Energy Aware Routing in

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Nov 21, 2013 (3 years and 11 months ago)

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Energy Aware Routing in
Wireless Sensor Networks

Jonathan Tate

19 December 2006

Outline


Wireless Sensor Networks


Routing strategies


Reducing energy impact of routing


Simulation as a design tool

Wireless Sensor Networks


A type of MANET


Every node is a router and a data source


Nodes are severely resource
-
constrained


Rapidly changing topology


May contain thousands of nodes


Resilient to failure of individual nodes


Self
-
organising

[Akyildiz02, Culler04]

What does a WSN do?


Nodes monitor the environment


Sensor data has geographical context


Identity of individual node is unimportant


Hostile environments


Environmental monitoring


Military


Surveillance


Emergency and disaster management

[Akyildiz02, Culler04, Szewczyk04]

Sensor Nodes

Spec chip [Berkley03]

Intel mote [Club04]

MICA [Polastre03]

MICA 2 [Crossbow06]

Topology Control


No control over physical location of nodes


Signal strength modulation to control connectivity


Logical structure overlaid on physical topology

Inter
-
cluster routing

Node
-
centric zones of two hops

[Royer99, Beijar02, Chen01, Chiang97]

Energy
-
Aware Routing


Maximise network lifetime (no accepted definition)


Communication is the most expensive activity


Possible goals include:


Shortest
-
hop (fewest nodes involved)


Lowest energy route


Route via highest available energy


Distribute energy burden evenly


Lowest routing overhead


Distributed algorithms cost energy


Changing component state costs energy

[Raghunathan02, Jones01, Singh98, Weiser94, Shah02, Stojmenovic01]

Routing Strategies


Aim to make communication more efficient


Trade
-
off between routing overhead and
data transmission cost


Strategies incur differing levels of
communication and storage overhead


Hybrid approaches are possible

[Jones01, Beijar02, Royer99, Broch98]

Stateless Routing


Nodes maintain no routing information


Flooding


Messages rebroadcast to neighbours


Gossiping


Messages rebroadcast to neighbours, probability <1


Geographic


Need to know direction to destination


Epidemic


Pairwise exchange of messages between carriers


Copes with temporary network partition


No routing state, but message buffering infeasible in WSNs

[Vahdat00, Xu01, Karp00, Ko98, Imielinski96]

Proactive and Reactive Routing


Proactive routing


Routes created and maintained in advance


Low latency, high resource demand


Does not scale to large networks


Reactive routing


Routes created and cached as required


High latency, lower resource demand

[Johnson96, Perkins94, Perkins97, Das00, Park97]

Data
-
centric Routing


Routing application data rather than packets


Node identities unknown to users


Data naming and labelling


Users express interests in named data, protocol
sets up data flows


Combines routing and distributed data
management


Data aggregated and summarised in flows


Well suited to WSN paradigm

[Intanagonwiwat00, Ratnasamy02, Heinzelman99]

Flooding


Used in data delivery or route discovery


Very simple algorithm, implicit multicast


Observed results surprisingly complex


Stragglers, Backward Links, Long Links, Clustering


Last 5% of nodes take as much time as preceding
95%, independent of radio power


Some nodes will never receive the message


Redundant communications waste energy

[Ni99, Ganesan02]

Flooding Behaviour

1
st

broadcast

Final state

2
nd

broadcast

3
rd

broadcast

[Ganesan02]

Broadcast Storm Problem


Flooding is appropriate if topology changes
rapidly; other approaches cannot keep up


Broadcast Storm Problem


Redundancy


Contention


Collisions


WSN nodes cannot afford energy or computation
cost of wasteful communication

[Ni99]

Solving the BSP


Cannot ignore problem as flooding is needed


Nodes attempt to determine how much the
network will benefit from rebroadcast


Proposed classes of solution:

1.
Probabilistic (gossiping)

2.
Counter
-
based

3.
Distance
-
based

4.
Location
-
based

5.
Cluster
-
based


WSNs require simple, low
-
resource solution

[Ni99]

Gossiping


Simple extension of flooding


Probability of rebroadcast,
p
<1


Bimodal behaviour theory


For given
p
, results are consistent


Very few nodes receive message, or almost all


Critical probability,
p
c
, at which switch occurs


Significant energy savings by setting
p

just above
p
c


Protocols modified to use gossiping perform
better (e.g. AODV+G, DSR+G)

[Haas02]

Gossiping


Bimodal behaviour formalised and analysed


p
c

varies between systems


p
c

cannot be determined analytically


Determine
p
c

for a system by simulation


Depends on reliable, accurate simulation


Simulations find no evidence of phase transition
behaviour at
p
c
, contradicting theory


Is the theory or simulation result correct?

[Sasson02]

Network Simulation


Real
-
world experiments often infeasible


Reproducible conditions


Simulated entities may not yet exist


No simulation is 100% accurate


Too little detail harms accuracy


Too much detail harms scalability

[Heidemann01, Johnson99, Kotz03]

Existing Simulators


Numerous simulators have been used in WSN
and MANET research


ns2, SeaWind, MaRS, PowerTOSSIM, TOSSF,
Tython, SensorSim, Aeon, EmStar, SENS, Avrora,
Atemu, SWAN, GloMoSim, …


Few simulators scale to large networks


Hard to partition problem for parallel simulation as any
given pair of nodes could interact at any time


Cannot manage level of simulation detail appropriately

[Biaz01, Zeng98]

The ns
-
2 and ns
-
3 Simulators


ns
-
2 widely used in network research


Does not directly execute mote code


Exponential execution time in the number of nodes


Impractical to model networks larger than 100
-
150 nodes


ns
-
3 proposed, but not yet implemented


ns
-
3 uses parallelisation for scalability, but still won’t scale
to very large networks


Using multiple processors increases capacity, perhaps to ~1000
nodes at best due to coordination overhead


Still nowhere near a million node network

[Henderson06, Das02, Naoumov03]

Simulation as a Design Tool


GP used to evolve cluster head election
algorithm in [Weise06]


Candidate algorithms evaluated for fitness
in a simulated network


Offline tuning of algorithm to a network


Simulation time restricts feasible
exploration of search space

[Weise06]

Possible Future Directions


Design for analysis


Logical structures with specialist nodes


Online evolution through GP in
-
network


Hierarchical simulation


Application
-
level protocols


Distributed scheduling


Distributed knowledge management

Conclusions


WSNs monitor hostile environments using
resource
-
constrained nodes


Communications activity is expensive


Network lifetime depends on energy
management policy


Algorithms must suit the target network


Large
-
scale simulation is vital in design,
tuning and evaluation of WSN algorithms

References

[Perkins94]

C. Perkins and P. Bhagwat, “Highly Dynamic Destination
-
Sequenced Distance
-
Vector Routing
(DSDV) for Mobile Computers”,
ACM SIGCOMM'94 Conference on Communications
Architectures, Protocols and Applications
, pages 234
-
244, 1994.

[Perkins97]

C. Perkins and E. Royer, “Ad
-
hoc On
-
Demand Distance Vector Routing”, In
MILCOM '97


panel on Ad Hoc Networks
, Nov. 1997.

[Johnson96]

D. Johnson and D. Maltz, “Dynamic Source Routing in Ad Hoc Wireless Networks”,
Mobile
Computing
, vol. 353, 1996.

[Vahdat01]

A. Vahdat and D. Becker. “Epidemic Routing for Partially Connected Ad Hoc Networks”.
Technical Report CS
-
200006, Duke University, April 2000.

[Ko98]

Y. Ko and N. Vaidya, “Location
-
Aided Routing (LAR) in Mobile Ad Hoc Networks”,
Mobile
Computing and Networking
, pages 66
-
75, 1998.

[Karp00]

B. Karp and H. Kung, “GPSR: Greedy Perimeter Stateless Routing for Wireless Networks”,
Mobile Computing and Networking
, pages 243
-
254, 2000.

[Xu01]

Y. Xu, J. Heidemann and D. Estrin, “Geography
-
informed Energy Conservation for Ad Hoc
Routing”,
Mobile Computing and Networking
, pages 70
-
84, 2001.

[Imielinski96]

T. Imielinski and J. Navas, GPS
-
Based Addressing and Routing, Computer Science, Rutgers
University, March 1996.

[Park97]

V. Park and M. Corson, “A Highly Adaptive Distributed Routing Algorithm for Mobile Wireless
Networks”,
INFOCOM 3
, pages 1405
-
1413, 1997.

References

[Weise06]

T. Weise and K. Geihs, “Genetic Programming Techniques for Sensor Networks”.
Proceedings of
5. GI/ITG KuVS Fachgesprach Drahtlose Sensornetze
, pages 21
-
25, 2006.

[Henderson06]

T. Henderson, S. Roy, S. Floyd, and G. Riley, “NS
-
3 Project Goals”. To appear in
WNS2 (Workshop
on ns
-
2: the IP Network Simulator)

October 2006.

[Beijar02]

N. Beijar, “Zone Routing Protocol (ZRP)”, unpublished.

[Royer99]

E. Royer and C. Toh, “A Review of Current Routing Protocols for Ad
-
Hoc Mobile Wireless
Networks”.
IEEE Personal Communications
, Apr. 1999.

[Zimmerman80]

H. Zimmerman, “OSI Reference Model


The ISO Model of Architecture for Open Systems
Interconnection”,
IEEE Transactions on Communications
, vol. 28, no.4, pages 425
-
432, April 1980.

[Raghunathan02]

V. Raghunathan, C. Schurgers, S. Park and M. Srivastava, “Energy
-
Aware Wireless Microsensor
Networks”,
IEEE Signal Processing Magazine
, vol. 19, no. 2, pages 40
-
50, March 2002.

[Akyildiz02]

I. Akyildiz, W. Su, Y. Sankarasubramaniam, E. Cayirci, “Wireless sensor networks: a survey”,
Computer Networks
, no. 38, pages 393
-
422, 2002.

[Culler04]

D. Culler, D. Estrin and M. Srivastava, “Overview of Sensor Networks”,
IEEE Computer
, vol. 37,
no. 8, pages 41
-
49, August 2004.

[Heinzelman99]

W. Heinzelman, J. Kulik and H. Balakrishnan, “Adaptive protocols for information
dissemination in wireless sensor networks”, In
Proceedings of MOBICOM 1999
, Seattle, 174
-
185,
1999.

References

[Ni99]

S. Ni, Y. Tseng, Y. Chen, and J. Sheu. “The Broadcast Storm Problem in a Mobile Ad Hoc
Network”.
Proceedings of the Fifth Annual ACM/IEEE International Conference on Mobile Computing
and Networking
, pages 151
-
162, Aug 1999.

[Sasson03]

Y. Sasson, D. Cavin, and A. Schiper. “Probabilistic Broadcast for Flooding in Wireless Mobile Ad
Hoc Networks”.
Proceedings of IEEE Wireless Communications and Networking Conference (WCNC
2003)
. 2003.

[Haas02]

L. Li and J. Halpern and Z. Haas. “Gossip
-
Based Ad Hoc Routing”, unpublished.

[Ganesan02]

D. Ganesan, B. Krishnamachari, A. Woo, D. Culler, D. Estrin, S. Wicker. “Complex Behavior at
Scale: An Experimental Study of Low
-
Power Wireless Sensor Networks”. Technical Report
CSD
-
TR 02
-
0013, UCLA, February 2002.

[Hall99]

E. Hall. “
Internet Core Protocols
”. O’Reilly, Sebastopol, CA, 2000.

[Club04]

Intel Editor’s Day 2004,
http://www.clubedohardware.com.br/artigos/119/2

[Polastre03]

Wireless Sensor Networks for Habitat Monitoring (abstract),
http://www.eecs.berkeley.edu/IPRO/Summary/03abstracts/chapter6.html

[Crossbow06]

Crossbow MICA2 900MHz,
http://www.xbow.com/Products/productdetails.aspx?sid=174

[Chen01]

B. Chen, K. Jamieson, H. Balakrishnan, R. Morris, “Span: An Energy
-
Efficient Coordination
Algorithm for Topology Maintenance in Ad Hoc Wireless Networks”,
Mobile Computing and
Networking
, pages 85
-
96, 2001.

References

[Berkeley03]

ForeFront Fall 2003,
http://www.coe.berkeley.edu/forefront/fall2003/breakthroughs.html

[Jones01]

C. Jones, K. Sivalingam, P. Agrawal, and J. Chen, “A Survey of Energy Efficient Network
Protocols for Wireless Networks”,
Wireless Networks
, vol. 7, no. 4, pages 343
-
358, 2001.

[Singh98]

S. Singh, M. Woo, and C. Raghavendra, “Power
-
Aware Routing in Mobile Ad Hoc Networks”,
Mobile Computing and Networking
, pages 181
-
190, 1998.

[Weiser94]

M. Weiser, B. Welch, A. Demers, and S. Shenker, “Scheduling for Reduced CPU Energy”,
Operating Systems Design and Implementation
, pages 13
-
23, 1994.

[Shah02]

R. Shah, J. Rabaey, “Energy Aware Routing for Low Energy Ad Hoc Sensor Networks”, In
Proceedings of IEEE Wireless Communications and Networking Conference (WCNC)
, Orlando, FL,
March 2002.

[Stojmenovic01]

I. Stojmenovic and X. Lin, “Power
-
aware localized routing in wireless networks”,
IEEE
Transactions on Parallel and Distributed Systems
, vol. 12, no. 11, pages 1122
-
1133, 2001.

[Biaz01]

S. Biaz, G. Holland, Y. Ko and N. Vaidya, “Evaluation of Protocols for Wireless Networks”,
unpublished.

[Broch98]

J. Broch, D. Maltz, D. Johnson, Y. Hu and J. Jetcheva, “A Performance Comparison of Multi
-
Hop
Wireless Ad Hoc Network Routing Protocols”,
Mobile Computing and Networking
, pages 85
-
97, 1998.

[Chiang97]

C. Chiang, H. Wu, W. Liu and M. Gerla, “Routing in Clustered Multihop, Mobile Wireless
Networks With Fading Channel”, In
Proceedings of IEEE SICON'97
, pages 197
-
211, 1997.

References

[Das00]

S. Das, C. Perkins and E. Royer, “Performance Comparison of Two On
-
demand Routing
Protocols for Ad Hoc Networks”,
INFOCOM 1
, pages 3
-
12, 2000.

[Intanagonwiwat00]

C. Intanagonwiwat, R. Govindan and D. Estrin, “Directed diffusion: a scalable and robust
communication paradigm for sensor networks”,
Mobile Computing and Networking
, pages
56
-
67, 2000.

[Ratnasamy02]

S. Ratnasamy, B. Karp, L. Yin, F. Yu, D. Estrin, R. Govindan, and S. Shenker, “GHT: A
Geographic Hash Table for Data
-
Centric Storage in SensorNets”, In
Proceedings of the First
ACM International Workshop on Wireless Sensor Networks and Applications (WSNA)
, Atlanta,
Georgia, September 2002.

[Szewczyk04]

R.Szewczyk, J. Polastre, A. Mainwaring and D. Culler, “Lessons From A Sensor Network
Expedition”, In
Proceedings of the First European Workshop on Sensor Networks (EWSN)
,
January 2004.

[Heidemann01]

J. Heidemann, N. Bulusu, J. Elson, C. Intanagonwiwat, K. Lan, Y. Xu, W. Ye, D. Estrin, and R.
Govindan. “Effects of detail in wireless network simulation”. In
Proceedings of the SCS
Multiconference on Distributed Simulation
, pages 3
-
11, January 2001.

[Naoumov03]

V. Naoumov and T. Gross. “Simulation of large ad hoc networks”. In
Proceedings of
MSWIM'03
, pages 50
-
57. ACM Press, 2003.

[Zeng98]

Xiang Zeng and Rajive Bagrodia and Mario Gerla. “GloMoSim: A Library for Parallel
Simulation of Large
-
Scale Wireless Networks”,
Workshop on Parallel and Distributed
Simulation
, pages 154
-
161, 1998

References

[Johnson99]

D. Johnson. “Validation of wireless and mobile network models and simulation”. In
Proceedings of the DARPA/NIST Network Simulation Validation Workshop
, Fairfax, Virginia, USA,
May 1999.

[Kotz03]

D. Kotz, C. Newport and C. Elliot, “The mistaken axioms of wireless
-
network research”,
Dartmouth College Computer Science Technical Report TR2003
-
467, July 2003.

Questions


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