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Communications & Data . Dave Finkleman. 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 ). - PowerPoint PPT Presentation
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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– 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)– 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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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
• 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• 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 high- level 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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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
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ICO CommSat
Representative mission geometry, sensors & links
Full Duplex Comms withInterceptors in Flight
High Altitude Airship
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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
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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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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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Flat routing comparisons
N : # of nodes in the networke : # of communication pairs in the network
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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