data collection and dissemination
DESCRIPTION
Data Collection and Dissemination. Outline. Data Dissemination Trickle – Address single packet Data Collection DSF. Data Dissemination - Trickle. Simple Broadcast Retransmission. Broadcast Storm Problem Redundant rebroadcasts Severe contention Collision. Trickle. Motivation - PowerPoint PPT PresentationTRANSCRIPT
Data Collection and Dissemination
Outline
• Data Dissemination– Trickle – Address single packet
• Data Collection– DSF
[Dissemination_1] 3
Data Dissemination - Trickle
Simple Broadcast Retransmission
• Broadcast Storm Problem– Redundant rebroadcasts– Severe contention– Collision
Trickle
• Motivation– WSNs require network code propagation
• Challenges– WSNs exhibit highly transient loss patterns,
susceptible to environmental changes– WSNs network membership is not static– Motes must periodically communicate to learn
when there is new code• Periodical metadata exchange is costly
Trickle Requirement
• Low Maintenance• Rapid Propagation• Scalability
Trickle
• An algorithm for code propagation and maintenance in WSNs
• Based on “Polite Gossip”– Each node only gossip about new things that it has
heard from its neighbors, but it won’t repeat gossip it has already heard, as that would be rude
• Code updates “trickle” through the network
Trickle
• Within a node time period– If a node hears older metadata, it broadcasts the new data– If a node hears newer metadata, it broadcasts its own
metadata (which will cause other nodes to send the new code)
– If a node hears the same metadata, it increases a counter• If a threshold is reached, the node does not transmit its metadata• Otherwise, it transmits its metadata
Trickle – Main Parameters
• Counter c: Count how many times identical metadata has been heard
• k: threshold to determine how many times identical metadata must be heard before suppressing transmission of a node’s metadata
• t: the time at which a node will transmit its metadata. t is in the range of [0, τ]
[Dissemination_1]: Figure 3 10
Trickle Maintenance – One Example
• Assume– No packet loss– Perfect interval synchronization
• How to relax these assumptions?
[Dissemination_1]: Figure 5 11
Trickle Maintenance without Synchronization – Short Listen Problem
• Mote B selects a small t on each of its three intervals– Although other motes transmit, mote B’s transmissions are never
suppressed• The number of transmissions per intervals increases significantly
Solution to Short Listen Problem
• Instead of picking a t in the range [0, τ], t is selected in the range [τ/2, τ]
[Dissemination_1]: Section 5 13
Propagation• Tradeoff between different values of τ
– A large τ• Low communication overhead• Slowly propagates information
– A small τ• High communication overhead• Propagate more quickly
• How to improve?– Dynamically adjust τ
• Lower Bound τl
• Upper Bound τh
Trickle Complete Algorithm
Data Collection
[Collection_2] 16
Data Collection
• Link-Quality based Data Forwarding– Wireless communication links are extremely
unreliable– ETX: to find high-throughput paths on multiple
• Sleep-Latency Based Forwarding– Duty Cycling: sensor nodes turn off their radios
when not needed• Idle listening waste much energy
[Collection_2] 17
Sleep Latency in Low Duty-Cycle Sensor Networks
Sleep now. Wake up in 35 seconds
Sleep now. Wake up in 4 seconds
Sleep now. Wake up in 57seconds
Sleep now. Wake up in 13 seconds
35s latency
57s latency
4s latency13s latency
A
B
C
D
E
Unreliable Radio Links
90%
95%
50%
70%
A
B
C
D
E
State-of-the-art Solutions: ETX
50%, 100s
50%, 100s
40%, 10s40%, 10s
ETX = 1/0.5 + 1/0.5 = 4
ETX = 1/0.4 + 1/0.4 = 5
Expected E2E delay is 400sExpected E2E delay is 50s
A
B
C
DSole link quality based solutions cannot help reduce E2E delay in extremely low-duty cycle sensor networks!
ETX only considers link quality
State-of-the-art Solutions: DESS
10%, 10s 10%, 10s
100%, 20s
100%, 20s
DESS = 10 + 10 = 20s
DESS = 20 + 20 = 40s
Expected E2E delay is 200sExpected E2E delay is 40s
A
B
C
DSole sleep latency based solutions cannot help reduce E2E delay in extremely low-duty cycle sensor networks!
DESS only considers sleep latency
End-to-End Delay vs. Duty Cycle
• Suppose one fixed forwarding node– Suffer excessive delivery delays when waiting for
the fixed receiver to wake up again if the ongoing packet transmission fails
End-To-End Delay vs. Average Link Quality
• Given bad link quality, the end to end delay increases dramatically
Sensor States Representation
• Scheduling Bits– (10110101)*
• Switching Rate– 0.5HZ 16s round time On
10110101
Off
Data Delivery Process
1 2 3 4
Sleep latency is 1
Sleep latency is 2
Sleep latency is 3
End to End (E2E) Delay is 6
(1000000000)* (0100000000)* (0001000000)* (0000001000)*
1st attempt: Sleep latency is 1
Main Idea
1 2 3 4(1000000000)* (0100000000)* (0001000000)* (0000001000)*
Sleep latency is 1
2nd attempt: Sleep latency is 1 + 10 =11ith attempt: Sleep latency is 1 + 10 * (i-1)
(0010000000)*
5
2nd attempt: Sleep latency is 1 + 1 =2
We should try a sequence of forwarding nodes instead of a fixed forwarding node!
Dynamic Switching-based Forwarding (DSF) is important in extremely low duty-cycle sensor networks.
Optimization Objectives
• EDR: Expected Delivery Ratio
• EED: Expected End-to-End Delay
• EEC: Expected Energy Consumption
Optimization Objectives(1) : EDR
1 3
4
(100)*
(100)*EDR = 90%
(001)*EDR = 80%
(010)*EDR = 70%2
60%
50%
40%
EDR: Expected Delivery Ratio.
0.6*0.7
+ (1-0.6)*0.5*0.8
+ (1-0.6)*(1-0.5)*0.4*0.9=0.652
EDR for node 1 is (EDR1):
Forwarding Sequence
See Equation (3)
Optimizing EDR
1
3
(100)*
(001)*EDR = 80%
2 (010)*EDR = 70%
100%
100% If only node 3 is selected as forwarding node:
EDR1 = 1 * 0.8 = 0.8
We should only choose a subset of neighboring nodes as forwarding nodes!
Shall we try all available neighbors?
If both node 2 and node 3 are selected as forwarding nodes:
EDR1 = 1 * 0.7 = 0.7
Optimizing EDR with dynamic programming
1
2
3
4
(100)*
(100)*EDR = 90%
(001)*EDR = 80%
(010)*EDR = 70%
60%
50%
40%
Select only a subset of neighbors as forwarders
Node 4 has to be selected
Then we attempt to add more nodes into the forwarding sequence backwardly.
Try or skip
Try or skip
Try or drop
Distributed Implementation
• EDRb(Ø) = 1– The sink node has no packet loss
• EEDb(Ø) = 0– The sink node has no delay
• EECb(Ø) = 0– The sink node has no energy consumption
Distributed Implementation
sink
42
1 3EDR = 98%, EED = 2, EEC = 1
EDR = 99%, EED = 15, EEC = 2
EDR = 100%, EED = 0, EEC = 0
EDR = 97%, EED = 20, EEC = 5 EDR = 90%, EED = 90, EEC =
12
Complete Protocol Implementation at Node e