SLEEP CONTROL FOR LIFE TIME MAXIMIZATION AND ROUTING IN WSN

International Journal of Control, Automation, Communication and Systems (IJCACS), Vol.1, No.1, January 2016
DOI: 10.5121/ijcacs.2016.1102 9
SLEEP CONTROL FOR LIFE TIME
MAXIMIZATION AND ROUTING IN WSN
V.Amsa 1
and S. Raj Anand 2
1
PG.Scholar, Departement of MCA, Veltech High Tech Engineering College
2
Assistant Professor, Departement of MCA, Veltech High Tech Engineering College
Abstract
Recently the research is about the life time maximization and the routing in wireless sensor network it is an
important issue in today’s WSN.To solve these types of problems some of the algorithms and techniques are
addressed in this paper and also introduced network architecture. To save the life time in the network .This
paper proposed sleep control for the sensor node in the network and connected dominating set based alpha
minimum routing cost algorithm for the routing. Wsn is a node which is connected to several or thousands
of the sensor in wireless area such as radio transceiver either internal antenna or as external antenna.
Keywords
WSN, Sleep Control, Routing, Alpha Minimum Routing.
1. Introduction
Wireless sensor network deployed thousands of sensor nodes. Nodes are based the on batteries in
WSN. To extend the life time of the battery sleep control is used and also saves the power
consumption of the nodes. Sleep control uses the semi active state for all the nodes in WSN. To
forward the packets or any kind of data we use routing. Routing has many kind of techniques. In
this paper we use alpha minimum routing algorithm and for connection with nodes we deployed
connected dominating set based. Connected dominating is set based for the nodes with its
neighborhood. The main advantage is recalculation is not needed for the routing. Our proposal is
focused on the routing and life time maximization in WSN. Semi active state is deployed for
sleep control in order to send the data instead of sleep or wake up the nodes when the input is
received. For all nodes in the network. First check the nodes whether it is in active state or it is
in off state. To check this purpose we introduced connected domination set based algorithm to
connect the neighbor nodes. When the connection is established, all the nodes in the network
applied with semi active state and it produces the active state when the input is received. [1]Any
cast packet is done using sleep-wake scheduling and it is used to reduce the wastage of energy.
[2]GPSR provides per router than the shortest path and it finds the correct new router and it
compares the mobile wireless sensor network with dynamic source routing. [3] GDSTR algorithm
is used to find the shortest path than geographic face algorithm.[4] LCR provides the efficient the
routing in WSN. [5] compared with geographic packet forwarding,CAGIF consumes much more
energy and decreases the signal over heads. [6]The unsafe area can be shown in the form of
rectangular region and achieve the better performances in routing. [7]EBGR provides the node
based on the energy level and it finds the next node relay position. [8] Coverage of the network is
done using low duty-cycled sensor random and coordinates sleep algorithm. [9]DSDA collects

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the information from its neighbor node. [10] Efficient mobile sensor node,
griddeploymentidentifies the weight of the each grid such as predeployed node, boundaries etc.
Hence the main objective is to save the life time of the sensor nodes and to provide the routing
with low cost, with this we can avoid the data delay and to avoid the failure nodes in the network.
The need of the project is to save the energy while the transmission takes place in the WSN by
sleep control and to avoid datadelay alpha minimum routing algorithm is proposed.
2. Existing Lifetime Imrovements In Wsn
Wireless sensor network consists of many techniques and algorithm. The existing system focus
on packet forwarding and the lifetime maximization using sleep and wake up the nodes due to
this proposal packets are delayed .The sleep and wake up is provided to nodes through which
data reaches its destination and its has no alternative path when the node is failed. This kind of
problems raised in the existing .Later a new proposal is produced Backbone algorithm. Backbone
algorithm provides the routing in the limited manner to save the life time of the sensor. It does not
affect the network and it saves the energy. To overcome all these problems we proposed some
algorithms and techniques in this paper.
2.1 Draw Backs Of Life Time Improvements In Wsn
The disadvantages of the existing are power consumption, data delay, and routings.
3. Proposed Methodolgy Of Sleep Control For Life Time Maximization
In Wsn
The proposal of this paper concentrates in life time maximization, routing and sleep control in
WSN.Semi active state is applicable for the nodes in the network, which provides semi active
strategies. The strategies include gain scheduling and clipped optimal schemes with continuously-
varying and on-off control. It improves the performances of the passive system.Connected
dominating set based provides the node connection. A connected dominating set based provides
connection to the neighbor nodes and also provides minimum connected dominating set of graph
G is a set D of vertices with two properties.The first is any node in D can reach any other node in
D by a path that stays entirely within D.That is D indicates a connected sub graph of G.The
second is every vertex in G either belongs to D or is adjacent to a vertex in D .D is the dominating
set of G.Alpha minimum routing cost algorithm is used for the routing which avoids the routing
traffic and provides easy transmission for the data.
4. Algorithm
There are two algorithms and one application used in this paper
1. Connected dominating set based algorithm
2. Alpha minimum routing algorithm
3. Semi Active state application

The figure 1 denotes the overall architecture of the proposed
node is predicted to check the neighbor nodes are
sends the request to all the nodes to rec
is received based on the I address
used in this stage which is shown in
the signals are extended to the u
in fig1and an alternative path can be provided for this network if the file is not received.
5. Routing In Wsn
Routing plays a major role in the WSN
some of the routings are location based
flatrouting, package based routing etc. Data are
hop is done it is actually one type of ad hoc networks.WSN provides attention for the routing due
to its flexibility, efficiency and
routing process because it is deployed in open and unprotected
function nodes cannot be trusted but by processing some of the algorithm and
process it safely. In this paper
algorithms for example military applications.
Figure 1: overall architecture
denotes the overall architecture of the proposed system. From the base station the
e neighbor nodes are available. If the nodes are within the network it
sends the request to all the nodes to receive a positive acknowledgement. The acknowledg
I address. Now the file is send to the node. The proposed algorith
used in this stage which is shown in the fig1.Switching on and off is proposed for the nodes and
o the uncovered areas. Routing is provided at this stage which is shown
g plays a major role in the WSN .Routing are in different ways to reach its
of the routings are location based routing, distanced based routings,hierarchalroutings,
based routing etc. Data are sending based on the routing. In WSN multipoint
ype of ad hoc networks.WSN provides attention for the routing due
and scalability. Several types of attacks are produced during the
routing process because it is deployed in open and unprotected environment. For critical netw
function nodes cannot be trusted but by processing some of the algorithm and techniques we
we address connected dominating and alpha minimum routing
algorithms for example military applications.
11
the base station the
the nodes are within the network it
acknowledgement
proposed algorithm is
the fig1.Switching on and off is proposed for the nodes and
is stage which is shown
t ways to reach its destination,
hierarchalroutings,
routing. In WSN multipoint
ype of ad hoc networks.WSN provides attention for the routing due
produced during the
critical network
techniques we can
we address connected dominating and alpha minimum routing

12
6. Sensor Network
In wireless sensor network nodes are in the form of sensor, sensors are used to pass the data from
base station to the destination sleep scheduling is provided to the sensor to save the life time of
the nodes .The request is send to all the nodes to check whether the nodes are in the active or in
sleep state. when the nodes are in active state the positive acknowledgment will be send to the
base station or to the sender and it sends the data to the neighbor node and it hops to the next node
before it hopes to next node the previous node will be in the semi active state or to the sleep node
it depends upon the package. Each node wakes up independently of neighboring nodes in order to
save energy. By putting nodes to sleep when there are no events, the energy consumption of the
sensor nodes can be significantly reduced.
6.1 Advantages Of Proposal
The main advantage is to save the life time of the sensor and routing which is based on the
location and the distance based. Wsn provides the efficient routing for any kind of data’s or
packets .The cost level is reduced by the following algorithms addressed in this paper.
Application
It can be applied to the following areas,
• Mobile phone networks
• Wifi and Wi-MAX networks
• All other wireless sensor networks
7. Simulation Result
Figure 2. Lifetimes in Sensor Network
0
5
10
15
20
25
30
35
40
45
1 2 3 4
Existing range
Propose range
nodes
ranges

13
The Figure 2 Shows the simulation results between the existing and proposed system.
In the above figure 2 shows the comparison between the existing range and the proposed range
the life time range is extended in the proposal.
Figure 3. Lifetime Maximization in WSN
The Figure 3 shows the lifetime maximization in WSN to save the power of nodes.
The above figure shows the number of nodes and the network coverage area with the new
proposal methods and techniques
0
100
200
300
400
500
600
1 2 3 4 5
Number of nodes
Network
Lifetime

14
Figure4. Hops of the node and its utilization
Series 1 shows the range of the nodes
Series 2 shows the number of nodes
Series 3 shows the utilization of the network coverage
8 CONCLUSION
In this paper we address the life time maximization of the sensor and the routing in the WSN. The
network structure is limited with these techniques such as connected dominating, alpha minimum
routing cost algorithm and the sleep control by using these types we can save the life time
maximization in WSN and can avoid the routing collisions and it provides signals to the
uncovered area which is shown in the fig1.we can provide further more techniques to save the life
time of the sensor. We also produced some highlighted techniques in this challenging network .In
WSN there are many challenging works but with is proposal it is possible but it needs more
techniques and algorithms to improve the life time maximization.
Refernces
[1] K.Maheswri, Dr.S.Karthik,Dr.S.KirubakaranLifetime improvement of Wireless Sensor Network by
Using Sleep-WakeSchedulingand Any Cast Packet Forwarding Scheme Vol:02, 2013, pp:197-200.
[2] B. Karp and H. T. Kung, “GPSR: Greedy perimeter Stateless routing for wireless networks,” in
Proc.MobiCom, Vol: 01,2000,pp 243-254
[3] B. Leong, B. Liskov, and R. Morris, “Geographic routing without planarization,” in Proc. NSDI, Vol:
01, 2006, pp. 339–352.
0
10
20
30
40
50
60
1 2 3 4 5
Net work coverage
Nodes
Range
Hops
Utilization

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[4] Y.-J. Kim, R. Govindan, B. Karp, and S. Shenker, “Lazy cross-link removal for geographic
routing,” in Proc. SenSys, 2006, pp. 112–124.
[5] L.Zhangand Y.Zhang, Energy efficient cross layer protocol of channel aware geographic-informed
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[6] Z.Jiang, J.Ma, W.Lou, and J.Wu, “An information model for geographic greedy forwarding in
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[7] Zhang and H. Shen, “Energy-efficient beaconless geographic routing in wireless sensor networks,”
IEEE Trans. Parallel Distrib. Syst., vol. 21, no. 6, pp. 881–896, 2010.
[8] C.-F. Hsin and M. Liu, “Network coverage using low duty-cycled sensors: Random & coordinated
sleep algorithms”, in Proc.IPSN,2004 pp.433-442.
[9] P. Cheng, F. Zhang, J. Chen, Y. Sun, and X. Shen, “A distributed TDMA scheduling algorithm for
target tracking in ultrasonic sensor networks,” IEEE Trans. Ind. Electron., vol. 60, no. 9, pp. 3836–
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[10] R. C. Luo and O. Chen, “Mobile sensor node deployment and asynchronous power management for
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[11] H. Song, V. Shin, and M. Jeon, “Mobile node localization using fusion prediction-based interacting
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4359, 2012.
[12] J. Pan, L. Cai, Y. T. Hou, Y. Shi, and X. X. Shen, “Optimal base-station locations in two-tiered
wireless sensor networks,” IEEE Trans. Mobile Comput., vol. 4, no. 5, pp. 458–473,2005.

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