ArticlePDF Available

Energy Efficient Sleep Awake Aware (EESAA) intelligent Sensor Network routing protocol

Authors:

Abstract and Figures

Wireless Sensor Networks (WSNs), with growing applications in the environment which are not within human reach have been addressed tremendously in the recent past. For optimized working of network many routing algorithms have been proposed, mainly focusing energy efficiency, network lifetime, clustering processes. Considering homogeneity of network, we proposed Energy Efficient Sleep Awake Aware (EESAA) intelligent routing protocol for WSNs. In our proposed technique we evaluate and enhance certain issues like network stability, network lifetime and cluster head selection process. Utilizing the concept of characteristical pairing among sensor nodes energy utilization is optimized. Simulation results show that our proposed protocolnificantly improved the
Content may be subject to copyright.
arXiv:1212.4106v1 [cs.NI] 17 Dec 2012
1
Energy Efficient Sleep Awake Aware (EESAA)
Intelligent Sensor Network Routing Protocol
T. Shah, N. Javaid, T. N. Qureshi
COMSATS Institute of Information Technology,
44000, Islamabad, Pakistan.
Abstract—Wireless Sensor Networks (WSNs), with growing
applications in the environment which are not within human
reach have been addressed tremendously in the recent past. For
optimized working of network many routing algorithms have
been proposed, mainly focusing energy efficiency, network life-
time, clustering processes. Considering homogeneity of network,
we proposed Energy Efficient Sleep Awake Aware (EESAA)
intelligent routing protocol for WSNs. In our proposed technique
we evaluate and enhance certain issues like network stability,
network lifetime and cluster head selection process. Utilizing
the concept of characteristical pairing among sensor nodes
energy utilization is optimized. Simulation results show that our
proposed protocolnificantly improved the network parameters
and can be a useful approach for WSNs.
Index Terms—Energy efficient, protocol, sleep, awakw
I. INTRODUCTION
Advancement in technologies, devices many opportunities
for efficient usage of resources in critical atmospheres. Wire-
less Sensor Networks (WSNs) brought a revolutionary change
in this context. Gathering and delivering of useful information
to the destination, became able with advent of this technology.
Applications like battlefield surveillance, smart office, traffic
monitoring and etc, can be well monitored through such
schemes.
WSN is composed of multiple unattended ultra-small,
limited-power sensor nodes deployed randomly in the area
of interest such as inaccessible ares or disaster places for
gathering of useful information. Miniature sensor nodes ca-
pable of sensing, processing useful information from, and
transmitting to destination has opened many research issues.
These battery powered sensor nodes are mounted with limited
processing and storage facilities. As WSNs are exposed to
dynamic environments, due to such configuration connectivity
loss of nodes may degrade the performance of network.
Design of protocols which should be energy efficient and
hence, enhancing the network life time is important for better
performance. Centralized algorithms are effected badly when
a critical node stops working and thus, results in a serious
protocol failure. In contrast, distributed protocols can handle
such failures more efficiently and can be a suitable solution.
Clustering structured routing protocol capable of data aggre-
gation are designed for energy efficiency of a network. Within
a cluster localized algorithms can operate without any wait
of control messages and hence, reducing the delay. Better
scalability is also achieved through these localized algorithms
when compared with centralized one’s.
In this paper. we evaluate the performance of clustering
algorithms on the basis of stability period, network life time
and throughput for WSNs. We enhance the above mentioned
parameters. Information from sensor nodes is forwarded to
cluster heads (CHs) and these CHs are responsible to transmit
this information to base station (BS) which is placed far away
from the field.
Clustering algorithms like LEACH, and DEEC [1,5] for
sensor networks have achieved reasonable goals regarding
better performance of networks. Following their thoughts
we proposed a new pairing concept based on applications
and specified distances between the sensors which will yield
significant improvements in the efficiency of network.
Rest of the paper is organized as follows: Section II
describes related work whereas, Section III describes our
protocol EESAA and section IV describes simulations. In the
end we concluded the paper.
II. RELATED WORK
In WSNs, (Homogenous, Heterogenous) energy always re-
mains a constraint. Many techniques have been proposed to
utilize energy of sensor nodes in a better way. Concept of
clustering yields significant results in optimizing energy cost
for both homogenous and heterogenous networks. In clustering
some of the nodes are selected as CHs and had to spent
more energy than rest of nodes for a specific period of time.
This high energy consumption is due to aggregation and long
range transmission of data. Many clustering algorithms e.g.,
LEACH, PEGASIS, DEEC, SEP, E-SEP [1,2,5,4,6].etc have
been proposed which discuses the efficient usage of energy in
sensor networks.
CHs in LEACH [1] protocol are selected periodically and
energy drains uniformly by role rotation. In PEGASIS [2]
energy load is distributed by forming a chain itself or being
organized by BS. For such chain formation global knowledge
about the network is essential and results in wastage of
resources. In DEEC [5] , sensor node are independently elected
as CHs based initial energy and residual energy. SEP [4] is
designed to deal with heterogenous networks which introduced
the concept of advance and normal nodes for cluster head
election.
Performance is evaluated on the basis of network stability
period, clustering process and throughput. In our EESAA,
2
keeping homogeneity in mind we tried to enhance all these
parameters. EESAA keeps the merits of distributed clustering
as well.
III. EESAA: THE PROPOSED PROTOCOL
In this section, we present a new routing protocol for
homogenous networks called EESAA. Our goal is to minimize
energy consumption in order to enhance network stability
period and network lifetime. For this purpose, we introduced
the concept of pairing. Sensor nodes of same application and
at minimum distance between them will form a pair for data
sensing and communication. In our EESAA protocol, we also
enhance CHs selection technique, by selecting CHs on basis of
remaining energy of nodes. More comprehensive description
of coupling among nodes is defined as follows.
A. Advance Coupling Network Model (ACNM)
In this section, we explain Advance Coupling Network
Model(ACNM). Initially senor nodes measure their location
through GPS (Global Positioning System). The nodes transmit
their location information, Application type and N ode I D
to the Base Station (BS). Then, this gathered information is
utilized by BS to compute mutual distance between nodes.
Nodes which are at minimum distance from each other in
their intra cluster transmission range and of same application
type are coupled in pair by BS. Then BS broadcast pairing
information to all the nodes in network. Nodes become aware
of their coupled node. During coupling process some nodes
are left out because they are not in inter cluster transmission
range of any other node.
According to the proposed scheme, The nodes switch be-
tween ”Sleep” and ”Awake” mode during a single commu-
nication interval. Initially node in a pair switch into Awake-
mode also called Active-mode if its distance from the BS is
less then its coupled node. Node in Active-mode will gather
data from surroundings and transmit this data to CHs. During
this period transceiver of the coupled node will remain off,
and switches into Sleep-mode. Sleep-mode nodes cease their
communication with CHs and only sense the network status.
In next communication interval, nodes in Active-mode switch
into Sleep-mode and Sleep-mode nodes switch into awake-
mode. In this way, we are able to minimize energy consump-
tion because nodes in Sleep-modes save their energy by not
communicating with the CHss. Nodes in Sleep-mode also save
their energy by avoiding overhearing and idle listening during
Sleep-mode. Isolated nodes remain in Active-mode for every
round till their energy resources depleted.
B. Network Settling Phase (NSP)
In NSP, optimal number of CHs are selected with the help of
distributed algorithm. Initially all nodes have same energy and
network is homogenous in terms of energy level. In LEACH
[1] protocol every node decides to become CH or not in current
round. The decision is based on desired percentage of CHs per
round which is Pd. In order to assure average number of CH
(Pd×N) for N number of nodes, Leach allows each node to
become CH after every 1/Pdrounds. Number of rounds after
which a node become CH refer to as epoch. In homogenous
network, energy of nodes after first round can not be same. If
the epoch for some high energy nodes and low energy is same,
these nodes have same probability to become CHs. There is
no proper distribution of CH responsibilities, nodes with low
energy will die quickly as compare to nodes with high energy.
In our EESAA protocol the CHs selection after first round is
based on remaining energy of each node.
Nodes in Active-mode take participation in CH election
process. In first round when all nodes have same initial energy
Eo, nodes in Active-mode will elect them self as CHs on
the basis of probability of selecting CH using distributed
algorithm. Each node chose a random number between 0 to 1
and compares it to a threshold Th, which is calculated as:
Th=(Pd
1Pd((firstround)mod 1
Pd)if nA
0otherwise (1)
where, A is the set of nodes which are in Active-mode
in first round. If the random number selected by node is
less then threshold Th, Node will elect itself as a CH and
called as Parent-Cluster-Heads (PCHs). When node has been
selected as PCH, it broadcasts an advertisement message to
whole network. Only Active-mode nodes hear the broadcast
advertisements from different PCHs, They select their PCHs
on the basis of Received Signal Strength Indication (RSSI) of
advertisements. When an Active-mode node decides to which
cluster it wants to associate, it transmits a request to that
PCH using Carrier Sensed Multiple Access (CSMA) MAC
protocol to avoid collision. Along with request Active-mode
nodes also transmit their energy information to the PCH. The
PCH computes the remaining energy and its distance from
each node and select CH, called Child-Cluster-Head(CCH),
for the next round. CCH is selected on the basis of maximum
remaining energy of nodes. If different nodes have same
remaining energy then a node at minimum distance from PCH
is selected as CCH. When PCH selects CCH, it sets up TDMA
schedule for associated nodes for communication. PCH then
broadcast CCH information and TDMA schedule associated
nodes in its cluser. Each node in cluster transmit its data to
PCH in its TDMA slot.
C. Network Transmission Phase (NTP)
In NTP, all nodes in Active-mode, transmit their sensed
data to CH during their assigned TDMA slots. Nodes in
Sleep-mode do not take participation in NTP and thus save
their energy by turning their transceiver off. CHs aggregates
received data form each nodes and transmit to BS. Data
aggregation is a key signalling technique to compress the
amount of data. Due to data aggregation technique a noticeable
amount of energy is saved. If there are N total number of nodes
and k are the optimal number of CHs then the average number
of nodes in each cluster will be:
N
K1(2)
3
0 10 20 30 40 50 60 70 80 90 100
0
20
40
60
80
100
pair2
pair3
pair4
pair5
pair6
pair7
pair8
pair9
pair10
pair11
pair12
pair13
pair14
pair15 pair16 pair17
pair18 pair19
pair20
pair21
pair22
pair23
pair24
pair25
pair26
pair27
pair28
pair29 pair30
pair31
pair32
pair33
pair34
pair35
pair36
pair37
pair38
pair39
pair40
pair41
Isolated
nodes
Coupled
nodes
Fig. 1. Advance Network Coupling Model
In order to transmit data, The radio of a non-CH node
dissipates ET X to run the transmitter circuitry and Eamp for
transmit amplifier to achieve acceptable SNR (Signal-to-Noise
Ratio). So, for transmission of LCbit message a non-CH node
expands:
EnonCH =N
K1(ET X ×LC×Eamp ×LC×d2
toCH
(3)
To receive data from non-CH node on by the radio of CH in
each cluster expands:
Erec = (ERX ×Lc)N
K1(4)
where, ERX is energy dissipate by receiver circuitry for
receiving data. Energy dissipated by CH to aggregate data
received from its associated nodes.
EAGR = (EAD ×Lc)N
K(5)
Transmission energy ETdissipates by CH to transmit
aggregated data to the BS is:
ET=ET X ×LA×Eamp ×LA×d2
toBS (6)
where, LAis aggregated data and d2
toBS is the distance
between CH and BS. Total energy dissipated by CH a round
is:
ECH =Erec +EAGR +ET(7)
Total energy dissipate by CH is the energy dissipated in
reception of data from its associated nodes,aggregation of
received data and transmission of that data to the BS.
D. Node Mode Setup Phase (Node Mode Setup Phase)
In this phase, Every node decides whether switch to sleep
mode or active mode for the next round. Active-mode node
first check that weather it is CCH or not. If it is not CCH it
will turn its transceiver off and switch into sleep mode. If it
is elected as CCH, it will remain active for the next round.
Sleep-mode nodes switch to active if their coupled partner not
selected as CCH. Nodes are not coupled with any other node
will remain active through its lifetime.
Algorithm 1 : Node Mode Setup Phase
1: END OF ROUND
2: if ( node == coupled ) then
3: if ( node mode==active && CCH FLAG==1) then
4: node mode=active
5: else if (node mode==active&&CCH FLAG==0) then
6: node mode = sleep
7: else if (node mode==sleep&&neighbor CCH FLAG==1)
then
8: node mode=sleep
9: else if (node mode==sleep&&neighbor CCH FLAG==0)
then
10: node mode=active
11: end if
12: else if (node==coupled&&node neighbor==dead) then
13: node mode=active
14: else
15: node mode = active
16: end if
Above algorithm defines how nodes switch between sleep
and awake mode in our EESAA protocol. Node will first check
that it is coupled or not. If node is coupled then node check
its mode and if it is in Active-mode then it check its CCH
flag. If its CCH flag is ON, it will remain in Active-mode. If
node is in Active-mode and its CCH flag is not ON it will
switch into Sleep-mode. If node is in Sleep-mode, it checks
that whether its coupled partner’s CCH flag is on or not. If
node’s coupled partner’s CCH flag is on it will remain in sleep
mode. If not then node switches to active mode. If coupled
partner of a node is dead it will remain active. All that nodes
which are left out in coupling process remain active for whole
network life time.
IV. SIMULATION RESULTS
We measure the performance of our proposed protocol
EESAA by performing comparative simulations. In our sim-
4
Network
Settling
Phase
Network Transmission
Phase
Compare
RSSI,
link
quality,
Type
In CH
range
Yes
No
All nodes send their
location info to BS
BS uses central coupling algorithm to make
couple among nodes with same application and
at minimum distance
Coupled
No
Yes
All other nodes are coupled with
any one of the their neighbor
BS broadcast their status
information
NoYes
PCHs
Active mode
In CHs
range
Receive CHs
Advertisements
CCHs
Broadcast CH
advertisement
Wait and listen
medium till selection
Receive AS-Req
from nodes Send AS-Req to CH with
energy information
Receive
TDMA
slot from
PCH
Receive data
from nodes
Send sensed data
in assigned slot
Aggregate received data
from member nodes Base Station
Nodes receive their status update and
become aware of their coupled partner
Every coupled node will compare its distance to BS to
its partner distance to BS
Node will remain active if distance is less than its partner
Awake
mode
All active mode nodes
Yes
No
Some Active-
nodes are
selected as
CHs based
on probabilty
Nodes switch to
sleep-mod
CCH
Compare the residual
energy of each node and
measure distance between
nodes and itself
PCHs select the CCHs
for next round
PCHs assign TDMA slot for data
transmission and broad TDMA schedule
and CCH information
Start
End
Fig. 2. Flow chart of EESAA
ulations we generate a sensor field of 100m×100msize. In
this field we randomly drop (100) sensor nodes with initially
energy Eo. Parameters for our simulation are given in table I.
For analyzing and comparing the performance of EESAA
protocol with LEACH, SEP and DEEC protocols we consider
the following metrics as given in [1,3,4].
1) Stability period: It is duration of network operation from
start till first node dies.
2) Network lifetime: Network lifetime is duration from start
till last node is alive.
3) Instability period: It is duration of network operation
from first node dies till the least node dies.
4) Number of Cluster-heads:It indicates the number of
clusters generated per round.
5) Packet to BS: It is rate of successful data delivery to BS
from CHs.
We analyze network lifetime of LEACH, SEP, DEEC and
our EESAA protocols. We examine the way the number of
alive nodes varies as network evolves. In fig 3 it is depicted
that EESAA has a prolong stability period as compare to the
other protocols. In EESAA first node dies around 1800 round.
Stability period of EESAA is almost 120%50%and 35%
5
0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000
0
50
100
number of rounds
Number of dead nodes
DEAD NODES
LEACH
DEEC
SEP
EESAA
Fig. 3. Dead Nodes for 100m×100mNetwork with 100 nodes
0 1000 2000 3000 4000 5000 6000
0
10
20
30
40 Count of Cluster Head
Number of rounds
Number of Cluster−Heads per round
LEACH
DEEC
SEP
EESAA
Fig. 4. CHs per round
0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000
0
1
2
3
4x 104
Number of rounds
Number of packets
PACKETS TO BS
LEACH
DEEC
SEP
EESAA
Fig. 5. Packet to BS Nodes for 100m×100mNetwork with 100 nodes
0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000
0
50
100
Number of rounds
Number of alive nodes
ALLIVE NODES
LEACH
DEEC
SEP
EESAA
Fig. 6. Alive Nodes for 100m×100mNetwork with 100 nodes
TABLE I
SIMULATION PARAME TERS
Parameter value
Network size 100m * 100m
Initial Energy .5 J
Pd.1 J
Data Aggregation Energy cost 50pj/bit j
Number of nodes 100
Packet size 4000 bit
Transmitter Electronics (EelectTx) 50 nJ/bit
Receiver Electronics (EelecRx) 50 nJ/bit
Transmit amplifier (Eamp) 100 pJ/bit/m2
greater than LEACH, SEP and DEEC respectively. From fig
3 it is also depicted that EESAA has 100%102%and 50%
maximum network life time as compared to LEACH, SEP
and DEEC. It is because of sleep-awake property of nodes
and effective cluster-head selection’s algorithm.
From Fig.4 we notice that the first node dies around 1700
and last node dies after 4000 rounds. This shows that in
EESAA instable region starts very later as compare to other
protocols. Figure 5 also shows that there is sudden increase in
number of dead nodes in SEP and LEACH protocols whilst in
EESAA nodes dies at a constant rate. This observation depicts
that in EESAA energy dissipation is properly distributed
among all the nodes in the network which in result increases
network lifetime.
In Fig.5 we analyze the number of CHs selected in every
round for all routing protocols. As shown in Fig.6 SEP, DEEC,
LEACH has more uncertainties in CHs selection. Random
number of CHs are selected in every round but ESSA has
some patterns and controlled CHs selection. EESAA efficient
CHs selection algorithm helps it in better and constant data
rate transmission to BS. Although EESAA has sleep-awake
policy for nodes and less number of data is transmitted to
BS however, ESSAA successful data delivery to BS is much
better than SEP and LEACH although SEP and LEACH is
transmitting data continuously. Other main reason of higher
data rate achievement is longer network life time of EESAA.
Successful data delivery is shown in Fig 6.
6
V. CONCLUSION
In this paper, we presented a more optimized routing scheme
for WSNs. Main focus was to enhance cluster-head selection
process. In EESAA, CHs ale selected on the basis of remaining
energy. In EESAA nodes also switches between sleep and
active modes in order to minimize energy consumption. In
our proposed strategy, stability period of network, and life
time has been optimized. Simulation results show that their
is significant improvement in all these parameters when com-
pared with some of the existing routing protocols e.g., SEP,
LEACH and DEEC.
REFERENCES
[1] 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.
[2] S. Lindsey and C. S. Raghavendra. PEGASIS: ower-ef?cient gathering
in sensor information systems. In Proceedings of the IEEE Aerospace
Conference, March 2002.
[3] X. H. Wu, S. Wang, ”Performance comparison of LEACH and LEACH-
C protocols by NS2,” Proceedings of 9th International Symposium on
Distributed Computing and Applications to Business, Engineering and
Science. Hong Kong, China, pp. 254-258, 2010
[4] G. Smaragdakis, I. Matta, A. Bestavros, SEP: A Stable Election Protocol
for clustered heterogeneous wireless sensor networks, in: Second Interna-
tional Workshop on Sensor and Actor Network Protocols and Applications
(SANPA 2004), 2004.
[5] L. Qing, Q. Zhu, M. Wang, ”Design of a distributed energy-efficient
clustering algorithm for heterogeneous wireless sensor networks”. ELSE-
VIER, Computer Communications 29, 2006, pp 2230- 2237.
[6] Femi A. Aderohunmu, Jeremiah D. Deng ”An Enhanced Stable Election
Protocol (SEP) for Clustered Heterogeneous WSN”. X. H. Wu, S. Wang,
”Performance comparison of LEACH and LEACH-C protocols by NS2,”
Proceedings of 9th International Symposium on Distributed Computing
and Applications to Business, Engineering and Science. Hong Kong,
China, pp. 254-258, 2010
[7] Fan Xiangning1,2 Song Yulin ”Improvement on LEACH Protocol of
Wireless Sensor Network” International Conference on Sensor Technolo-
gies and Applications 2007.
[8] 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 Com-
munications, June 2004.
[9] Md. Junayed Islam, Md. Muhidul Islam, Md. Nazrul Islam ”A-sLEACH
: An Advanced Solar Aware Leach Protocol for Energy Efficient Routing
in Wireless Sensor Networks” Proceedings of the Sixth International
Conference on Networking (ICN’07)
... This paper focuses on energy-efficient exposure protocols that ensures a longer duration of WSN. The comparison between LEACH [18], PEGASIS [19], SEP [20], DDEEC [21], EESAA [22], IAATPC [23] and EESCA [24].This paper is organized as follows: Section 2 elaborates the Literature survey; segment 3 discusses on the performance of Protocols; part 4 concludes the paper. ...
... EESAA [22] presented an additional optimized energyefficient scheme for WSNs. In [18] protocol CHs are selected periodically and energy is dissipated uniformly by changing the position of the node. ...
... III. DISCUSSION ON PERFORMANCE OF PROTOCOLS This section presents the relative analysis, and comparative analysis for energy-efficient protocols w.r.to cluster connectivity, clustering method, cluster count, CH & their significance. Table 1 shows the comparison of functioning of energy-efficient protocols like LEACH [18], PEGASIS [19], SEP [20], DDEEC [21], EESAA [22], IAATPC [23] and EESCA [24]. Table 2 shows a comparative analysis for energyefficient protocols w.r.to cluster properties. ...
... Despite the data aggregation mechanisms provided at the CH in these approaches, the redundant transmission to CH by closely located nodes within the same cluster can lead to a substantial amount of energy consumption within the network. In [31], a concept of characteristics pairing among the sensor nodes is used. In this approach, the sensor nodes of closer proximity are grouped to form pairs. ...
... Redundant transmission from overlapped sensor nodes was not considered [31] The concept of characteristics pairing among the sensor nodes is used. In this approach, the sensor node of closer proximity a grouped to form pairs. ...
Article
Full-text available
This research addresses the problem of redundant data transmission and improves load-balance routing in wireless sensor network (WSN). Redundant data generates higher data transfer and additional traffic loads, which degrade the network performance. The sub-clustering approach is used to minimize redundant transmissions by grouping overlapped or closely located nodes in a cluster into several sub-clusters such that only one node is required to sense the surroundings and send data to the cluster head (CH). The remaining sub-cluster members turn off their radios to save energy. However, the grouping of nodes into non-overlapping clusters and sub-clusters as well as proper selection of nodes to be awaked within a sub-cluster remained a challenging issue. Moreover, using a single node in a cluster performing the role of CH and relay could lead to load-balancing issues as the position of the selected CH may not ensure balanced intra-cluster and intercluster transmissions at the same time. In this paper, we proposed a Two-Step-Clustering (TSC) to improve the performance of WSN. In TSC, in the first step, the sensor nodes of minimum distance from each other were grouped into balanced non-overlapping clusters and sub-clusters. Then, a sleep-awake mechanism was employed among the members of the sub-cluster such that the sub-cluster members take turns according to their remaining energy. This is done to minimize redundant transmission to achieve energy efficiency. Furthermore, two CHs were selected, i.e., primary, and secondary CHs. The primary CH is responsible for intra-cluster data collection and the secondary CH is responsible for inter-cluster data transmission. This improves load-balanced routing within the network. In addition, single-hop and multi-hop routing were used to send data to BS. The result shows that the TSC has 54% lifetime improvements against SEED and 60% against DHSCA.
... Shah et al 23 proposed energy-efficient sleep awake aware (EESAA) routing protocol in which SNs paired to each other if they were engaged for the same application. With this arrangement, they introduced an advanced coupling network model (ACNM). ...
Article
Full-text available
The development of tiny sensor nodes (SNs) has incarnated numerous applications in the field of wireless sensor networks (WSN). These devices became much popular in multidisciplinary research area such as the internet of things (IoT). However, the use of these devices has been restricted due to some constraints like SN energy, data aggregation, quality of service (QoS), reliability, SN deployment, scalability, energy consumption, and many more. Among all these constraints, we focus on SN energy, SN deployment, and energy consumption of the network. Because if the consumption of SN energy is less, network lifetime automatically increases. So, we propose active–passive node topology on deployed SNs which enhance the network lifetime. With the help of the proposed mechanism, the lifetime and stability have increased by 60% and 3%, respectively, as compared with directed diffusion protocol in Experiment 1. In another experiment, the lifetime has increased by 67%, 64%, and 62% as compared with LEACH, NEAP, and DREEP, respectively, in homogeneous environment. The proposed scheme also performed significant improvement in heterogeneous environment. The simulation performance shows that the proposed protocol increases the network lifetime and stability of the network. An active–passive node topology on deployed Sensor nodes is proposed to enhance the network lifetime. The proposed scheme performed significant improvement in both homogeneous and heterogeneous environments. The simulations show that the proposed protocol increases the network lifetime and stability of the network.
... For exceeding that, each node needs to have the global knowledge of the networks; DEEC and DDEEC estimate the ideal value of network lifetime, which is used to compute the reference energy that each node should expand during each round. EESAA protocol [13] is trying to minimize energy consumption to enhance network stability period and network lifetime. For this purpose, EESAA introduced the concept of pairing. ...
... Initially, the network is homogeneous in energy with the same level. After the first round, the CH selection is based on each node's residual energy [30]. For the CH selection process, active nodes participate. ...
Article
Wireless sensor networks (WSNs) require an enormous number of sensor nodes (SNs) to maintain processing, sensing, and communication capabilities for monitoring targeted sensing regions. SNs are generally operated by batteries and have a significantly restricted energy consumption; therefore, it is necessary to discover optimization techniques to enhance network lifetime by saving energy. The principal focus is on reducing the energy consumption of packet sharing (transmission and receiving) and improving the network lifespan. To achieve this objective, this paper presents a novel improved energy-efficient cluster-based routing protocol (IECRP) that aims to accomplish this by decreasing the energy consumption in data forwarding and receiving using a clustering technique. Doing so, we successfully increase node energy and network lifetime. In order to confirm the improvement of our algorithm, a simulation is done using matlab, in which analysis and simulation results show that the performance of the proposed algorithm is better than that of two well-known recent benchmarks. © 2021 The Korea Institute of Information and Communication Engineering. All Rights Reserved.
... Finally, the energy source from the battery is the main thing (5). If a sensor node stopped it"s working due to low energy it will lead to big problem and serious protocol failure (6). It is impossible to recharge the battery while nodes are deploying in a belligerent environment. ...
Article
Wireless sensor network plays prominently in various applications of the emerging advanced wireless technology such as smart homes, Commercial, defence sector and modern agriculture for effective communication. There are many issues and challenges involved during the communication process. Energy conservation is the major challenging matter and fascinates issue among the researchers. The reason for that, Wireless sensor network has ‘n’ number of sensor nodes to identify and recognize the data and send that data to the base station or sink through either directly or intermediate node. These nodes with poor energy create intricacy on the data rate or flow and substantially affect the lifespan of a wireless sensor network. To decrease energy utilization the sensor node has to neglect unnecessary received data from the neighbouring nodes prior to send the optimum data to the sink or another device. When a specific target is held in a particular sector, it can be identified by many sensors. To rectify such process this paper present Data agglomeration technique is one of the persuasive techniques in the neglecting unnecessary data and of improves energy efficiency and also it increases the lifetime of WSNs. The efficacious data aggregation paradigm can also decrease traffic in the network. This paper discussed various data agglomeration technique for efficient energy in WSN
Chapter
Usually, wireless sensor networks (WSNs) are installed in large areas to monitor various physical conditions of the environment and forward the collected sensed data to a base station (central node), for instance: gas monitoring, intrusion detection, tracking objects, etc. However, sensor nodes are usually deployed unattended and battery-powered with no external power source. Therefore, WSNs face the challenge of limited energy source available onboard, where packet transmission and sensing functions are the most power consumption factors in WSN. Therefore, to overcome the energy depletion in sensor nodes, it is important to study the energy management issue in WSN. In this chapter, the significance of energy management issue is discussed first, and then the possible energy management strategies for WSN are presented and illustrated.
Conference Paper
Wireless Sensor Networks (WSNs) have an extensive range of applications but they have many challenging problems to be addressed. The energy consumption of nodes and the extension of network lifetime are among the core challenges. Energy aware routing is one of the methods to solve the energy problem of WSNs. To achieve the desired network operations the clustering (Hierarchical) routing protocols showed remarkable and outstanding improvement in prolonging the lifetime of WSNs. More significantly, heterogeneity-aware and threshold-based (application-aware) clustering routing protocols deal with more practical and realistic scenarios. In this paper, we propose a new clustering routing protocol, ZET (Zone and Energy Threshold based Clustering Routing Protocol) that is application-aware and heterogeneity-aware. In the execution environment, ZET distributed algorithm divides the whole network area into multiple zones. After dividing the nodes into multiple zones, ZET will select a cluster-head node with the highest energy-efficiency in each zone. We initially design the ZET for homogeneous network in which initial energy is same for all nodes. Then we introduce the heterogeneity in its execution network. We evaluate the performance of ZET using MATLAB simulations. The results show that ZET has better network life time, stability and throughput compared with existing routing protocols.
Book
Full-text available
This edited book is comprised of original research that focuses on technological advancements for effective teaching with an emphasis on learning outcomes, ICT trends in higher education, sustainable developments and digital ecosystem in education, management and industries. The contents of the book are classified as; (i) Emerging ICT Trends in Education, Management and Innovations (ii) Digital Technologies for advancements in education, management and IT (iii) Emerging Technologies for Industries and Education, and (iv) ICT Technologies for Intelligent Applications. The book represents a useful tool for academics, researchers, industry professionals and policymakers to share and learn about the latest teaching and learning practices supported by ICT. It also covers innovative concepts applied in education, management and industries using ICT tools.
Article
Full-text available
While wireless sensor networks are increasingly equipped to handle more complex functions, in-network processing may require these battery powered sensors to judiciously use their constrained energy to prolong the effective network life time especially in a heterogeneous settings. Clustered techniques have since been employed to optimise energy consumption in this energy constrained wireless sensor networks. We propose an Enhanced-SEP clustering algorithm in a three-tier node scenario to prolong the effective network life-time. Simulation results shows that the Enhanced-SEP achieves better performance in this respect, compared to other existing clustering algorithms in both heterogeneous and homogenous environments.
Article
Full-text available
We study the impact of heterogeneity of nodes, in terms of their energy, in wireless sensor networks that are hierarchically clustered. In these networks some of the nodes become cluster heads, aggregate the data of their cluster members and transmit it to the sink. We assume that a percentage of the population of sensor nodes is equipped with additional energy resources—this is a source of heterogeneity which may result from the initial setting or as the operation of the network evolves. We also assume that the sensors are randomly (uniformly) distributed and are not mobile, the coordinates of the sink and the dimensions of the sensor field are known. We show that the behavior of such sensor networks becomes very unstable once the first node dies, especially in the presence of node heterogeneity. Classical clustering protocols assume that all the nodes are equipped with the same amount of energy and as a result, they can not take full advantage of the presence of node heterogeneity. We propose SEP, a heterogeneous-aware protocol to prolong the time interval before the death of the first node (we refer to as stability period), which is crucial for many applications where the feedback from the sensor network must be reliable. SEP is based on weighted election probabilities of each node to become cluster head according to the remaining energy in each node. We show by simulation that SEP always prolongs the stability period compared to (and that the average throughput is greater than) the one obtained using current clustering protocols. We conclude by studying the sensitivity of our SEP protocol to heterogeneity parameters capturing energy imbalance in the network. We found that SEP yields longer stability region for higher values of extra energy brought by more powerful nodes.
Article
Full-text available
This paper studies LEACH protocol, and puts forward energy-LEACH and multihop-LEACH protocols. Energy-LEACH protocol improves the choice method of the cluster head, makes some nodes which have more residual energy as cluster heads in next round. Multihop-LEACH protocol improves communication mode from single hop to multi-hop between cluster head and sink. Simulation results show that energy-LEACH and multihop-LEACH protocols have better performance than LEACH protocols.
Conference Paper
Full-text available
Energy conservation plays a crucial in wireless sensor networks since such networks are designed to be placed in hostile and nonaccessible areas. While battery-driven sensors will run out of battery sooner or later, the use of renewable energy sources such as solar power or gravitation may extend the lifetime of a sensor network. We propose to utilize solar power in wireless sensor networks and extend LEACH a well-known cluster-based protocol for sensor networks to become solar-aware. The presented simulation results show that making LEACH solar-aware significantly extends the lifetime of sensor networks.
Article
In order to prolong the network lifetime, energy-efficient protocols should be designed to adapt the characteristic of wireless sensor networks. Clustering Algorithm is a kind of key technique used to reduce energy consumption, which can increase network scalability and lifetime. This paper studies the performance of clustering algorithm in saving energy for heterogeneous wireless sensor networks. A new distributed energy-efficient clustering scheme for heterogeneous wireless sensor networks is proposed and evaluated. In the new clustering scheme, cluster-heads are elected by a probability based on the ratio between residual energy of node and the average energy of network. The high initial and residual energy nodes will have more chances to be the cluster-heads than the low energy nodes. Simulational results show that the clustering scheme provides longer lifetime and higher throughput than the current important clustering protocols in heterogeneous environments.
Article
In this work, performance evaluation of LEACH and LEACH-C protocols based on NS2 is depicted, which helps to reveal the regularity how performances of these two routing protocols change with the sink locations. For a more accurate description of this regularity, two novel concepts are proposed, i.e., Sensor Node Distribution Gravity and Distance Metric between sink and Gravity. Simulation results show that a distance threshold area, which is a key factor for choosing between LEACH and LEACH-C protocols, can be achieved.
Article
The clustering Algorithm is a kind of key technique used to reduce energy consumption. It can increase the scalability and lifetime of the network. Energy-efficient clustering protocols should be designed for the characteristic of heterogeneous wireless sensor networks. We propose and evaluate a new distributed energy-efficient clustering scheme for heterogeneous wireless sensor networks, which is called DEEC. In DEEC, the cluster-heads are elected by a probability based on the ratio between residual energy of each node and the average energy of the network. The epochs of being cluster-heads for nodes are different according to their initial and residual energy. The nodes with high initial and residual energy will have more chances to be the cluster-heads than the nodes with low energy. Finally, the simulation results show that DEEC achieves longer lifetime and more effective messages than current important clustering protocols in heterogeneous environments.