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