The document discusses energy efficient techniques for data collection in wireless sensor networks using TDMA protocols. It first reviews related work on constructing efficient data gathering trees and exploiting spatial-temporal correlations. It then examines the fundamental limitations of interference and half-duplex radios with TDMA. The paper proposes a fast convergecast algorithm for tree-based WSNs using TDMA to minimize schedule length and addresses techniques to overcome interference limitations. In conclusion, the algorithm is found to be energy efficient for data collection in WSNs using TDMA protocols.

1. Prepared by
Gaikwad Manjusha R.(M.tech )

2. Introduction
Literature survey
SINR Definition & its constraints
Comparision model
CDMA/CA
Backoff Algorithm
TDMA
Tree formation protocol
Merits & Demerits ofTDMA
Presentation Outline

3.  WSN
 SINR
 SNIR
 SNR
 SIR
Introduction

4. Titel of paper Author Publication Year of
publication
Findings
On the
construction of
efficient data
gathering tree
in wireless
sensor
Networks
N.Thepvilojana
pong, Y. Tobe
and K. Sezaki
IEEE ISCAS,
pp. 648-651.
May 2005. Constructed a
data gathering
tree that
maximize
network lifetime
An energy-
efficient data
collection
framework for
wireless sensor
networks by
exploiting
spatiotemporal
correlattion
C. Liu, K. Wu
and J
IEEE Trans.
Parallel and
Distributed
Systems,
pp. 1010-1023
Jul. 2007 An efficient data
gathering
appoarch is
implemented by
combining the
dual prediction &
Clustering
algorithm
Analyzing the
transitional
region in
low power
wireless links
M. Zuniga and B.
Krishnamachari
IEEESECON,
pp. 517-526
Oct 2004 a systematic
medium-scale
measurement of
packet delivery
in three

5. Titel of paper Author Publication Year of
publication
Findings
Topology control
meets SINR: the
scheduling
complexity of
arbitrary
Topologies
T. Moscibroda,
R.Wattenhofer
and A. Zollinger
ACM MobiHoc,
pp. 310-321
May 2006. Analysis on
topology control
in the context of
the physical
Signal-to-
Interference-
plus-Noise-Ratio
(SINR)
model, focusing
on the question
of how and how
fast the
links of a
resulting
topology can
actually be
realized over
time.
Joint power
control and link
L. Fu, C. Liew
and J. Huang
IEEE ICC, pp.
3066-3072
May 2008. the
minimum-length

6. Title of paper Author publication Year of
publication
Findings
Optimum
integrated link
scheduling an
power control
for multihop
wireless
networks
A. Behzad and I.
Rubin
IEEETrans.
vehicular
Technology, pp.
194-205
Jan.2007 The joint
routing,
link scheduling
and power
control to
support high
data rates
for broadband
wireless multi-
hop networks.

7. Mathematical definition=
SINR(x)= P
SINR Constraints
I+N

9. Protocol Model
Physical Model
-Interference model(SINR)
Comparision Model

10. CSMA/CA -
D-MAC
B-MAC
B-MAC+
X-MAC
TDMA
MAC Protocols

11. Gives waiting time for the station
Waiting time=K*51.2 micro sec
n
k= 0 to 2 - 1
Backoff Algorithm for CSMA/CD

12. D-MAC
Fig-Active and sleep period of D-MAC

13. B-MAC
Fig-Preamble in B-MAC, B-MAC+, X-MAC

14.  LEACH(low energy adaptive clustering hierarchy)
 PEGASIS(power-efficient gathering in sensor
information system)
 Hierarchical-PEGASIS
Hierarchical routing approaches for
sensor networks

15. Tree formation using CSMA/CA protocol

16. Fig: Average Message Success Rate observed from nodes at the
same level of the collection tree when using B-MAC

17. Fig: Average Latency of Messages Received at CP from nodes at different
levels of the collection tree when using B-MAC.

18. Fig: Message Success Rate decreases as the number of transmissions
increaseThis is because the number of collisions increase.

19.  Efficient Transmission
 Data & Voice Communication
 Carry Data Rates
 Cost effective Technology
 Extended Battery life
 Efficient Utilization of hierarchical cell
structure
Advantages ofTDMA

20.  PredefinedTime Slots
 Multipath Distortion
 Synchronization
Disadvantages OfTDMA

21. The proposed algorithm is energy efficient In
this paper, we studied fast convergecast in WSN where
nodes communicate using a TDMA protocol to minimize
the schedule length. We addressed the fundamental
limitations due to interference and half-duplex
transceivers on the nodes and explored techniques t
overcome the same.
CONCLUSION

22. [1] N. Thepvilojanapong, Y. Tobe and K. Sezaki, “On the construction of
efficient data gathering tree in wireless sensor networks,” IEEE ISCAS,
pp. 648-651, May 2005.
[2] C. Liu, K. Wu and J. Pei, “An energy-efficient data collection framework
for wireless sensor networks by exploiting spatiotemporal
correlation,”IEEE Trans. Parallel and Distributed Systems, pp. 1010-1023,
Jul. 2007.
[3] M. Zuniga and B. Krishnamachari, “Analyzing the transitional region in
low power wireless links,” IEEE SECON, pp. 517-526, Oct. 2004.
[4] H. Choi, J. Wang and E. A. Hughes, “Scheduling for information
gathering on sensor network,” Wireless Networks, vol. 15, pp. 127-140,
Jan. 2009
References

23. [5] O. Durmaz Incel, A. Ghosh, B. Krishnamachari and K. Chintalapudi,
“Fast data collection in tree-based wireless sensor networks,”
IEEE Trans. Mobile Computing, vol. 11, no. 1, pp. 86-99, Jan. 2012.
[6] O. Goussevskaia,Y.A. Oswald and R. Wattenhofer, “Complexity in
geometric SINR,” ACM MobiHoc, pp. 100-109, September 2007.
[7] S. Kompella, J. E. Wieselthier and A. Ephremides, “A cross-layer
approach to optimal wireless link scheduling with SINR constraints,”
IEEE Military Communications Conference, pp. 1-7, Oct. 2007.
[8] T. Moscibroda, R. Wattenhofer and A. Zollinger,
“Topology control meets SINR: the scheduling complexity of arbitrary
Topologies,”ACM MobiHoc, pp. 310-321, May 2006.
References

24. [9] A. Behzad and I. Rubin, “Optimum integrated link
scheduling and
power control for multihop wireless networks,” IEEETrans.
vehicularTechnology, pp. 194-205, Jan. 2007.
[10] L. Fu, C. Liew and J. Huang, “Joint power control and link
scheduling in wireless networks for throughput
optimization,”
IEEE ICC, pp. 3066-3072, May 2008.

25. Thank You