Location-assisted
routing comparisons
• N = # of nodes in the
network
• e = # of communication
pairs in the network
• M = Average # of nodes in
a cluster
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