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Mistry Jolly et al Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 4, Issue 5( Version 3), May 2014, pp.68-71
www.ijera.com 68 | P a g e
Meliorated Outcomeinwsn Using Better CH Selection by
Weighted Parameters
Mistry Jolly and Prof. Gurcharan Sahani
Abstract
In recent era, the research for improving the performance of the WSN is done in the „speed of light‟. LEACH is
the protocol which has changed the scenario of using WSN for any application like monitoring physical
parameters, measuring parameters surveillance etc. Also LEACH-C can be used for the same with some
modifications in LEACH like deciding CH centrally in fixed amount. But there is a con of LEACH; it decides
the CH based on random generation value. Therefore, in proposed scheme, threshold is calculated using
weighted parameter of residual energy and distance from the base station.
Keywords: WSN-Wireless sensor network, LEACH, NS2, residual energy
I. Introduction
For the applications like measuring and
monitoring the physical parameters and surveillance,
WSN is used. The research in this area is growing
day by day. LEACH, very well known for WSN, uses
clustering method for WSN. By clustering, the
lifetime of energy can be increased compare to MTE
[1]. LEACH-C is the expansion of LEACH which
uses clustering done by BS centrally. But in both
protocols we find cons like LEACH decides CH
based on threshold value which has one value
randomly generated. While LEACH-C has advantage
over LEACH that it uses fixed amount of CH. But
LEACH-C has same disadvantage like it uses central
information after each round and it has same
threshold value equation. So we proposed new
scheme in which the no. of CH remains constant and
it finds better CH using weighted threshold value
calculated by residual energy and distance from the
base station. Hence, CH is far more comparable with
previous two protocols i.e. LEACH and LEACH-C.
In proposed scheme, the CH is decided by
residual energy consideration so as to make this
decision better. Residual energy is the energy which
can be defined as the ratio of current energy to the
initial energy. Also CH is having important weight of
distance of node to distance from the base station.
Fig. 1 Clustered architecture of WSN
The paper includes in following section
related work on LEACH and LEACH-C. Section 3
has brief description about proposed scheme and
section 4 and 5 includes Simulation results and result
analysis.
II. Related Work
A. LEACH
LEACH is protocol in which the clustering
is done among all the sensor nodes as shown in figure
1. LEACH protocol works in two phases 1. Set up
phase and 2. Steady state phase.
Fig. 2: working of LEACH in two phases
1. Set up phase:
In set up phase, the clustering process
among all the nodes is being done. The sensor nodes
first calculate the threshold value and depending on
this threshold value it advertises its CH status. The
RESEARCH ARTICLE OPEN ACCESS
Mistry Jolly et al Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 4, Issue 5( Version 3), May 2014, pp.68-71
www.ijera.com 69 | P a g e
threshold value can be calculated by following
equation
𝑇 𝑛 =
𝑝
1 − 𝑟 𝑚𝑜𝑑
1
𝑝
𝑝 ∈ 𝐺
0 𝑒𝑙𝑠𝑒
Where T(n) is threshold value for nth
node
for particular round. P is probability of node to be CH
and r is random no. generated by the node. G is se tof
possible CH which were not CH in previous round.
The nodes with highest threshold value will
advertise their CH status. Remaining node will
receive this status and it will respond the tentative
CH taking into consideration the distance of that
node from own. In response to this CH advertisement
it will send Join request to corresponding CH node.
Hence the cluster will be formed. Now, duty of CH is
to create TDMA schedule for all the cluster members
and give them a particular time slot.
Fig 3: Flow chart of Set up phase in LEACH
2. Steady State Phase:
In steady state phase all the cluster members
will send their data to their CHs. CHs will receive the
data and aggregate this data. After aggregation it will
send these data bytes to BS.
B. LEACH-C
LEACH-C has same working like LEACH.
In LEACH-C the clustering is done centrally. CHs
are decided by BS based on the distance of the node
from BS. BS can decide the distance of the node by
GPS receiver. So here set up phase of LEACH-C will
change remaining procedure is same as LEACH.
III. Proposed Scheme
The proposed scheme work in two phases
set up phase and steady state phase. The steady state
phase of the proposed is same as LEACH and
LEACH-C.
There is some variation in set up phase for
selection procedure of CH for each round. Before,
network initialization it is assumed that each node
knows its distance from the BS. For this either BS
can broadcast one packet having vectors of distance
from the BS from all nodes or each node may have
GPS system built in.
In proposed scheme, the CH is decided on
the bases of threshold value which will be calculated
on the weighted value of residual energy and distance
of the node from the BS.
So the equation becomes
𝑇 𝑛 =
𝑝
1 − 𝑟′ 𝑚𝑜𝑑
1
𝑝
𝑝 ∈ 𝐺
0 𝑒𝑙𝑠𝑒
Where r‟ will be calculated as below
𝑟′
= 𝑤1 ∗ 𝐸𝑟𝑒𝑠𝑠𝑖𝑑𝑢𝑎𝑙 + 𝑤2 ∗ 𝐷𝑖𝑠𝑡𝑎𝑛𝑐𝑒_𝐹𝑟𝑜𝑚_𝐵𝑆
Here w1 and w2are the weight factors. For the
proposed scheme, we have taken the values of w1 and
w2 equal and half i.e. 0.5
Eressidual can be calculated by taking the ratio of
current energy of the node to the initial energy of that
node.
So the calculated value of threshold will be
improved value.
Threshold value includes the probability of
node to be cluster head for nth
round and if it belongs
to set G which denotes the set of nodes which were
not CHs in last node.
IV. Simulation Results
Fig. 4 shows the graph for Time V/s No. of
nodes alive for particular simulation time. It helps to
decide lifetime of the network. From this, we can
observe that, life time of network is higher for
LEACH compare to LEACH-C. Here, proposed
scheme gives improved lifetime of 15-20%compare
to LEACH. So the network can work for more time.
Mistry Jolly et al Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 4, Issue 5( Version 3), May 2014, pp.68-71
www.ijera.com 70 | P a g e
Figure 4 Plot for Time V/s No. of nodes alive
Fig. 5 shows the graph of Time V/s Data
Bytes received at BS. LEACH-C has advantage over
LEACH that amount of data transferred will be high
in case of LEACH-C. As we can see the proposed
scheme, it has almost same or more than LEACH-C
amount of data bytes transferred to the BS.
Figure 5 Plot of Time V/s Data Bytes received at BS
Figure 6 Plot of amount of data transfer v/s No. of
nodes alive
Fig. 6 shows the amount of data transferred
to BS V/s No. of nodes alive. As we can see from the
graph the proposed scheme has more average no. of
data bytes received per node.
Figure 7 Comparative Analysis of LEACH and
Proposed Method
Fig. 7 shows the comparative analysis of
LEACH, LEACH-C and proposed scheme. The
results have been generated for 5 different times
simulation runs. In each simulation we can see the
amount of data received and lifetime of the network
is increased for proposed scheme. And we are
gaining the advantage of the LEACH-C in energy
dissipation. The energy dissipation in proposed
scheme is less than LEACH and LEACH-C.
V. Conclusion
Because of better selection of CH, the
lifetime of the network is increased, number of nodes
alive over time is increased and energy consumption
is reduced. From simulation, it can be observed that
lifetime of the network is increased by 20-25
percentage. Also with use of better CH selection, we
can receive more number of data bytes at BS. The
data received at BS for proposed is increased by 10
percent as compared to traditional protocol. Also, as
time increased, the no. of data received at BS will
more compare to LEACH and LEACH-C.
REFERENCES
[1] Brett A. Warneke, Kristofer S.J. Pister,”
MEMS for Distributed Wireless Sensor
Networ University of California at Berkeley.
[2] I. F. Akyildiz, W.Su, Y. Sankara
subramaniam, and E. Cayirci, “Wireless
sensor networks: asurvey”, Computer
Networks 38, Elsevier,pp.393–422,2002.
[3] C.Perkins, Ad Hoc Networks, Addison-
Wesley, Reading, MA, 2000.
[4] W. Heinzelman, J. Kulik, and H.
Balakrishnan,”Adaptive Protocols for
Information Dissemination in Wireless
Sensor Networks,” Proc. 5th
ACM/IEEE Mobicom Conference
(MobiCom ‟99), Seattle, WA, August,
1999. pp.174-85.
[5] J. Kulik, W. R. Heinzelman, and H.
Balakrishnan, ”Negotiation-based
protocols for disseminating information
in wireless sensor networks,” Wireless
Networks, Volume: 8, pp.169-185,
2002.
Mistry Jolly et al Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 4, Issue 5( Version 3), May 2014, pp.68-71
www.ijera.com 71 | P a g e
[6] C. Intanagonwiwat, R. Govindan, and
D. Estrin, ”Directed diffusion: a
scalable and robust communication
paradigm for sensor networks,”
Proceedings of ACM MobiCom ‟00,
Boston, MA, 2000, pp. 56-67.
[7] W. Heinzelman, A. Chandrakasanand
H. Balakrishnan, ”Energy-Efficient
Communication Protocol for Wireless
Mi- crosensor Networks,” Proceedings
of the 33rd Hawaii International
Conference on System Sciences
(HICSS ‟00), January 2000.
[8] S. Lindsey, C. Raghavendra,
“PEGASIS: Power-Efficient Gathering
in Sensor Information Systems”, IEEE
Aerospace Conference Proceedings,
2002, Vol. 3, 9-16 pp. 1125-1130.
[9] A. Savvides, C-C Han, aind M. Srivastava,
“Dynamic fine-grained localization in Ad-
Hoc networks of sensors,” Proceedings of
the Seventh ACM Annual International
Conference on Mobile Computing and
Networking (Mobi Com), July 2001. pp.
166-179.
[10] W. Heinzelman, A. Chandrakasan, and H.
Balakrishnan, ”Energy-efficient routing
protocols for wireless microsensor
networks, ” in Proc. 33rdHawaii Int. Conf.
SystemSciences(HICSS), Maui, HI,Jan.
2000.
[11] Wendi B Heinzelman, A P Chandrakasan,
Hari Balakrishnan,”An application-specific
protocol architecture on wireless
microsensor networks", IEEE transaction on
wireless communications, 2002, PP. 660-
670.
[12] V. Loscr, G. Morabito, S. Marano, “A Two-
Levels Hierarchy for Low-Energy Adaptive
Clustering Hierarchy (TL-LEACH)",
Vehicular Tech-nology Conference, 2005.
[13] Thiemo Voigt, Hartmut Ritter, Jochen
Schiller, Adam Dunkels, and Juan Alonso,”
Solar-aware Clustering in Wireless Sensor
Networks”, In Proceedings of the Ninth
IEEE Symposium on Computers and
Communications, June 2004.
[14] Rajashree.V.Biradar, Dr. S.R. Sawant, Dr.
R. R. Mudholkar , Dr. V.C .Patil ”Multihop
Routing In Self-Organizing Wireless Sensor
Networks”IJCSI International Journal of
Computer Science Issues, Vol. 8, Issue
1,January 2011.
[15] Hu Junping, Jin Yuhui, “A Time-based
Cluster-Head Selection Algorithm for
LEACH” IEEE Symposium Computers and
Communications (ISCC), 2008.

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  • 1. Mistry Jolly et al Int. Journal of Engineering Research and Applications www.ijera.com ISSN : 2248-9622, Vol. 4, Issue 5( Version 3), May 2014, pp.68-71 www.ijera.com 68 | P a g e Meliorated Outcomeinwsn Using Better CH Selection by Weighted Parameters Mistry Jolly and Prof. Gurcharan Sahani Abstract In recent era, the research for improving the performance of the WSN is done in the „speed of light‟. LEACH is the protocol which has changed the scenario of using WSN for any application like monitoring physical parameters, measuring parameters surveillance etc. Also LEACH-C can be used for the same with some modifications in LEACH like deciding CH centrally in fixed amount. But there is a con of LEACH; it decides the CH based on random generation value. Therefore, in proposed scheme, threshold is calculated using weighted parameter of residual energy and distance from the base station. Keywords: WSN-Wireless sensor network, LEACH, NS2, residual energy I. Introduction For the applications like measuring and monitoring the physical parameters and surveillance, WSN is used. The research in this area is growing day by day. LEACH, very well known for WSN, uses clustering method for WSN. By clustering, the lifetime of energy can be increased compare to MTE [1]. LEACH-C is the expansion of LEACH which uses clustering done by BS centrally. But in both protocols we find cons like LEACH decides CH based on threshold value which has one value randomly generated. While LEACH-C has advantage over LEACH that it uses fixed amount of CH. But LEACH-C has same disadvantage like it uses central information after each round and it has same threshold value equation. So we proposed new scheme in which the no. of CH remains constant and it finds better CH using weighted threshold value calculated by residual energy and distance from the base station. Hence, CH is far more comparable with previous two protocols i.e. LEACH and LEACH-C. In proposed scheme, the CH is decided by residual energy consideration so as to make this decision better. Residual energy is the energy which can be defined as the ratio of current energy to the initial energy. Also CH is having important weight of distance of node to distance from the base station. Fig. 1 Clustered architecture of WSN The paper includes in following section related work on LEACH and LEACH-C. Section 3 has brief description about proposed scheme and section 4 and 5 includes Simulation results and result analysis. II. Related Work A. LEACH LEACH is protocol in which the clustering is done among all the sensor nodes as shown in figure 1. LEACH protocol works in two phases 1. Set up phase and 2. Steady state phase. Fig. 2: working of LEACH in two phases 1. Set up phase: In set up phase, the clustering process among all the nodes is being done. The sensor nodes first calculate the threshold value and depending on this threshold value it advertises its CH status. The RESEARCH ARTICLE OPEN ACCESS
  • 2. Mistry Jolly et al Int. Journal of Engineering Research and Applications www.ijera.com ISSN : 2248-9622, Vol. 4, Issue 5( Version 3), May 2014, pp.68-71 www.ijera.com 69 | P a g e threshold value can be calculated by following equation 𝑇 𝑛 = 𝑝 1 − 𝑟 𝑚𝑜𝑑 1 𝑝 𝑝 ∈ 𝐺 0 𝑒𝑙𝑠𝑒 Where T(n) is threshold value for nth node for particular round. P is probability of node to be CH and r is random no. generated by the node. G is se tof possible CH which were not CH in previous round. The nodes with highest threshold value will advertise their CH status. Remaining node will receive this status and it will respond the tentative CH taking into consideration the distance of that node from own. In response to this CH advertisement it will send Join request to corresponding CH node. Hence the cluster will be formed. Now, duty of CH is to create TDMA schedule for all the cluster members and give them a particular time slot. Fig 3: Flow chart of Set up phase in LEACH 2. Steady State Phase: In steady state phase all the cluster members will send their data to their CHs. CHs will receive the data and aggregate this data. After aggregation it will send these data bytes to BS. B. LEACH-C LEACH-C has same working like LEACH. In LEACH-C the clustering is done centrally. CHs are decided by BS based on the distance of the node from BS. BS can decide the distance of the node by GPS receiver. So here set up phase of LEACH-C will change remaining procedure is same as LEACH. III. Proposed Scheme The proposed scheme work in two phases set up phase and steady state phase. The steady state phase of the proposed is same as LEACH and LEACH-C. There is some variation in set up phase for selection procedure of CH for each round. Before, network initialization it is assumed that each node knows its distance from the BS. For this either BS can broadcast one packet having vectors of distance from the BS from all nodes or each node may have GPS system built in. In proposed scheme, the CH is decided on the bases of threshold value which will be calculated on the weighted value of residual energy and distance of the node from the BS. So the equation becomes 𝑇 𝑛 = 𝑝 1 − 𝑟′ 𝑚𝑜𝑑 1 𝑝 𝑝 ∈ 𝐺 0 𝑒𝑙𝑠𝑒 Where r‟ will be calculated as below 𝑟′ = 𝑤1 ∗ 𝐸𝑟𝑒𝑠𝑠𝑖𝑑𝑢𝑎𝑙 + 𝑤2 ∗ 𝐷𝑖𝑠𝑡𝑎𝑛𝑐𝑒_𝐹𝑟𝑜𝑚_𝐵𝑆 Here w1 and w2are the weight factors. For the proposed scheme, we have taken the values of w1 and w2 equal and half i.e. 0.5 Eressidual can be calculated by taking the ratio of current energy of the node to the initial energy of that node. So the calculated value of threshold will be improved value. Threshold value includes the probability of node to be cluster head for nth round and if it belongs to set G which denotes the set of nodes which were not CHs in last node. IV. Simulation Results Fig. 4 shows the graph for Time V/s No. of nodes alive for particular simulation time. It helps to decide lifetime of the network. From this, we can observe that, life time of network is higher for LEACH compare to LEACH-C. Here, proposed scheme gives improved lifetime of 15-20%compare to LEACH. So the network can work for more time.
  • 3. Mistry Jolly et al Int. Journal of Engineering Research and Applications www.ijera.com ISSN : 2248-9622, Vol. 4, Issue 5( Version 3), May 2014, pp.68-71 www.ijera.com 70 | P a g e Figure 4 Plot for Time V/s No. of nodes alive Fig. 5 shows the graph of Time V/s Data Bytes received at BS. LEACH-C has advantage over LEACH that amount of data transferred will be high in case of LEACH-C. As we can see the proposed scheme, it has almost same or more than LEACH-C amount of data bytes transferred to the BS. Figure 5 Plot of Time V/s Data Bytes received at BS Figure 6 Plot of amount of data transfer v/s No. of nodes alive Fig. 6 shows the amount of data transferred to BS V/s No. of nodes alive. As we can see from the graph the proposed scheme has more average no. of data bytes received per node. Figure 7 Comparative Analysis of LEACH and Proposed Method Fig. 7 shows the comparative analysis of LEACH, LEACH-C and proposed scheme. The results have been generated for 5 different times simulation runs. In each simulation we can see the amount of data received and lifetime of the network is increased for proposed scheme. And we are gaining the advantage of the LEACH-C in energy dissipation. The energy dissipation in proposed scheme is less than LEACH and LEACH-C. V. Conclusion Because of better selection of CH, the lifetime of the network is increased, number of nodes alive over time is increased and energy consumption is reduced. From simulation, it can be observed that lifetime of the network is increased by 20-25 percentage. Also with use of better CH selection, we can receive more number of data bytes at BS. The data received at BS for proposed is increased by 10 percent as compared to traditional protocol. Also, as time increased, the no. of data received at BS will more compare to LEACH and LEACH-C. REFERENCES [1] Brett A. Warneke, Kristofer S.J. Pister,” MEMS for Distributed Wireless Sensor Networ University of California at Berkeley. [2] I. F. Akyildiz, W.Su, Y. Sankara subramaniam, and E. Cayirci, “Wireless sensor networks: asurvey”, Computer Networks 38, Elsevier,pp.393–422,2002. [3] C.Perkins, Ad Hoc Networks, Addison- Wesley, Reading, MA, 2000. [4] W. Heinzelman, J. Kulik, and H. Balakrishnan,”Adaptive Protocols for Information Dissemination in Wireless Sensor Networks,” Proc. 5th ACM/IEEE Mobicom Conference (MobiCom ‟99), Seattle, WA, August, 1999. pp.174-85. [5] J. Kulik, W. R. Heinzelman, and H. Balakrishnan, ”Negotiation-based protocols for disseminating information in wireless sensor networks,” Wireless Networks, Volume: 8, pp.169-185, 2002.
  • 4. Mistry Jolly et al Int. Journal of Engineering Research and Applications www.ijera.com ISSN : 2248-9622, Vol. 4, Issue 5( Version 3), May 2014, pp.68-71 www.ijera.com 71 | P a g e [6] C. Intanagonwiwat, R. Govindan, and D. Estrin, ”Directed diffusion: a scalable and robust communication paradigm for sensor networks,” Proceedings of ACM MobiCom ‟00, Boston, MA, 2000, pp. 56-67. [7] W. Heinzelman, A. Chandrakasanand H. Balakrishnan, ”Energy-Efficient Communication Protocol for Wireless Mi- crosensor Networks,” Proceedings of the 33rd Hawaii International Conference on System Sciences (HICSS ‟00), January 2000. [8] S. Lindsey, C. Raghavendra, “PEGASIS: Power-Efficient Gathering in Sensor Information Systems”, IEEE Aerospace Conference Proceedings, 2002, Vol. 3, 9-16 pp. 1125-1130. [9] A. Savvides, C-C Han, aind M. Srivastava, “Dynamic fine-grained localization in Ad- Hoc networks of sensors,” Proceedings of the Seventh ACM Annual International Conference on Mobile Computing and Networking (Mobi Com), July 2001. pp. 166-179. [10] W. Heinzelman, A. Chandrakasan, and H. Balakrishnan, ”Energy-efficient routing protocols for wireless microsensor networks, ” in Proc. 33rdHawaii Int. Conf. SystemSciences(HICSS), Maui, HI,Jan. 2000. [11] Wendi B Heinzelman, A P Chandrakasan, Hari Balakrishnan,”An application-specific protocol architecture on wireless microsensor networks", IEEE transaction on wireless communications, 2002, PP. 660- 670. [12] V. Loscr, G. Morabito, S. Marano, “A Two- Levels Hierarchy for Low-Energy Adaptive Clustering Hierarchy (TL-LEACH)", Vehicular Tech-nology Conference, 2005. [13] Thiemo Voigt, Hartmut Ritter, Jochen Schiller, Adam Dunkels, and Juan Alonso,” Solar-aware Clustering in Wireless Sensor Networks”, In Proceedings of the Ninth IEEE Symposium on Computers and Communications, June 2004. [14] Rajashree.V.Biradar, Dr. S.R. Sawant, Dr. R. R. Mudholkar , Dr. V.C .Patil ”Multihop Routing In Self-Organizing Wireless Sensor Networks”IJCSI International Journal of Computer Science Issues, Vol. 8, Issue 1,January 2011. [15] Hu Junping, Jin Yuhui, “A Time-based Cluster-Head Selection Algorithm for LEACH” IEEE Symposium Computers and Communications (ISCC), 2008.