Scalable Data Aggregation for
Dynamic Events in Sensor Networks
Kai-Wei Fan, Sha Liu, Prasun Sinha
Computer Science and Engineering, Ohio State University
ACM SenSys 2006
Outline
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Introduction
Structure-Less Aggregation
Experiments and Simulation
Conclusion
Introduction
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Data Aggregation
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Communication cost is often larger than computation cost.
Redundancy in raw data.
Aggregate packets near sources to reduce transmission cost.
 Prolong the lifetime.
Aggregation Approaches
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Static structure
Dynamic structure
Structure-free
Static Structure for Aggregation
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Routing on a pre-computed structure
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Pros
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Low maintenance cost
Good for unchanged traffic pattern
Cons
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Long stretch problem
Unsuitable for event-based network
Sink
Dynamic Structure for Aggregation
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Create a structure dynamically
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Pros
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Optimization for source nodes
Cons
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High maintenance cost
Sink
Structure-Free Aggregation
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No structure  No structure maintenance cost
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Aggregation without structure
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Where to transmit?
Wait for whom?
Improve aggregating by transmitting packets to the same
node at the same time
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Spatial Convergence  Data Aware Anycast
Temporal Convergence  Random Waiting
Data Aware Anycast
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Anycast
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One-to-any forwarding
Anycast to neighbor having packets for aggregating
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Class A: Nodes closer to the sink with data for aggregation
Class B: Nodes with data for aggregation
Class C: Nodes closer to the sink
Class A
Sender
Class A Nbr
Class A Nbr
Class B Nbr
Class C Nbr
Class B
Class C
RTS
CTS
Canceled CTS
Canceled CTS
Random Waiting
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Fixed Delay
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Nodes close to sink pick high delay.
…
Sink
τ=n
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τ=n-1
τ=n-2
τ=1
τ=0
Random Delay
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Source nodes pick random delay between 0 and τ before
transmission.
DAA and RW Example
2
3
1
4
Sink
Not guarantee aggregation of all packets from a single event !!
Structure-Less Aggregation
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Structure-free aggregation does not guarantee all
packets are completely aggregated to one.
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High cost for un-aggregated or partial-aggregated packets
Structure-Less Aggregation (2 Phases)
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1st : Based on structure-free aggregation (DAA & RW)
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Aggregate packets form sources to aggregators locally
2nd : Further aggregation on an implicitly constructed structure
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Aggregate packets from aggregators to sink
Tree on Directed Acyclic Graphic (ToD)
Tree on Directed Acyclic Graphic(ToD)
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Definition
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Contiguous events
Cell: A square area with side length greater than the diameter which an
event can span
F-cluster: First cluster, composed of multiple cells
S-cluster: Second cluster, composed of multiple cells (interleaved with Fcluster)
1D Construction of ToD
F-cluster
S-cluster
Tree on Directed Acyclic Graphic(ToD)
sink
sink
F-cluster-head
S-cluster-head
Shortest Path
Shortest Path
a
F-clusters
b c
d
F6
S-cluster
sink
Shortest Path Tree
S5
S6
F6
a
b
c
d
a b
c d
S5
S6
Dynamic Forwarding for 1D (1)
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Forwarding Rules
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Rule 0: Forward packets to F-aggregator by structure-free data
aggregation protocol.
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Rule 1: Event spans two cells in a F-cluster, forward to sink
sink
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Rule 2: Event spans one cells, forward to appropriate S-aggregator
sink
Dynamic Forwarding for 1D (2)
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Property 1. Packets will be aggregated at a F-aggregator,
or will be aggregated at a S-aggregator.
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If only nodes in one cell are triggered and generate the packets
 Aggregated at one F-aggregator (all nodes in a cell resides in the
same F-cluster)
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If nodes in two cells are triggered and generate the packets.
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Two cells are in the same F-cluster
 aggregated at the F-aggregator
Two cells are in different F-clusters
 aggregated at the S-aggregator
Tree on Directed Acyclic Grahpic(ToD)
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2D Construction
A B C
S1 S2
D E F
S3 S4
G H I
(a) F-clusters
A1
A2
B1
B2
C1
C2
A1
A2
A3
A4
B3
B4
C3
C4
A3
D1
D2
E1
E2
F1
F2
D1
D3
D4
E3
E4
F3
F4
D3
G1
G2
H1
H2
I1
I2
G3
G4
H3
H4
I3
I4
(b) Cells
B1
C1
C2
A4 B3
S1
D2 E1
B4 C3
S2
E2 F1
C4
E4 F3
S4
H2 I1
F4
G1
D4 E3
S3
G2 H1
G3
G4
H4
I4
H3
B2
(c) S-clusters
I3
F2
I2
Dynamic Forwarding for 2D (1)
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Event may span multiple cells in a F-cluster
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Assume the region spanned by an event is contiguous.
Maximum 4 cells
(a) 1 Cell
(a) 2 Cells
(a) 3 Cells
(a) 4 Cells
No other F-cluster will have packets  Forward to sink
Forward to other S-aggregators
Dynamic Forwarding for 2D (2)
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Forwarding Rules
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Rule 0: Forward packets to F-aggregator by structure-free data
aggregation protocol.
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Rule 1: Event spans three or four cells in a F-cluster, forwards to sink.
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Rule 2: Event spans a cell in a F-cluster, forward to a S-aggregator.
Corresponding S-cluster
F-cluster
Cell generating packets
Dynamic Forwarding for 2D (2)
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Rule 3: Event spans two cells, forward to two S-aggregators in order.
F-cluster Y
S-cluster I
C
C
C1
C2
S-cluster II
F-aggregator
S-aggregator
Sink
F-cluster X
 Forward to 1st S-aggregator (near sink), then forward to 2nd S-aggregator
Dynamic Forwarding Example
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Example
Rule 0
Rule 2
C3
C1
Sink
C2
Rule 3
Aggregator Selections
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Nodes play the role of F-aggregator in turn.
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With probability based on residual energy
Hash current time to a node within that cluster
Delegate the role of S-aggregator to F-aggregator
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Select the F-aggregator in the F-cluster near sink as the S-aggregator
Sink
F-aggregator
and
S-aggregator (Right-top S-cluster)
Sink
Dynamic Forwarding for 2D (3)
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Property 2. Packets will be aggregated at the Faggregator, at the 1st S-aggregator, or at the 2nd Saggregator.
Experiments (1)
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Experiments Environment
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105 Mica2-based nodes
7 x 15 grid network
Node spacing: 3 feet
Transmission range: 2 grid-neighbor
2 F-clusters
Fixed event location
Protocols
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Dynamic Forwarding over ToD (ToD)
Data Aware Anycast (DAA)
Shortest Path Tree (SPT)
Shortest Path Tree with Fixed Delay (SPT-D)
Experiments (2)
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Event Size
Normalized Number of Transmissi on
Long Stretch Problem
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Number of Total Transmissi ons
Number of Contributing Sources
Better Performance:
More chance of being aggregated
Experiments (3)
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Delay
Stable: Random Delay
Better Performance:
Heavily depends on delay
Experiments (4)
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Large Simulation Environment
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2000m x 1200m area
1938 nodes (grid network)
Node spacing: 35m
Transmission range: 50m
Cell side length = Event diameter
Event with random way-point model at 10m/s for 400 seconds
Protocols
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ToD
DAA
SPT
OPT
Experiments (5)
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Event Size
Best but not consider overhead
Experiments (6)
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Scalability (Event with different distance to sink)
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Event Size: 400m
Event Area: 400m x 800m
Area Distance to Sink
: 200m ~ 1400m
Experiments (7)
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Cell Size
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Event Size:
200m, 400m, 600m
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Best Cell Size:
200m Event 100m Cell
400m Event 200m Cell
600m Event 200m Cell
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Future Work:
Select appropriate cell size
Conclusion
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The paper proposes a semi-structured approach (ToD)
that locally uses a structure-less technique followed by
Dynamic Forwarding.
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ToD avoids the long stretch problem in fixed structured
approach and eliminates the overhead of maintenance of
dynamic structure.