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Combs, Needles, and Haystacks:Balancing Push and Pull for Information Discovery
Xin LiuComputer Science Dept.
University of California, Davis
Collaborators: Qingfeng Huang & Ying Zhang, PARC
Presented by Chien-Liang Fok on March 4, 2004 for CSE730
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Objective
Simple, reliable, and efficient on-demand information discovery mechanisms
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Where are the tanks?
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Pull-based Strategy
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Pull-based Cont’d
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Push-based Strategy
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Comb-Needle Structure
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Assumptions
Events: Anywhere & Anytime Queries: Anywhere & Anytime
Global discovery-type One shot
Network: Uniform Examples:
Firefighters query information in the field Surveillance
Sensor nodes know their locations
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When an Event Happens
Event
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When a Query is Generated
Event
Query
Event
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Tuning Comb-Needle
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Query Freq. < Event Freq.
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Query Freq. < Event Freq.
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Reverse Comb
Query
Event
When query frequency > event frequency
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The Spectrum of Push and Pull
Pull Push
Global pull +Local push
Global push +Local pull
Push & Pull
Inter-spike spacing increases
Reverse comb
Relative query frequency increases
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Mid-term Review
Basic idea: balancing push and pull
Preview: Reliability Random network An adaptive scheme
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Strategies for Improving Reliability
Local enhancement Interleaved mesh (transient failures) Routing update (permanent failures)
Spatial diversity Correlated failures Enhance and balance query success rate at
different geo-locations Two-level redundancy scheme
l=2s
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Spatial Diversity
Query
xEvent
Diversify queryspatially using green arrows
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Random Network
Constrained geographical flooding Needles and combs have certain widths
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Simulation Using Prowler
Transmission model:
Reception model: Threshold MAC layer: Simulates Berkeley Motes’ CSMA Use Default radio model:
σa=0.45, σb=0.02, perror=0.05, =0.1
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Two Experiments
1. What is the optimal spacing of the comb & needle length given Fq and Fe?
2. What is the robustness of the protocol in a really sparse network?
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Experiment 1 Results
l=1, s=3 optimal l=1, s=3 optimal
loptimal ~
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Experiment 2 Results
Wider the CGF width More Reliable More Energy
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Adaptive Scheme
Comb granularity depends on the query and event frequencies
Nodes estimate the query and event frequencies to guess s
Important to match needle length and inter-spike spacing
Allow asymmetric needle length Comb rotates
Load balancing Broadcast information of current inter-spike spacing
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Simulation
20x20 regular grid Communication cost: hop counts No node failure Adaptive scheme
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Event & Query Frequencies
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Tracking the Ideal Inter-Spike Spacing
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Simulation Results
Gain depends on the query and event frequencies Even if needle length < inter-spike spacing, there is a
chance of success. Tradeoff between success ratio and cost
99.33% success ratio and 99.64% power consumption compared to the ideal case
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Summary
Adapt to system changes Can be applied in hierarchical structures
Pull Push
Global pull +Local push
Global push +Local pull
Push & Pull
Relative query frequency increases
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Future work
Further study on random networks Building a “comb-needle-like” structure
without location information Integrated with data aggregation and
compression Comprehensive models for communication
costs