SimilarityAware Query Processing in Sensor Networks

1
Similarity-Aware Query Processing in Sensor
Networks

• Ping Xia
• Panos K. Chrysanthis
• Alexandros Labrinidis
• Advanced Data Management Technologies Lab
• University of Pittsburgh

2
Disasters happen What next?

• Use sensor networks to predict and mitigate
  disasters
• Use sensor networks to respond to disasters
  efficiently
• Use sensor network data to improve response
  in the future

3
Pitfalls of Base Station Architecture
4
Data Centric Storage (GHT)
Some queriesare similar!
Consolidator-Node
5
Roadmap

• Motivation
• Similarity-Aware Query Processing
• Evaluation
• Conclusions

6
Similarity-Aware Query Processing (SAQP)
O-Node
I-Node
Q-Node
M-Node
Q-Node
O-Node
7
SAQP Algorithm

• Three steps
• A Q-node sends a query to an I-node.
• I-node checks list of candidate O-nodes and list
  of candidate M-nodes, from which a set of nodes
  is selected as responder set.
• Query is forwarded to nodes in the responder set
  and satisfactory events are sent from those nodes
  to the Q-node.

8
Issues

• Query split
• Query range (5, 30), (10, 25)
• M-View with range (10, 25), (15, 20)
• Candidate selection
• How to determine the responder set from the
  candidate O-nodes and candidate M-nodes?

9
Query split
Q r
5
10
25
30
10
r2
r1
r3
15
r4
r6
r5
20
r8
r7
r9
25
Q1 r5 --- Send to the corresponding M-node
Q2 ? --- For further evaluation
Solution r r5
Solution r1r2r3r4r6r7r8r9 ?
10
Candidate Selection

• A greedy algorithm
• 1. Responder F,
• CandidateONodes Onodes with
  satisfactory events ,
• CandidateMNodes Mnodes such that their
  ranges overlap with query range.
• 2. If set CandidateMNodes ! F, pick one and
  add it into set Responder. Meanwhile, remove some
  Onodes from set CandidateOnodes if their events
  are covered.
• 3. If there are energy saving, keep the
  change. Otherwise, undo the change.
• 4. Do step 2 and 3 until CandidateMNode F
• 5. Responder Responder (remaining)
  CandidateONodes

11
Roadmap

• Motivation
• Similarity-Aware Query Processing
• Evaluation
• Conclusions

12
Evaluation

• Energy Model
• Etransmit Etrans k Eamp d2
• Ereceive Erec k
• Metrics
• Energy Cost
• Response time ( of hops)
• 3 schemes
• GHT (Geographic Hash table, WSNA 02)
• IGHT (Index-based GHT)
• SAQP

13
Experiments

• Sensitivity analysis on
• Query Skewness
• Q(VLowVHigh, t-Deltat), VHigh-VLow is fixed
  and the center (VHighVLow)/2 follows zipf
  distribution.
• Time Interval
• Q(VLowVHigh, t-Deltat)
• Query Locality
• Confining factor C restrict queries issued from a
  region with size (CX) x (CY)
• Event Size
• Number of Queries
• Number of Events

14
Simulation parameters
15
Query Skewness
Energy Consumption
Response Time
Higher energy savings if queries are more skewed
(more similar)
16
Time Interval
Energy Consumption
Response Time
Higher energy savings compared to IGHT, if query
range is large
17
Query Locality
Energy Consumption
Response Time
Higher energy savings if queries initiated from
same region
18
Roadmap

• Motivation
• Similarity-Aware Query Processing
• Evaluation
• Conclusions

19
Conclusions

• We proposed a similarity-aware query processing
  (SAQP) scheme that
• creates materialized views in sensor networks
• utilizes the materialized views to answer future
  queries that are similar to past ones.
• By using our query split strategy and candidate
  selection algorithm, SAQP
• reduces energy consumption,
• with a slight increase in response time,
• without compromising QoD.

20
Thank You

• Questions?

21

• BACKUP

22
Our Framework

• O-node (Original node)
• Where the events are stored (locally).
• Q-node (Query node)
• The node who issued the current query.
• M-node (M-view node)
• A Q-node that has issued a query in the past
  becomes a M-node for future queries. (Query
  results) M-Views are stored at M-nodes.
• I-node (Index node)
• Where the indexes to events and directories of
  materialized-views are stored. Each directory is
  associated with a query processed in the past.

23
The framework (cont.)

• Events
• O-nodeId, scalar attributes, event details,
  timestamp
• Indexes
• O-nodeId, scalar attributes, timestamp
• M-View directories
• M-nodeId, range, timestamp

24
QoD

• Two events (e1, e2 in time order) are detected by
  the same O-Node
• A Query (q) is initiated after the two events are
  detected.
• Both events and the query are forwarded to the
  I-Node, but it reaches the I-Node in the order
  e1, q and e2.
• In GHT, only e1 will be returned.
• In SAQP, the O-Node might be selected as a
  responder, both e1 and e2 will be returned.
• Conclusion SAQP achieves better QoD

25
Event size
26
Number of Queries
27
Number of Events
28
GPSR Greedy Forwarding
D
x
y
29
GPSR Greedy Forwarding Failure
30
GPSR Perimeter Forwarding
d
z
z
e
e
c
c
a
a
f
x
x
b