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Data Elevators
Applying the Bundle Protocol in Delay Tolerant Wireless Sensor Networks
Wolf-Bastian Pottner, Felix Busching, Georg von Zengen, Lars Wolf
IEEE MASS 2012, 2012-10-09
Introduction Bundle Protocol Data Elevator Network Capacity Conclusion
Motivation
ZebraNet
tion and type of activity. By selecting andusing these tools, the vineyard workerwould provide the necessary input intothe system naturally and effortlessly. Theconcept of tracking workers’ movementthrough space has already been sug-gested as a useful tool for generatingbilling reports and time studies in custo-dial environments such as hospitals.10
We envision an instantiation of this ideawith the added concept of tagged tools toprovide an indication of workers’ activ-ities. The manager’s need to track activ-ities in the vineyard also suggests thatfocusing attention on developing local-ization algorithms for sensor networks—specifically tracking the location oftagged objects moving through a sensornetwork—is a research direction poten-tially useful for agricultural applications.
System architectureOur study also suggested different
types of interfaces that could be seam-lessly incorporated into the vineyard,including the tagged tools described ear-lier. However, our understanding of theworkflow also suggested some ways thatthe system infrastructure itself could bereorganized to optimize power manage-ment and equipment costs. Our efforts tocreate a working sensor network imple-mentation in a local vineyard gave ussome insight into the interplay betweenpower management, equipment costs,system architecture, and user needs.
Power management is one of the pri-mary issues in the design of sensor net-work systems intended to operate wire-lessly.11 An ideal system would be asensor network made up of devices thathave an extremely long battery life and
are automatically rechargeable or aretiny, disposable, inexpensive, and easilyreplaced. The concepts of Smart Dustand Paintable Computers are two pro-posals of this ideal vision.12,13 Becausewe believe that sensor networks are use-ful in the near term, we must realisti-cally face power management issues toavoid the worst-case scenario where bat-teries must be frequently replaced inhundreds or thousands of individualdevices. We have uncovered opportuni-ties for a system wide approach topower management by designing thesoftware and system architecture tooptimize power management. However,our modest gains could be greatlyimproved if the hardware wereredesigned with these system wide con-figurations in mind.
Self-organizing ad hoc sensor net-works are generally considered thedefault system architecture, in partbecause they present more interestingcomputational problems for computerscientists to tackle. However, this archi-tecture assumes RF connections, oftenusing TDMA (time division multipleaccess, a technology for delivering digi-tal wireless service) between each moteand its neighbors. This arrangement ofsystem components requires enough
equipment to cover a space with a fullyconnected network. It’s an optimal archi-tecture for some types of applicationsbut is by no means the only one oralways the ideal arrangement of the net-work. Specifically, the self-organizingmultihop architecture that forwards datais the only architecture that makes muchsense for sensor network applications inremote, inaccessible environments.
We discovered that other system archi-tectures could be employed in vineyardsbecause they are neither remote nor inac-cessible. For example, one architectureused data mules to collect and transportdata from sensor network motes dis-tributed throughout the vineyard (seeFigure 2).14 From our interviews andobservations, we learned that during thegrowing season, workers move up anddown the rows a lot. In one vineyard,two family dogs also spent a lot of timegoing up and down the rows. Any ofthese moving bodies (even the dogs)could serve as a “data mule” by carry-ing a small device that simply and invis-ibly gathers data wirelessly from the sta-tic, distributed motes.
The data would be transmitted fromthe static mote to the data mule motewhenever the two motes are in physicalproximity and there’s new data to trans-
JANUARY–MARCH 2004 PERVASIVEcomputing 15
Figure 2. Data mule system architecturein the vineyard. (a) The motes recordenvironmental data and vineyard activities. (b) In the course of daily activities, the worker collects more dataonto the shovel. (c) The worker takes thetool back to the shed. (d) Back in the toolshed, the shovels upload their data to thecentral database.
(a)
(b)
(d) (c)
Vineyard Computing SeNDT
ObservationDelay Tolerance is widely used (and needed) in sensor network research
Wolf-Bastian Pottner | Data Elevators | 2
Introduction Bundle Protocol Data Elevator Network Capacity Conclusion
Common Requirements
Measurement
Periodic sampling of sensor values
Networking
Multi-hop data delivery
Disrupted links, changing topologies
Delay is not important, reliability is
9=
; Store, carry and forward
Hardware
Long lifetime
Minimal installation e↵ort
Few maintenance cycles
! Low-power
! Wireless
! Robust
Wolf-Bastian Pottner | Data Elevators | 3
Introduction Bundle Protocol Data Elevator Network Capacity Conclusion
Wireless Sensor Networks (WSNs)
Wireless Sensor Networks
Multi-hop wireless
Battery powered
Wireless Sensor Nodes
Based on microcontrollers
IEEE 802.15.4 radios
App. 16 kB RAM, app. 128 kB ROM
Low-power hardware
Storage (flash, SD, ...)
INGA
T-Mote Sky
Wolf-Bastian Pottner | Data Elevators | 4
Introduction Bundle Protocol Data Elevator Network Capacity Conclusion
Outline
Introduction
Bundle Protocol in Delay Tolerant Wireless Sensor Networks
Data Elevator Application Scenario
Capacity of Delay Tolerant Wireless Sensor Networks
Conclusion
Wolf-Bastian Pottner | Data Elevators | 5
Introduction Bundle Protocol Data Elevator Network Capacity Conclusion
Protocols for Wireless Sensor Networks
Predominant WSN Protocols
6LoWPAN: IPv6 over low-power WPAN
Contiki’s and TinyOS’ proprietary protocols
! Not delay tolerant (not store, carry and forward)
Store, Carry and Forward Protocols
ZebraNET (non-standardized)
Vineyard Computing (non-standardized)
Seal-2-Seal (non-standardized)
Bundle Protocol (RFC 5050)
Wolf-Bastian Pottner | Data Elevators | 6
Introduction Bundle Protocol Data Elevator Network Capacity Conclusion
Benefits and Drawbacks of Standard Protocols
Benefits
Seamless integration
Lower entry barrier
Generic solutions
Drawbacks
Not optimized for use case
Higher overhead
Benefits of the Bundle Protocol
Flexibility: Variable length header fields, extension blocks, etc.
Overlay Protocol: Works on top of heterogeneous technologies
Well suited: Designed for unstable links and changing topologies
Q: Is the Bundle Protocol too heavy for nodes?
Wolf-Bastian Pottner | Data Elevators | 7
Introduction Bundle Protocol Data Elevator Network Capacity Conclusion
Bundle Protocol Overhead Comparison
Overhead [Bytes]
802.15.4
802.15.4
802.15.4
802.15.4
802.15.4
IPv6 TCP
6LoWPAN TCP
6LoWPAN TCP CL
Bundle Protocol
Bundle Protocol
6LoWPAN
6LoWPAN
UDP
UDP
TCP / IPv6
UDP / 6LoWPAN
TCP / 6LoWPAN
BP / UDPCL / 6LoWPANBP / TCPCL / 6LoWPAN
802.15.4 IPv6 UDPUDP / IPv6 57
69
23
38
4461
802.15.4 Bundle ProtocolBP / IEEE 802.15.4 CL 31
802.15.4 RIMEContiki‘s RIME 19
IEEE 802.15.4 maximum frame size is 127 bytes
A: Protocol overhead is higher but manageable
Wolf-Bastian Pottner | Data Elevators | 8
Introduction Bundle Protocol Data Elevator Network Capacity Conclusion
Bundle Protocol Complexity Comparison
160
180
200
220
240
260
280
300
0 10 20 30 40 50 60 70
Pa
rsin
g o
f In
com
ing
Da
ta [
us]
Payload Length [bytes]
6LoWPAN HC06 / UDPBundle Protocol CBHE 0
5000
10000
15000
20000
25000
8 16 24 32SD
NV
Op
era
tion
s p
er
Se
con
d
Integer Size [bit]
DecodeEncode
Run on INGA at 8 MHz
A: Computational complexity is comparable
Wolf-Bastian Pottner | Data Elevators | 9
Introduction Bundle Protocol Data Elevator Network Capacity Conclusion
How can we implement the Bundle Protocol on nodes?
Literature
Bundle Protocol as overlay protocol over 6LoWPAN
Our Approach on the Nodes: µDTN
BP in IEEE 802.15.4 data frames
Cross-layer, avoiding layers 3 and 4
Implementation based on Contiki OS
Our Approach on the PC
IEEE 802.15.4 radio attached to PC
IBR-DTN software extension to handle radio
Wolf-Bastian Pottner | Data Elevators | 10
Introduction Bundle Protocol Data Elevator Network Capacity Conclusion
Data Elevator Application Scenario
Opening QuestionHow can we get temperature readings from the rooftop into our lab?
Concept
Node with sensor on rooftop
Elevator is data mule
Delay tolerant network
Setup
1 sensor, 3 relays, 1 sink
µDTN with RAM storage
Rooftop
#1
#2
#3
#4
Elevator: 1st 14thFloor
#5
Building ABuilding B
15 th Floor
3 rd Floor
14 th Floor
Temperature Sensor
Wolf-Bastian Pottner | Data Elevators | 11
Introduction Bundle Protocol Data Elevator Network Capacity Conclusion
Evaluation: Temperature and Delay (Weekend)
0
1
2
3
4
5
6
7
8
0 2 4 6 8 10 12 14 16 18 20 22 0 0
3
6
9
12
15
18
21
24
Bundle
Dela
y [h
]
Tem
pera
ture
[D
egre
e C
els
ius]
Time of Day [h]
Bundle Delay Temperature
Wolf-Bastian Pottner | Data Elevators | 12
Introduction Bundle Protocol Data Elevator Network Capacity Conclusion
Evaluation: Delay Distribution (Weekend)
0 10 20 30 40 50 60 70 80 90
100
>0-5 >10-15>20-25
>30-35>40-45
>50-55>60-65
>70-75>80-85
>90-95>100
Num
ber
of O
ccurr
ence
s [%
]
Bundle Delay Bins [m]
Delay DistributionAccumulated Delay Distribution
Wolf-Bastian Pottner | Data Elevators | 13
Introduction Bundle Protocol Data Elevator Network Capacity Conclusion
DT-WSN Capacity Model
Storage(Capacity((SCap,Send SCap,Recv
Bundles(in(Storage(SSend,i SRecv,i
Sender( Receiver(
BundleRatei
Channel Capacity:
Transmitted Bundles:
Storage Sender:
Storage Receiver:
Ci ,j = Durationi · BundleRateiTi = min(SSend ,i ,Ci ,j)
SSend ,i = min(SSend ,i�1 � Ti�1 + Ni , SCap,Send)
SRecv ,i = min(SRecv ,i�1 + Ti , SCap,Recv )
Wolf-Bastian Pottner | Data Elevators | 14
Introduction Bundle Protocol Data Elevator Network Capacity Conclusion
Evaluation: Capacity Model
0
10
20
30
40
50
60
70
80
0 50 100 150 200 250 300
Perm
anently
Lost
Bunld
es
[%]
Sample Interval [s]
Storage: 100 BundlesStorage: 300 Bundles
Storage: 500 Bundlesunlimited
Wolf-Bastian Pottner | Data Elevators | 15
Introduction Bundle Protocol Data Elevator Network Capacity Conclusion
Conclusions Wolf-Bastian [email protected]://www.ibr.cs.tu-bs.de/projects/mudtnProtocols
Standard protocols are generic solutions to common problems
BP is de facto standard in DTNs and should be in DT-WSNs
µDTN
Bundle Protocol implementation for Contiki
Overhead is comparable to 6LoWPAN
Integration into existing DTNs via transparent gateway nodes
Data Elevator
Data is delivered with delay but without loss
Wolf-Bastian Pottner | Data Elevators | 16
Introduction Bundle Protocol Data Elevator Network Capacity Conclusion
Evaluation: Temperature and Delay (Weekday)
0
1
2
3
4
5
6
7
8
0 2 4 6 8 10 12 14 16 18 20 22 0 0
3
6
9
12
15
18
21
24
Bundle
Dela
y [h
]
Tem
pera
ture
[D
egre
e C
els
ius]
Time of Day [h]
Bundle Delay Temperature
Wolf-Bastian Pottner | Data Elevators | 18
Introduction Bundle Protocol Data Elevator Network Capacity Conclusion
Evaluation: Delay Distribution (Weekday)
0 10 20 30 40 50 60 70 80 90
100
>0-5 >10-15>20-25
>30-35>40-45
>50-55>60-65
>70-75>80-85
>90-95>100
Num
ber
of O
ccurr
ence
s [%
]
Bundle Delay Bins [m]
Delay DistributionAccumulated Delay Distribution
Wolf-Bastian Pottner | Data Elevators | 19