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Sharp Hybrid Adaptive Routing Protocol for Mobile Ad Hoc Networks. Venugopalan Ramasubramanian (Rama) Zygmunt Haas Emin G ü n Sirer Cornell University. reactive on-demand routing enables overhead to scale with data traffic performance significantly affected by mobility. introduction.

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sharp hybrid adaptive routing protocol for mobile ad hoc networks

Sharp Hybrid Adaptive Routing Protocol for Mobile Ad Hoc Networks

Venugopalan Ramasubramanian (Rama)

Zygmunt Haas

Emin Gün Sirer

Cornell University

introduction
reactive

on-demand routing enables overhead to scale with data traffic

performance significantly affected by mobility

introduction

proactive

  • constant high overhead independent of data traffic
  • proactive maintenance enables low delay and often low loss rate

one protocol may out perform the other in different network conditions

changeis the only constant in mobile ad hoc networks

sharp overview
sharp overview
  • hybridization framework
    • combine proactive and reactive routing
  • application specific goals
    • destination nodes independently choose adaptation goals
    • minimal packet overhead, target loss rate, target delay jitter
  • adaptability
    • fine grain adaptation to changing network and traffic characteristics
    • self-tuning and driven by analytical model
  • efficiency
    • low overhead localized mechanisms
sharp proactive routing spr
sharp proactive routing (SPR)
  • destination rooted Directed Acyclic Graph (DAG)
    • multi-link routing
  • DAG construction
    • local broadcast (TTL = zone radius)
    • periodic reconstructions
  • DAG maintenance
    • link orientation reversal (TORA)
    • periodic update beacons
sharp proactive routing
sharp proactive routing
  • expanding radius from r to s (r < s)
    • reconstruct DAG with zone radius s and TTL s
  • shrinking radius from r to s (r > s)
    • reconstruct DAG with zone radius s and TTL r
    • distributed coordination and reliable packet delivery not required
  • multiple destinations apply SPR independently
    • overlapping regions share overhead
overhead of sharp routing components
proactive routing

independent of number of sources (S)

largely independent of mobility (λ: mean link lifetime)

depends on zone radius (r)

depends on number of nodes in proactive zone (NDr)

reactive routing

dependent on number of active routes (sources and destinations)

dependent on mobility

depends on distance (h-r)

depends on number of nodes in the search area (NSh-r)

AODV

SPR

D

S

h

r

h-r

overhead of sharp routing components
sharp adaptation
sharp adaptation
  • estimating mean link-lifetime and mean node degree
    • aggregated within proactive zone
    • piggy-backed on update beacons
  • estimating traffic characteristics
    • number of sources, routing distance, loss rate, delay jitter
    • measured at destination with information piggy-backed on data packets by the source
  • periodically choose radius before reconstruction
    • driven by analytical model
  • hysteresis
    • different low and high watermarks prevents oscillations
sharp protocols
sharp protocols
  • minimal packet overhead (SHARP-PO)
    • power and bandwidth constrained networks
    • estimate overhead during each reconstruction interval and adjust radius
  • targeted loss rate (SHARP-LR)
    • loss sensitive applications (TCP)
    • incur less overhead to achieve the target loss rate
  • targeted delay jitter (SHARP-DJ)
    • multi-media applications
    • incur less overhead to achieve the target delay jitter
  • each destination independently chooses adaptation strategy
evaluation
evaluation
  • GloMoSim simulator
  • lower layers
    • MAC: IEEE 802.11b; range: 250m; data rate: 11Mbps
  • mobility
    • random waypoint, 0 to 20 m/s, 0 pause time
    • mobility fraction: fraction of mobile nodes
  • scale
    • 600 nodes 3000m x 3000m, 2 pkts/sec
    • 200 nodes 1700m x 1700m, 8 pkts/sec
  • traffic
    • single destination
    • multiple destinations: 1, 4, 7, 10 sources respectively
    • all nodes destination
conclusions
conclusions
  • SHARP hybridization
    • explore the continuum between proactive and reactive routing strategies
  • application specific performance metrics
    • minimal packet overhead, target loss rate, target delay jitter
    • nodes independently choose adaptation goals
  • SHARP adaptability
    • fine grain control of hybridization across wide range of network and traffic scenarios
    • expensive mechanisms – clock synchronization, leader election, agreement – not required
sharp vs zrp
SHARP vs ZRP
  • SHARP supports application specific adaptation strategies (loss rate, delay jitter) in addition to packet overhead
    • ZRP optimizes only for packet overhead
  • SHARP constructs proactive zones only around destination-nodes
    • proactive zones around all nodes in ZRP
  • SHARP’s proactive routing has lower overhead – only maintains routes to the center node
    • ZRP ‘s proactive routing is expensive – maintain multi-cast tree to the edge nodes
  • SHARP expands proactive zone in response to link failures, whereas ZRP shrinks the proactive zone