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Integrated Intelligent Research (IIR) International Journal of Business Intelligents
Volume: 05 Issue: 01 June 2016 Page No.28-30
ISSN: 2278-2400
28
Priority Based Multi Sen Car Technique in WSN
D. Sophia Navis Mary, Vidhya.P.L,
Assistant Professor, Department of MCA, Ethiraj CollegeforWomen,Chennai,TamilNadu.
Research Scholar, Department of MCA, Ethiraj College for Women, Chennai,TamilNadu.
sophianavis@gmail.com, vidyachand93@gmail.com
Abstract- In Wireless sensor network (WSN), Clustering is an
efficient mechanism used to overcome energy capability
problem, routing and load balancing. This paper addresses
energy utilization and load distribution between the clusters. The
load balanced clustering algorithms (LBC) used to decrease the
energy utilization and distribute load into clusters. The SenCar
uses multi-user multi-input and multi-output (MU-MIMO)
technique which is introduced the multi SenCar to collects the
information from each cluster heads and upload the data in the
base station. This method achieves more than 50 percent energy
saving per node, 80 percent energy saving on cluster heads and
also achieves less data collection time compared to the existing
system.
Keywords-Wireless sensor network, load balancing, clustering,
SenCar, LBC, MU-MIMO.
I. INTRODUCTION
The Wireless sensor Network (WSNs) achieves energy
efficiency, transmission time andmany areas like military
surveillance, environmental and commercial areas [1], [2]. It
contains a variety of device nodes with restricted energy. The
sensing and transmission of knowledge involves largequantity of
energy consumption. Therefore,WSN carries an effectual
clustering technique is used to reduce utilization of energy. The
various environments contains different types of sensor nodes in
term of computation, sensors, power and communication. The
SenCarapproach is try to minimize theenergyutilization. It has an
efficient method to achieve good scalability, and increase
network lifetime and low data Latency.In WSN having number
of sensor node, each node is used to collect and transfer the data
with in particular time intervals [3]. This framework contains
three layers are used, the first sensor layer is representing to
organize the cluster themselves. The second cluster head layer is
to perform communication between cluster and cluster head.
Third layer is to represent to how to schedule MU-
MIMOtechnique performs in multiple clusters. SenCar is used to
upload data parallel in two cluster heads. The polling points to
gather information about cluster heads and send through the
sensor nodes. The MU-MIMO technique is used to reduce the
power consumption.
II. LITERATURE SURVEY
According to [1], [4] the author proposes new energy-efficient
approach for clustering nodes in ad hoc sensor networks. First
select cluster heads periodically in Hybrid Energy-Efficient
Distributed clustering [11]. When compare to residual energy
and secondary parameter inhybrid. In paper [2] author first
present how to place sensor node by use of a minimal number to
maximize the coverage area which considered sensor node is not
less than the sensing radius in communication radius. This paper
[7] deals with mobile data gathering, which says one or more
mobile collectors are used to supply with powerful transceivers
and batteries.
III. EXISTING SYSTEM
In previous work, mobile data gathering can spit into three
schemes. The first one is to establish relay routingin which is the
data’s are replay among sensors [3]. Furthermore, the relaying
concept should maintain load balanced allotment of data pattern,
and data reputation.The second scheme is SenCar is tried to
transfer the data from data sink collected from cluster heads.
Clustering strategy particularly used increase scalability and it is
very effectual in a data aggregation .This also reduce load and
traffic. The final strategy in asensor, data routing burden has
taken by mobile collector [7]. At first,the cluster head constructs
direct communication between basestations.When the energy
level reached a threshold level, theSenCar to evaluate distance
and travel to collectsthe data. Furthermore, the mobile collectors
may suffer variants of energy consumption, it’s affected the
resultin disagreeabledata latency and pair cluster creation is one
of the big troubles.
IV. PROPOSED SYSTEM
This system used to find a set of cluster head to be visited by a
SenCar. This also limits the number of data gathering such that
the resulting tour does not exceed the required deadline of data
packets.Here, the priority based data gathering technique used
Dual Rendezvous Point (data collected point) whenever received
packet rate exceeds more than threshold value it updates packet
size information to base station.
Integrated Intelligent Research (IIR) International Journal of Business Intelligents
Volume: 05 Issue: 01 June 2016 Page No.28-30
ISSN: 2278-2400
29
Fig.1 Data transmission in wsn.SC-SenCar,BS-Base Station.
Depending on packet priority, Sensor car analysis the shortest
route by MUMU-MIMO technique and travel to upload data
from Rendezvous point meanwhile it can transmit data to the
base station. It is diminish delay of data gathering and expand
power utilization and important data should be transmitting
firstpriority. So the result of power saving and consumption is
sustained [4], [12]. The technique of MUMU-MIMO is to carry
to upload data simultaneously and minimize data latency.
V. TECHNIQUES
A. Load balanced Clustering technique
The powerful operation of clustering is the cluster head selection
isone of the importantprocess [8]. But generally the cluster head
selection based up on the residual energy [12]. Here, it is
consider the percentage of residual energy of every sensor as the
initial clustering priority. Let consider as set of sensors, its
denoted by S=s1, s2,.sn .In every cluster head is to have the
independently select the decision about theparticular status and
priority information. In load balanced clustering algorithm is
define each cluster will make multiple cluster heads>1 which
denoted by the CHG size in each cluster no more than M.
Fig1. Cluster head selection.
The LBC algorithm can split in to four phases.
1) Initialization
2) Status claim
3) Cluster forming
4) Cluster head synchronization.
1. Initialization
Every sensornode to familiarize itself with all neighbors sensor
node considered as separate node, it declares itself. Moreover the
cluster head contains cluster itself. On other hand a sensor
allocate tentative as a first set of status and also assign the
priority of residual energy percentage. And select the initial
priority and highest priority of neighbors of M_1.
2. Status claim
In this phase, the local information updates iteratively and each
sensor declare its status and abstain the cluster head claim
promptly. In case a sensor can finally become a cluster head in
the beginning it depends on its priority. Particularly, the priority
candivide threezones and two thresholds, th and tm (th> tm) , a
sensor to assign a cluster head by own. In some cases of iteration,
the SenCarpriority is greater than th or less than tm compared
with its neighbors, it can certainly decide its final status and quit
from the iteration. This function is called self-driven status
transition.
3. Cluster forming
This phase is used design the formation of cluster that decides a
sensor should be associated with the cluster head [13]. The
session can be described as follows: a sensor can select with
tentative status or clustermember randomly. Cluster head
between its candidate peers for load balance purpose. In some
case, the candidate peers not have the cluster head, a sensor
would claim itself for tentative status and present candidate peers
as a cluster heads. The multiple cluster heads are used to reduce
the load.
4. Synchronization among Cluster Heads
TDMA (Time Division Multiple Access) approach is to perform
data collection, the cluster head consider intra-cluster time
synchronization among establish time [6]. In fourth structure,
firsteach cluster head will send out a beacon message with its
initial priority and local clock information to other nodes in a
cluster head groups. Then it evaluates the received beacon
messages to see if the priority of a beacon message is higher. If it
correct, it adjusts local clock according to the timestamp of the
beacon message. In this framework, such synchronization among
cluster heads is only performed while SenCar is collecting data.
Because data collection is not repeated in most mobile data
gathering applications, message overhead is certainly
manageable within a cluster.
B.MU-MIMO TECHNIQUE
MU-MIMO is one of the effectual approaches in wireless sensor
network. The single sensor node is very difficult to maintain
multiple antennas. In MU-MIMO used to achieve diversity and
minimize the bit error rate. The MU-MIMO used scheduling
algorithm is to coordinate transmissions. MU-MIMO technique
is better than the Single Input Single Output (SISO).So, it’s
difficult to manage this problem. TheMU-MIMO scheme isto
perform better when compare SISO approach in certain threshold
value large in transmission distance. According to [28],
thetechnique MU-MIMO can be reached to energy saving in
proper design of systemparameters. It also to manage the
transmission time, energy consumptions and modulation
C.SENCAR
In this method, the major concept is Sensor layer. Its carries the
information among the each cluster head. The sensor layer is
used to accept the communication along with the particular
neighbors. It represents the transmission range. The clusters are
self-organized them self-using sensor. Sensor can select the
Integrated Intelligent Research (IIR) International Journal of Business Intelligents
Volume: 05 Issue: 01 June 2016 Page No.28-30
ISSN: 2278-2400
30
cluster head which consider the high power level. Where the
multiple cluster head are noticed cluster group head (CHG) [8].In
previous method, here all sensor nodes are communicate directly
with base station, Because it have delay, node failure,
redundancy of data and large amount of energy utilization.
Fig3. Network architecture of mobile SenCar based WSN.
A SenCaruploads buffered data through the MU-MU-MIMO and
synchronize the local and global clocks on SenCar via
acknowledgement message.SenCar is to avoid the large use of
energy through to perform the re-clustering periodically. Here,
the SenCarsets the location and check the impact of channel and
denote the candidate locations of data. More over SenCar does
not go to collect all the polling points. Since SenCar has pre-
knowledge about the particular locations of polling points. It can
easy to discover the shortest route and collect the polling point
information and return to the data sink.
VI. CONCLUSION
In WSN, the mobile data collections are used to LBC and dual
data uploading. TheSenCar is used to technique of MU-MIMO,
which helps to create multi SenCar are used to collects the data
in short time. The result of LBC is toreduced energy usage. In
mobile data gathering is used to save 60 percentage of energy
and to increase the transmission time.
REFRENCES
[1] B. Krishnamachari, Networking Wireless Sensors. Cambridge, U.K.:
Cambridge Univ. Press, Dec. 2005.
[2] Shorey, A. Ananda, M. C. Chan, and W. T. Ooi, Mobile, Wireless, Sensor
Networks. Piscataway, NJ, USA: IEEE Press, Mar. 2006.
[3] F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, “A survey on
sensor networks,” IEEE Commun. Mag., vol. 40, no. 8, pp. 102–114, Aug.
2002
[4] C. Liu, K. Wu, and J. Pei, “An energy-efficient data collection framework
for wireless sensor networks by exploiting spatiotem-poral correlation,”
IEEE Trans. Parallel Distrib. Syst., vol. 18, no. 7, Pp.1010–1023, Jul. 2007.
[5] K. Xu, H. Hassanein, G. Takahara, and Q. Wang, “Relay node deployment
strategies in heterogeneous wireless sensor networks,” IEEE Trans. Mobile
Comput., vol. 9, no. 2, pp. 145–159, Feb. 2010.
[6] O. Gnawali, R. Fonseca, K. Jamieson, D. Moss, and P. Levis, “Collection
tree protocol,” in Proc. 7th ACM Conf. Embedded Netw. Sensor Syst.,
2009, pp. 1–14.
[7] E. Lee, S. Park, F. Yu, and S.-H. Kim, “Data gathering mechanism with
local sink in geographic routing for wireless sensor networks,” IEEE Trans.
Consum. Electron. vol. 56, no. 3, pp. 1433– 1441, Aug. 2010.
[8] O. Younis and S. Fahmy, “Distributed clustering in ad-hoc sensor networks:
A hybrid, energy-efficient approach,” in IEEE Conf. Comput. Commun. pp.
366–379, 2004.
[9] Modeling a Three-Tier Architecture for Sparse Sensor Networks---(R.
Shah, S. Roy, S. Jain, and W. Brunette)---(Sept. 2003)Networked
Infomechanical Systems: A Mobile Embedded Networked Sensor
Platform—(R. Pon, M.A. Batalin, J. Gordon, A. Kansal, D. Liu, M. Rahimi,
L. Shirachi, Y. Yu, M. Hansen, W.J. Kaiser)—(2005)
[10] O. Younis and S. Fahmy, “Distributed clustering in ad-hoc sensor networks:
A hybrid, energy-efficient approach,” in IEEE Conf. Comput. Commun.,
pp. 366–379, 2004.
[11] D. Gong, Y. Yang, and Z. Pan, “Energy-efficient clustering in lossy
wireless sensor networks,” J. Parallel Distrib. Comput., vol. 73, no. 9, pp.
1323–1336, Sep. 2013.
[12] A. Amis, R. Prakash, D. Huynh, and T. Vuong, “Max-min d-cluster
formation in wireless ad hoc networks,” in Proc. IEEE Conf. Comput.
Commun., Mar. 2000, pp. 32–41.
[13] A. Manjeshwar and D. P. Agrawal, “Teen: A routing protocol for enhanced
efficiency in wireless sensor networks,” in Proc. 15th Int. IEEE Parallel
Distrib. Process. Symp., Apr. 2001, pp. 2009–2015.
[14] F. Ye, G. Zhong, S. Lu, and L. Zhang, “PEAS: A robust energy conserving
protocol for long-lived sensor networks,” in Proc. 23rd
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Distrib. Comput. Syst., 2003, pp. 28–37

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Priority Based Multi Sen Car Technique in WSN

  • 1. Integrated Intelligent Research (IIR) International Journal of Business Intelligents Volume: 05 Issue: 01 June 2016 Page No.28-30 ISSN: 2278-2400 28 Priority Based Multi Sen Car Technique in WSN D. Sophia Navis Mary, Vidhya.P.L, Assistant Professor, Department of MCA, Ethiraj CollegeforWomen,Chennai,TamilNadu. Research Scholar, Department of MCA, Ethiraj College for Women, Chennai,TamilNadu. sophianavis@gmail.com, vidyachand93@gmail.com Abstract- In Wireless sensor network (WSN), Clustering is an efficient mechanism used to overcome energy capability problem, routing and load balancing. This paper addresses energy utilization and load distribution between the clusters. The load balanced clustering algorithms (LBC) used to decrease the energy utilization and distribute load into clusters. The SenCar uses multi-user multi-input and multi-output (MU-MIMO) technique which is introduced the multi SenCar to collects the information from each cluster heads and upload the data in the base station. This method achieves more than 50 percent energy saving per node, 80 percent energy saving on cluster heads and also achieves less data collection time compared to the existing system. Keywords-Wireless sensor network, load balancing, clustering, SenCar, LBC, MU-MIMO. I. INTRODUCTION The Wireless sensor Network (WSNs) achieves energy efficiency, transmission time andmany areas like military surveillance, environmental and commercial areas [1], [2]. It contains a variety of device nodes with restricted energy. The sensing and transmission of knowledge involves largequantity of energy consumption. Therefore,WSN carries an effectual clustering technique is used to reduce utilization of energy. The various environments contains different types of sensor nodes in term of computation, sensors, power and communication. The SenCarapproach is try to minimize theenergyutilization. It has an efficient method to achieve good scalability, and increase network lifetime and low data Latency.In WSN having number of sensor node, each node is used to collect and transfer the data with in particular time intervals [3]. This framework contains three layers are used, the first sensor layer is representing to organize the cluster themselves. The second cluster head layer is to perform communication between cluster and cluster head. Third layer is to represent to how to schedule MU- MIMOtechnique performs in multiple clusters. SenCar is used to upload data parallel in two cluster heads. The polling points to gather information about cluster heads and send through the sensor nodes. The MU-MIMO technique is used to reduce the power consumption. II. LITERATURE SURVEY According to [1], [4] the author proposes new energy-efficient approach for clustering nodes in ad hoc sensor networks. First select cluster heads periodically in Hybrid Energy-Efficient Distributed clustering [11]. When compare to residual energy and secondary parameter inhybrid. In paper [2] author first present how to place sensor node by use of a minimal number to maximize the coverage area which considered sensor node is not less than the sensing radius in communication radius. This paper [7] deals with mobile data gathering, which says one or more mobile collectors are used to supply with powerful transceivers and batteries. III. EXISTING SYSTEM In previous work, mobile data gathering can spit into three schemes. The first one is to establish relay routingin which is the data’s are replay among sensors [3]. Furthermore, the relaying concept should maintain load balanced allotment of data pattern, and data reputation.The second scheme is SenCar is tried to transfer the data from data sink collected from cluster heads. Clustering strategy particularly used increase scalability and it is very effectual in a data aggregation .This also reduce load and traffic. The final strategy in asensor, data routing burden has taken by mobile collector [7]. At first,the cluster head constructs direct communication between basestations.When the energy level reached a threshold level, theSenCar to evaluate distance and travel to collectsthe data. Furthermore, the mobile collectors may suffer variants of energy consumption, it’s affected the resultin disagreeabledata latency and pair cluster creation is one of the big troubles. IV. PROPOSED SYSTEM This system used to find a set of cluster head to be visited by a SenCar. This also limits the number of data gathering such that the resulting tour does not exceed the required deadline of data packets.Here, the priority based data gathering technique used Dual Rendezvous Point (data collected point) whenever received packet rate exceeds more than threshold value it updates packet size information to base station.
  • 2. Integrated Intelligent Research (IIR) International Journal of Business Intelligents Volume: 05 Issue: 01 June 2016 Page No.28-30 ISSN: 2278-2400 29 Fig.1 Data transmission in wsn.SC-SenCar,BS-Base Station. Depending on packet priority, Sensor car analysis the shortest route by MUMU-MIMO technique and travel to upload data from Rendezvous point meanwhile it can transmit data to the base station. It is diminish delay of data gathering and expand power utilization and important data should be transmitting firstpriority. So the result of power saving and consumption is sustained [4], [12]. The technique of MUMU-MIMO is to carry to upload data simultaneously and minimize data latency. V. TECHNIQUES A. Load balanced Clustering technique The powerful operation of clustering is the cluster head selection isone of the importantprocess [8]. But generally the cluster head selection based up on the residual energy [12]. Here, it is consider the percentage of residual energy of every sensor as the initial clustering priority. Let consider as set of sensors, its denoted by S=s1, s2,.sn .In every cluster head is to have the independently select the decision about theparticular status and priority information. In load balanced clustering algorithm is define each cluster will make multiple cluster heads>1 which denoted by the CHG size in each cluster no more than M. Fig1. Cluster head selection. The LBC algorithm can split in to four phases. 1) Initialization 2) Status claim 3) Cluster forming 4) Cluster head synchronization. 1. Initialization Every sensornode to familiarize itself with all neighbors sensor node considered as separate node, it declares itself. Moreover the cluster head contains cluster itself. On other hand a sensor allocate tentative as a first set of status and also assign the priority of residual energy percentage. And select the initial priority and highest priority of neighbors of M_1. 2. Status claim In this phase, the local information updates iteratively and each sensor declare its status and abstain the cluster head claim promptly. In case a sensor can finally become a cluster head in the beginning it depends on its priority. Particularly, the priority candivide threezones and two thresholds, th and tm (th> tm) , a sensor to assign a cluster head by own. In some cases of iteration, the SenCarpriority is greater than th or less than tm compared with its neighbors, it can certainly decide its final status and quit from the iteration. This function is called self-driven status transition. 3. Cluster forming This phase is used design the formation of cluster that decides a sensor should be associated with the cluster head [13]. The session can be described as follows: a sensor can select with tentative status or clustermember randomly. Cluster head between its candidate peers for load balance purpose. In some case, the candidate peers not have the cluster head, a sensor would claim itself for tentative status and present candidate peers as a cluster heads. The multiple cluster heads are used to reduce the load. 4. Synchronization among Cluster Heads TDMA (Time Division Multiple Access) approach is to perform data collection, the cluster head consider intra-cluster time synchronization among establish time [6]. In fourth structure, firsteach cluster head will send out a beacon message with its initial priority and local clock information to other nodes in a cluster head groups. Then it evaluates the received beacon messages to see if the priority of a beacon message is higher. If it correct, it adjusts local clock according to the timestamp of the beacon message. In this framework, such synchronization among cluster heads is only performed while SenCar is collecting data. Because data collection is not repeated in most mobile data gathering applications, message overhead is certainly manageable within a cluster. B.MU-MIMO TECHNIQUE MU-MIMO is one of the effectual approaches in wireless sensor network. The single sensor node is very difficult to maintain multiple antennas. In MU-MIMO used to achieve diversity and minimize the bit error rate. The MU-MIMO used scheduling algorithm is to coordinate transmissions. MU-MIMO technique is better than the Single Input Single Output (SISO).So, it’s difficult to manage this problem. TheMU-MIMO scheme isto perform better when compare SISO approach in certain threshold value large in transmission distance. According to [28], thetechnique MU-MIMO can be reached to energy saving in proper design of systemparameters. It also to manage the transmission time, energy consumptions and modulation C.SENCAR In this method, the major concept is Sensor layer. Its carries the information among the each cluster head. The sensor layer is used to accept the communication along with the particular neighbors. It represents the transmission range. The clusters are self-organized them self-using sensor. Sensor can select the
  • 3. Integrated Intelligent Research (IIR) International Journal of Business Intelligents Volume: 05 Issue: 01 June 2016 Page No.28-30 ISSN: 2278-2400 30 cluster head which consider the high power level. Where the multiple cluster head are noticed cluster group head (CHG) [8].In previous method, here all sensor nodes are communicate directly with base station, Because it have delay, node failure, redundancy of data and large amount of energy utilization. Fig3. Network architecture of mobile SenCar based WSN. A SenCaruploads buffered data through the MU-MU-MIMO and synchronize the local and global clocks on SenCar via acknowledgement message.SenCar is to avoid the large use of energy through to perform the re-clustering periodically. Here, the SenCarsets the location and check the impact of channel and denote the candidate locations of data. More over SenCar does not go to collect all the polling points. Since SenCar has pre- knowledge about the particular locations of polling points. It can easy to discover the shortest route and collect the polling point information and return to the data sink. VI. CONCLUSION In WSN, the mobile data collections are used to LBC and dual data uploading. TheSenCar is used to technique of MU-MIMO, which helps to create multi SenCar are used to collects the data in short time. The result of LBC is toreduced energy usage. In mobile data gathering is used to save 60 percentage of energy and to increase the transmission time. REFRENCES [1] B. Krishnamachari, Networking Wireless Sensors. Cambridge, U.K.: Cambridge Univ. Press, Dec. 2005. [2] Shorey, A. Ananda, M. C. Chan, and W. T. Ooi, Mobile, Wireless, Sensor Networks. Piscataway, NJ, USA: IEEE Press, Mar. 2006. [3] F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, “A survey on sensor networks,” IEEE Commun. Mag., vol. 40, no. 8, pp. 102–114, Aug. 2002 [4] C. Liu, K. Wu, and J. Pei, “An energy-efficient data collection framework for wireless sensor networks by exploiting spatiotem-poral correlation,” IEEE Trans. Parallel Distrib. Syst., vol. 18, no. 7, Pp.1010–1023, Jul. 2007. [5] K. Xu, H. Hassanein, G. Takahara, and Q. Wang, “Relay node deployment strategies in heterogeneous wireless sensor networks,” IEEE Trans. Mobile Comput., vol. 9, no. 2, pp. 145–159, Feb. 2010. [6] O. Gnawali, R. Fonseca, K. Jamieson, D. Moss, and P. Levis, “Collection tree protocol,” in Proc. 7th ACM Conf. Embedded Netw. Sensor Syst., 2009, pp. 1–14. [7] E. Lee, S. Park, F. Yu, and S.-H. Kim, “Data gathering mechanism with local sink in geographic routing for wireless sensor networks,” IEEE Trans. Consum. Electron. vol. 56, no. 3, pp. 1433– 1441, Aug. 2010. [8] O. Younis and S. Fahmy, “Distributed clustering in ad-hoc sensor networks: A hybrid, energy-efficient approach,” in IEEE Conf. Comput. Commun. pp. 366–379, 2004. [9] Modeling a Three-Tier Architecture for Sparse Sensor Networks---(R. Shah, S. Roy, S. Jain, and W. Brunette)---(Sept. 2003)Networked Infomechanical Systems: A Mobile Embedded Networked Sensor Platform—(R. Pon, M.A. Batalin, J. Gordon, A. Kansal, D. Liu, M. Rahimi, L. Shirachi, Y. Yu, M. Hansen, W.J. Kaiser)—(2005) [10] O. Younis and S. Fahmy, “Distributed clustering in ad-hoc sensor networks: A hybrid, energy-efficient approach,” in IEEE Conf. Comput. Commun., pp. 366–379, 2004. [11] D. Gong, Y. Yang, and Z. Pan, “Energy-efficient clustering in lossy wireless sensor networks,” J. Parallel Distrib. Comput., vol. 73, no. 9, pp. 1323–1336, Sep. 2013. [12] A. Amis, R. Prakash, D. Huynh, and T. Vuong, “Max-min d-cluster formation in wireless ad hoc networks,” in Proc. IEEE Conf. Comput. Commun., Mar. 2000, pp. 32–41. [13] A. Manjeshwar and D. P. Agrawal, “Teen: A routing protocol for enhanced efficiency in wireless sensor networks,” in Proc. 15th Int. IEEE Parallel Distrib. Process. Symp., Apr. 2001, pp. 2009–2015. [14] F. Ye, G. Zhong, S. Lu, and L. Zhang, “PEAS: A robust energy conserving protocol for long-lived sensor networks,” in Proc. 23rd IEEE Int. Conf. Distrib. Comput. Syst., 2003, pp. 28–37