123

1. ENHANCEMENT OF MEDIUM ACCESS
CONTROL FOR WIRELESS SENSOR
NETWORK
 DONE BY GUIDED BY
 K.MANOJKUMAR , Mr.S.ILANGOSAMBASIVAN,
II M.E(CS) prof.,ECE dept,SIET

2. Objective
 To propose a correlation based collaborative
MAC protocol –SCC-MAC
 To reduce energy consumption of the network

3. Existing Works
S.NO ABSTRACT AUTHOR YEAR
1. Variable duty cycle,
shorter for high and
longer for low traffic
Justin T.kautz,
Barry
E.Mullins
2007
2. By grouping sensor
nodes-cluster
header selection
algorithm
Inbo sim,
KoungJin
choi, koungJin
kwon
2009
3. Adoptable for
various traffic
condition
Philipp Hurni,
Torsten Braun
2009

4. Blocks Diagram For Proposed
SCC-MAC Protocol

5. Iterative Node Selection (INS)
Algorithm
 INS algorithm is used to find the number and
location of the representative nodes in WSN.
 The INS algorithm requires only the statistical
properties of the node distribution as input and
provides a correlation radius value for distributed
operation as output.

6. Proposed SCC-MAC Protocol
 To prevent the transmission of redundant
information about an event and prioritize the
forwarding of filtered data to the sink
 Number of nodes sending information about an
event is decreased

7. Continue..
 Proposed SCC-MAC protocol contains two
components corresponding to the source and
router functionalities
 Event MAC (E-MAC) filters out the correlated
records
 Network MAC (N-MAC) ensures prioritization of
route-thru packets
 Both E-MAC and N-MAC use a CSMA/CA
based medium access control

8. Continue..
 The information about correlation formation is
embedded inside the RTS/CTS/DATA/ACK
packets. No need of additional packets.
 A bit in the reserved space of RTS, CTS and
DATA packet structures is used as a new field
called First Hop (FH) Field.
 Based on information present in the FH field, E-
MAC and N-MAC will perform.

9. Packet Format

10. E-MAC & N-MAC Implementation

11. E-MAC Implementation

12. E-MAC & N-MAC Implementation

13. Output:1
 Average Energy consumption
 It is the average energy a sensor node consumes
during the simulation
 The initial energy is indicated in main.tcl file, using
that value we can draw the graph.

14. Energy consumption

15. Output:2
 Goodput
 The ratio between the total number of packets
received at the sink and the total number of packets
generated by all sensor nodes.

16. Good Put

17. Output:3
 Drop Rate
 It is the percentage of dropped packets to the total
packets sent throughout the simulation.

18. Drop Rate

19. Conclusion
 Exploiting spatial correlation at the MAC layer is
a powerful means of reducing the energy
consumption in WSN
 By allowing only a subset of sensor nodes to
transmit their data to the sink, the proposed MAC
protocol not only conserves energy, but also
minimizes unnecessary channel access contention
and thereby improves the packet drop rate without
compromising the event detection latency.

20. Continue..
 Using simulations, the performance of the
Proposed SCC-MAC protocol is investigated and
significant performance gains in terms of Energy
Consumption, Goodput and Packet Drop Rate are
shown.

21. Future Work
 For multiple types of traffic in WSN, SCC-MAC
protocol can be modified using multiple
correlation radius values for each phenomenon.
 The quality of service requirements of various
types of sensor information needs to be
considered as a future work.

22. Reference
 [1]“Spatial Correlation-Based Collaborative Medium Access Control in
Wireless Sensor Networks”, Mehmet C. Vuran, Member, IEEE, and Ian F.
Akyildiz, Fellow, IEEE,2006
 [2] “An Adaptable Energy-Efficient Medium Access Control Protocol for
Wireless Sensor Networks”, Justin T. Kautz, Barry E. Mullins, Rusty O.
Baldwin, Scott R. Graham, 2007
 [3] “Energy Efficient Cluster header Selection Algorithm in WSN”, Inbo
Sim, KoungJin Choi, KoungJin Kwon and Jaiyong Lee, 2008
 [4] “On the Adaptivity of today’s Energy-Efficient MAC Protocols under
varying Traffic Conditions”, Philipp Hurni, Torsten Braun, 2009
 [5] “Energy Efficient and Delay Optimized TDMA Scheduling for
Clustered Wireless Sensor Networks”, Liqi Shi and Abraham O. Fapojuwo,
2009

23. Continue..
 [6] “Energy Efficient Cross-Layer MAC Protocol for Wireless Sensor
Networks”, Bouabdellah KECHAR, Ahmed LOUAZANI, Larbi SEKHRI,
Mohamed Faycal KHELFI, 2008
 [7] “Energy Efficient Token Based MAC Protocol for Wireless Sensor
Networks”, Soumya Ray, ,Subhasis Dash ,Nachiketa Tarasia ,Anuja Ajay,
Amulya Ratan Swain, 2011
 [8] “Wireless Sensor Networks:Delay Guarentee and Energy Efficient
MAC Protocols”, Marwan Ihsan Shukur, Lee Sheng Chyan, Vooi Voon
Yap, 2009
 [9] “ M. Gastpar and M. Vetterli, “Source-channel communication in
sensor networks,” Proc. 2nd Int. Workshop on Information Processing in
Sensor Networks (IPSN’03), vol. 219, pp. 162–177, 2003.
 [10] M. C. Vuran, Ö. B. Akan, and I. F. Akyildiz, “Spatio-temporal
correlation: theory and applications for wireless sensor networks,” Comput.
Netw. J. (Elsevier), vol. 45, no. 3, pp. 245–259, Jun. 2004


24. Continue..
 [11] Mehmet C. Vuran, Member and Ian F. Akyildiz, Fellow,” Spatial
Correlation-Based Collaborative Medium Access Control in Wireless
Sensor Networks”,2004
 [12] K. A. Arisha, M. A. Youssef, and M. Y. Younis, “Energy-aware
TDMA-based MAC for sensor networks,” Comput. Netw. J. (Elsevier), vol.
43, no. 5, pp. 539–694, Dec. 2003.
 [13] S. Bandyopadhyay and E. J. Coyle, “Spatio-temporal sampling rates
and energy efficiency in wireless sensor networks,” in Proc. IEEE
INFOCOM, Mar. 2004, vol. 3, pp. 1728–1739.
 [14] “Power, spatio-temporal bandwidth, and distortion in large sensor
networks,” IEEE J. Sel. Areas Commun., vol. 23, no. 4, pp. 745–754, Apr.
2005.
 [15] W. Ye, J. Heidemann, and D. Estrin, “Medium access control with
coordinated adaptive sleeping for wireless sensor networks,” IEEE/ACM
Trans. Netw., vol. 12, no. 3, pp. 493–506, Jun. 2004.

25. Thank you