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Top-k Monitoring in Wireless Sensor Networks
Minji Wu, Jianliang Xu, Xueyan Tang, and Wang-Chien Lee
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 19, NO. 7, JULY 2007
Outline Introduction Filter-based Monitoring Approach
FILA Overview Query Reevaluation Filter Setting (Uniform versus Skewed) Filter Update (Eager versus Lazy)
Performance Study Simulation Setup Eager versus Lazy Filter Update Performance Comparison against TAG and Range
Caching Conclusions
Introduction Top-k Query
Environmental Monitoring A top-k query is issued to find out the
nodes and their corresponding areas with the highest pollution indexes for the purpose of pollution control or research study.
Network Management A top-k query may be issued to
continuously monitor the sensor nodes with the least residual energy.
Introduction In traditional database systems
Focused on snapshot top-k queries
This paper focuses on continuously monitoring top-k queries in sensor networks. Utilize previous top-k result to obtain
a new top-k result.
Top-1 query TAG (S. Madden et al. , OSDI ’02)
BS
C
A B
t1
t1 t1
t2
t2 t2
t3
t3 t3
35
38
37
43
45
48
51
56
52
43 51
51
45 56
56
48 52
52
A total of nine messages are sent
Top-1 query Range Caching (C. Olston et al., SIGMOD’01)
BS
C
A B
t1
t1 t1
t2
t2 t2
t3
t3 t3
35
38
37
43
45
48
51
56
52
4852
48 A total of four messages are sent
[39, 47]
[47, 80]
[20, 39]
Problem Definition Consider a top-k monitoring query that con
tinuously requests the (ordered) list of sensor nodes R with the highest readings, that is
FILA Overview
(1) Filter Setting the base station computes a filter [li, ui] for each sensor
node i and sends it to the node for installation.
(2) Query Reevaluation(3) Filter update
Query Reevaluation
Sensor-initiated updates (1) Internal update (2) Join update (3) Leave update
Internal update
Leave update
Join update
Critical bound
A Simple Case
Consider a simple case where only one sensor-initiated update is received by the base station
Only n1 needs to be probed
A Simple Case
Only the sensor nodes whose currentreadings are higher than v2’ respond to the probe
General Cases
Tinternal : the set of internal updates Tjoin : the set of join updates Tleave: the set of leave updates T : the old top-k set
If |T'| = |T| - | Tleave| + | Tjoin| k the new top-k set must be a subset of T'
Otherwise, if |T'| < k the nodes that are not in T' have to be probed.
An Example of Top-3 Monitoring
Another Example of Top-3 Monitoring
Filter Setting
Uniform filter setting
It is simple and favorable when the readings of all sensor nodes follow a similar changing pattern.
Filter Setting Skewed filter setting
taking into account the changing patterns of sensor readings.
Suppose the average time for the reading of node i to change beyond is fi() 1/fi() : the rate of sensor-initiated updates by n
ode i
Filter Setting We let every node measure the average delt
a change di of their sensor readings at a fixed rate.
Skewed filter setting
Filter Update Eager filter update
If a new filtering window [li', ui'] is different from the old one [li, ui] then the new filter [li', ui'] is immediately sent to node i
Lazy filter update If a new filtering window [li', ui'] fully contains
the old one [li, ui], that is, [li', ui'] [li, ui] then the base station delays the filter update until node i’s reading violates the old filter [li, ui].
Performance Study Simulation Setup
Energy cost in transmitting a message
s : message size : distance-independent term (50 nj/b) : coefficient (100 pj/b/m2) q: distance-dependent term ( 2) d: distance
Energy cost in receiving a message is set at 50 nJ/b
Performance Study
A Sensor initiated update message: Sensor ID : 4 bytes Sensor Reading: 4 bytes
A filtering window is characterized by 8 bytes.
Network Layouts
Real Data Traces Simulated using the real traces provided by the Live from Earth and
Mars (LEM) project at the University of Washington.
Two kinds of sensor readings are used temperature (TEMP) Dew point (DEW) logged by the station at the University of Washington from August 2004 t
o August 2005
Total 500000 sensor readings Extract many subtraces starting at different dates Each subtrace contains 20000 readings The subtraces were used to simulate the physical phenomena in the im
mediate surroundings of different sensor nodes.
Real Data Traces
Evaluation Metrics Network Lifetime
the network lifetime is defined as the time duration before the first sensor node runs out of power.
Average Energy Consumption It is defined as the average amount of energy
consumed by a sensor node per time unit. Monitoring Accuracy
This is defined as the mean accuracy of monitored results against the real results.
Eager versus Lazy Filter Update(multihop, k =10)
Network lifetime. Average energy consumption.
Eager versus Lazy Filter Update
Energy consumption by layer
Performance Comparison against TAG and Range Caching(single hop, k =3)
Network lifetime.Average energy consumption.
Performance Comparison against TAG and Range Caching (single hop, k =3)
Monitoring accuracy
Performance Comparison against TAG and Range Caching(Multihop, k =10)
Network lifetime. Average energy consumption.
Performance Comparison against TAG and Range Caching(Multihop, k =10)
Monitoring accuracy
Conclusion
This paper exploited the semantics of top-k query and proposed a novel energy-efficient monitoring approach called FILA.
Two filter setting algorithms (that is, uniform and skewed) and two filter update strategies (that is, eager and lazy) have been proposed.
Filter Setting Under random walk model
0.50.5
l
The average time for the reading to change beyond can be expressed as
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