DIFS: A Distributed Index for
Features
in Sensor Networks
Benjamin Greenstein, Deborah Estrin, Ramesh Govindan,
Sylvia Ratnasamy, and Scott Shenker Department of omputer
Science, University of California at Los. 2003.11.06
指導教授 : 陳朝鈞
報告者:李衍儀
2016/7/13
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Contents
• Introduction
• Approach
– GHT: A Geographic Hash Table/ Structured Replication
– Quad Tree
– DIFS
• Conclusion
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Introduction
•
•
Energy constrained sensor network.
Local Storage.
Small number of queries and more collected data.
Store event locally and query to all nodes.
Directed Diffusion, TAG: aggregation and pruning for statistics.
Inherent cost of flooding. (flood-then-respond)
•
Data-centric storage (DCS).
Storing data by name.
GHT/ Structured Replication.
Not efficient for range query.
Challenge: How to support range query efficiently?
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GHT/ Structured Replication
• Key/value-based distributed index
Event : Key. Hashed to geographic position
• Hotspot Problem: Structured Replication
• Structured Replication
Make 4d-1 images.
Store closest mirror.
Query to all mirror nodes.
Keys are an event names.
 Range queries over the value is not efficient
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Quad Tree
• Indexing values for range queries.
Spatially distributed quad tree of histogram.
• Efficient range queries.
Branches can be pruned during search.
• But, not scalable
Every data information must be propagated to the root.
Every queries must originate with root.
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query
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DIFS (1/5)
• Multiply rooted hierarchical index.
Nodes can have multiple parents.
Nodes store information for a particular range of values detected
within a particular geographic region.
• Load balance
Higher-level nodes cover smaller value ranges within large region.
Lower-level nodes cover larger value ranges within small region.
• Efficiently support range queries, queries about distribution of value
in space.
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DIFS (2/5)
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bfact: 2i
•
•
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Each child have bfact parents.
The range of child is bfact times
the range of parent.
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A Simplified Example
[0…3]; Full-N/W
[0…7]; Q1
[0…7]; Q2
[4…7]; Full-N/W
[0…7]; Q3
[0…7];Q4
bfact = 2
Max Levels = 2
Max Range [0…7]
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Conclusion
• DIFS: index structure for sensornets for energy-efficient and load
balanced range search.
• DIFS performs best when
Many queries posed relative to the number of generated events.
The result sets is small.
The result sets is not likely to be distributed the network.
• DIFS is scalable to a large number of searches or stores.
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