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BEENISH: Balanced Energy Efficient Network Integrated Super Heterogeneous Protocol for Wireless Sensor Networks

  • COMSATS Institute of Information Technology, Wah Cantt.

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In past years there has been increasing interest in field of Wireless Sensor Networks (WSNs). One of the major issue of WSNs is development of energy efficient routing protocols. Clustering is an effective way to increase energy efficiency. Mostly, heterogenous protocols consider two or three energy level of nodes. In reality, heterogonous WSNs contain large range of energy levels. By analyzing communication energy consumption of the clusters and large range of energy levels in heterogenous WSN, we propose BEENISH (Balanced Energy Efficient Network Integrated Super Heterogenous) Protocol. It assumes WSN containing four energy levels of nodes. Here, Cluster Heads (CHs) are elected on the bases of residual energy level of nodes. Simulation results show that it performs better than existing clustering protocols in heterogeneous WSNs. Our protocol achieve longer stability, lifetime and more effective messages than Distributed Energy Efficient Clustering (DEEC), Developed DEEC (DDEEC) and Enhanced DEEC (EDEEC).
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arXiv:1303.5285v1 [cs.NI] 21 Mar 2013
Procedia Computer Science 00 (2013) 1–6
International Workshop on Body Area Sensor Networks (BASNet-2013)
BEENISH: Balanced Energy Ecient Network Integrated
Super Heterogenous Protocol for Wireless Sensor Networks
T. N. Qureshi£, N. Javaid£, A. H. Khan£, A. Iqbal£, E. Akhtar, M. Ishfaq§
£COMSATS Institute of Information Technology, Islamabad, Pakistan.
University of Bedfordshire, Luton, UK.
§King Abdulaziz University, Rabigh, Saudi Arabia.
In past years there has been increasing interest in field of Wireless Sensor Networks (WSNs). One of the major issue of
WSNs is development of energy ecient routing protocols. Clustering is an eective way to increase energy eciency.
Mostly, heterogenous protocols consider two or three energy level of nodes. In reality, heterogonous WSNs contain large
range of energy levels. By analyzing communication energy consumption of the clustersand large range of energy levels
in heterogenous WSN, we propose BEENISH (Balanced Energy Ecient Network Integrated Super Heterogenous)
Protocol. It assumes WSN containing four energy levels of nodes. Here, Cluster Heads (CHs) are elected on the bases
of residual energy level of nodes. Simulation results show that it performs better than existing clustering protocols
in heterogeneous WSNs. Our protocol achieve longer stability, lifetime and more eective messages than Distributed
Energy Ecient Clustering (DEEC), Developed DEEC (DDEEC) and Enhanced DEEC (EDEEC).
2013 Published by Elsevier Ltd.
Keywords: CH, residual energy, heterogeneity, ecient, WSNs.
1. Introduction
Wireless Sensor Networks (WSNs) [1, 2, 3] have become popular in variety of applications such as
military surveillance, environmental, transportation trac, temperature, pressure and vibration monitoring.
To achieve fault tolerance, WSNs consist of hundreds or even thousands of sensor randomly distributed with
in the region [4, 5, 6]. All the nodes report sensed data to Base Station (BS) often called sink. Nodes in
WSNs are power constrained due to limited battery resource, and they might be placed where they can not
be accessed, so,impossible to recharge or replace. To save energy, regular and long distance communication
should be avoided to prolong network lifetime [1]. Sensor nodes take self decisions to accomplish sensing
tasks, constructing network topology and routing policy. Therefore, it become important to design energy
ecient algorithm for enhancing robustness against node failures and extending lifetime of WSNs.
Eciently Grouping sensor nodes in form of clusters is beneficial in minimizing the energy utilization.
Numerous energy ecient protocols are made based on clustering structure[1, 7, 8]. In clustering, nodes
assemble themselves in form of clusters with one node acting as the Cluster Head (CH). All cluster member
nodes transmit sensed data to their CH, while the CH aggregate data received and forward it to the remote
2/Procedia Computer Science 00 (2013) 1–6
BS [9, 10]. Clustering can be formed in two kind of networks i.e., homogenous and heterogeneous. WSNs
having nodes of same energy level are called homogenous WSNs. Low Energy Adaptive Clustering Hierar-
chy (LEACH) [11], Power Ecient Gathering in Sensor Information Systems (PEGASIS) [12] and Hybrid
Energy-Ecient Distributed Clustering (HEED) [13] are examples of cluster based protocols which are
designed for homogenous WSNs. These algorithms poorly perform in heterogeneous regions. Nodes have
less energy will expire faster than high energy nodes because these homogenous clustering based algorithms
are incapable to treat every node with respect to energy. In heterogeneous WSNs, nodes are deployed with
dierent initial energy levels. Heterogeneity in WSN may be the result of re-energizing of WSN in order to
extend the network lifetime [14, 15, 16]. Stable Election Protocol (SEP) [14], Distributed Energy Ecient
Clustering (DEEC) [17], Developed DEEC (DDEEC) [18], Enhanced DEEC (EDEEC) [19] are protocols
for heterogenous WSNs.
2. Radio Dissipation Model
The radio energy model describes that l-bit message is transmitted over a distance das in [10, 11] as
shown in Fig. 1.
Fig. 1. Radio Energy Dissipation Model
lEelec +lεf s d2,d<d0
lEelec +lεmpd4,dd0(1)
Where Eelec is energy used per bit to run transmitter or receiver circuit. Free space (f s) model is used
if distance is in less than threshold otherwise multi path (mp) model. Now, total energy dissipated in the
network during a round is given below, as supossed [10, 11].
Eround =L(2NEelec +NEDA +kεmpd4
toBS +Nεf s d2
toCH) (2)
Where, k=number of clusters,
EDA=Data aggregation cost expended in CH
dtoBS =Average distance between CH and BS
dtoCH=Average distance between cluster members and CH
Assuming all nodes are uniformly distributed over network so, dtoBS and dtoCH can be calculated as
following as in [10, 11]:
dtoCH =M
2πk,dtoBS =0.765 M
By finding the derivative of ERound with respect to kto zero, we get the kopt optimal number clusters as
in [10, 11, 17].
kopt =N
2πrεf s
toBS (4)
/Procedia Computer Science 00 (2013) 1–6 3
3. The BEENISH Protocol
In this section, we present details of our BEENISH protocol. BEENISH implements the same concept
as in DEEC, in terms of selecting CH which is based on residual energy level of the nodes with respect to
average energy of network. However, DEEC is based on two types of nodes; normal and advance nodes.
BEENISH uses the concept of four types of nodes; normal, advance, super and ultra-super nodes.
Let nishows the rounds for a node sito become CH, we refer it as rotating epoch. CH has to consume
more energy as compare to member nodes. In homogeneous networks, to ensure average poptNCHs in
each round, LEACH let every node si(i=1,2, ....N) to become CH once in every ni=1
popt rounds. During
operation of WSN all the nodes does not own the same remaining energy. So, if the epoch niis kept equal
for all nodes as in LEACH then energy is not eciently distributed and nodes having low energy die before
high energy nodes. BEENISH choose dierent epoch nifor dierent nodes with respect to their remaining
energy Ei(r). High energy nodes are more often elected as CH as compare to low energy nodes. So, high
energy nodes have smaller epoch nias compare to high energy nodes . In BEENISH ultra-super nodes
are largely elected as CH as compare to super, advance and normal nodes, and so, on. In this way energy
consumed by all nodes is equally distributed.
Let pi=1
niis probability of node to become CH during epoch nirounds. When all the nodes have same
every level at each epoch, selecting the average probability pito be popt can ensure that there are poptNCHs
every round and approximately all nodes die at the same time. If nodes are having dierent energy then
nodes with more energy have pilarger than popt.
In BEENISH, average energy of rth round can be obtained as follows and as supposed in DEEC:
NEtotal(1 r
R) (5)
Ris showing total rounds from the start of network to the all nodes die and can be estimated as in DEEC
and given as under:
Eround (6)
Eround is the energy dissipated in a network during single round as given in 2.
To achieve the optimal number of CH at start of each round, node sidecides whether to become a CH
or not based on probability threshold calculated by expression in the following equation, and as supposed in
[11, 17].
1pi(rmod 1
Pi)if siǫG
0otherwise (7)
Where Gis the set of nodes eligible to become CH. If a node sihas not been CH in the most recent ni
then it belongs to set G. Random number between 0 and 1 is selected by nodes belonging to set G. If the
number is less than threshold T(si), the node siwill be CH for that current round.
In real scenarios, WSNs have more greater than two or three energy levels of nodes. In WSN due to
random CH selection, large range of energy levels are created. So, as much more energy levels we quantize
and define dierent probability for every energy level will lead to as much better results and lead to energy
eciency. In BEENISH, we first time use concept of four level heterogeneous network having normal,
advance, super and ultra-super nodes. The probabilities for four types of nodes are given below:
popt Ei(r)
(1+m(a+m0(a+b+m1(b+u)))) ¯
E(r)siis the normal node
popt (1+a)Ei(r)
(1+m(a+m0(a+b+m1(b+u)))) ¯
E(r)siis the advanced node
popt (1+b)Ei(r)
(1+m(a+m0(a+b+m1(b+u)))) ¯
E(r)siis the super node
popt (1+u)Ei(r)
(1+m(a+m0(a+b+m1(b+u)))) ¯
E(r)siis the ultra super node
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Threshold is calculated for CH selection of normal, advanced, super and ultra-super nodes by putting
above values in equation below.
1pi(rmod 1
Pi)if siǫG
0otherwise (9)
In the equation of T(si), we find that nodes with greater remaining energy Ei(r) at round rare more
possibly to become CH as compare to low energy nodes. The aim of this mechanism is to eciently divide
the energy consumption in the network and extend the stability period which is defined by first node die and
network lifetime defined by last node die from the start of WSN.
Simulations show that BEENISH is more ecient protocol than DEEC, DDEEC and EDEEC for WSN
containing four and multi level heterogeneity in terms of first node die and last node die.
4. Simulations and Results
This section evaluates the performance of BEENISH protocol using MATLAB. We consider a WSN
containing of N=100 nodes randomly deployed inside 100m×100mfield. For simplicity, we assume that
all nodes are either fixed or micro-mobile and ignore energy loss due to signal collision and interference
between signals of dierent nodes that are due to dynamic random channel conditions. Our simulations
use radio parameters mentioned in Table 1. Protocols compared with BEENISH include DEEC, DDEEC
and EDEEC. We estimated performance for the case of four level and multi-level heterogeneous WSNs. We
observe performance of DEEC, DDEEC, EDEEC and BEENISH for four level and multi-level heterogenous
WSNs. We take the parameters; m=0.5,m0=0.3,m1=0.2,a=1.5,b=2.0and u =2.5, containing
50 normal nodes having E0energy, 35 advanced nodes having 1.5 times more energy than normal nodes,
12 super nodes containing 2 times more energy than normal nodes and 3 ultra-super nodes containing 2.5
times more energy than normal nodes. First node for DEEC, DDEEC, EDEEC and BEENISH dies at 1103,
1367, 1421 and 1661 rounds, respectively. All nodes die at 5191, 3976, 6866 and 6903 rounds, respectively.
Fig. 3 shows BEENISH sends more data to BS than DEEC, DDEEC and EDEEC. BEENISH is ecient as
compare to all protocols in terms of stability period, network life time and packets sent to the BS.
0 2000 4000 6000 8000 10000
Number of Rounds
Number of Nodes Alive
Fig. 2. Alive Nodes During Network Lifetime
/Procedia Computer Science 00 (2013) 1–6 5
0 2000 4000 6000 8000 10000
4.5 x 10
Number of Rounds
Number of Packets sent to BS
Fig. 3. Packets sent to BS
5. Conclusion
Our proposed BEENISH is energy-aware clustering protocol for heterogenous WSNs, with the concept
of four types of nodes. Election of CH based on residual and average energy of the network. So, nodes with
high energy have more chances to get selected as CH, as compare to the low energy nodes. BEENISH is
proved to be the most ecient protocols as compared to DEED, DDEEC and EDEEC for all types of WSNs
in terms of stability period, network lifetime and throughput.
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... Moreover, it also enables data aggregation, saving the nodes' energy further. Moreover, there are two strategic classes of the clustering techniques-static clustering [6]- [10] and dynamic clustering [11]- [19]. In the static clustering technique, once formed, clusters remain constant for the rest of the network lifetime or until they are not resolved administratively. ...
... Clustering has already established its importance and acceptability in traditional wireless sensor networks to a great extent, especially with regard to the features like scalability and energy efficiency. Many works, [8], [19], [23]- [36], have already been done referring to clustering as the key to achieving the objectives like scalability and energy efficiency. Clustering has not only proved its significance in the traditional WSNs but also in the IoT-based HWSN to achieve energy efficiency. ...
... However, the scheme-EDDEEC, like its precursors [15]- [17], heavily depends upon the heterogeneity-specific probability-based solution for CHs' selection and considers only three-level heterogeneous networks. Qureshi et al. [19] proposed an extension of [18] accommodating four types of sensor nodes. Like its parent schemes, [19] also uses uniquely defined probabilistic CH-selection equations pertaining to each class of sensor nodes. ...
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Internet-of-Things (IoT)-based Heterogeneous Wireless Sensor Network (HWSN) has emerged as a prevalent technology that plays a significant role in developing various human-centric applications. Like in a wireless sensor network (WSN), energy is also the most crucial resource in IoT-based HWSN. The researchers have proposed many works to achieve energy-efficient network operations by minimizing energy usage. A vast proportion of these works emphasize using the clustering approach, which has proved its worth to a great extent. However, most schemes require the repeated formation of clusters incurring a significant amount of nodes’ energy in the clustering process. The protocol design of such schemes also varies with the changing levels of heterogeneity. In this work, a hybrid clustering scheme- An Energy-Efficient Hybrid Clustering Technique (EEHCT) has been proposed for IoT-based HWSN that minimizes the energy consumption in clusters’ formation and distributes the network load evenly irrespective of the heterogeneity level to prolong network lifetime. It appropriately utilizes dynamic and static clustering strategies to formulate the load-balanced clusters in the network. EEHCT establishes its supremacy over state-of-the-art schemes via an extensive set of simulations and experimentation in terms of multiple network performance metrics like stability, throughput, and network lifetime. Like, it achieves a gain up to 90.27% with respect to network lifetime over its peers in the standard operating conditions and under varying network configurations. In addition to quantitative analysis, a statistical analysis has also been provided to demonstrate the formation of energy-balanced clusters through the proposed scheme.
... Qureshi et al. [50] explored four types of nodes belonging to four energy levels and designed the Balanced Energy Efficient Network Integrated Super Heterogeneous (BEENISH) protocol. BEENISH used the relative ratio of residual energy to select cluster heads. ...
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Wireless sensor networks (WSN) are critical for IoT, smart cities, smart health, and other smart services. Network characteristics such as energy consumption, latency, dependability, and stability have a significant impact on WSN performance. However, the numerous capabilities of the nodes, as well as the adjustment of different properties, result in a heterogeneous network. A proper classification, assessment, and management of this heterogeneity are crucial for a long-term network operation. This article gives a full topological taxonomy of heterogeneity, as well as a detailed discussion on the effect of heterogeneity on many aspects of WSN. Comparative analysis of the effect of heterogeneity on different parameters of network performance establishes the advantage of heterogeneous WSN in modern networks. Different measurement methodologies for the estimation of heterogeneity are included in the paper. Relevance of properly managed heterogeneity in the state-of-the-art technologies are presented as the possible future applications.
... Energy-efficient clustering scheme (EECS) [46] is also another heuristic algorithm that reduces the unbalanced 3 Journal of Sensors consumption of energy by considering the three attributes and also considering the respective weight cost factor for the sensor node. EEHC (energy-efficient heterogeneous cluster scheme) [47] provides the election probability weights that are directly related to the residual energy of the sensor node, whereas BEENISH [48] (balanced energy-efficient network-integrated super heterogeneous) protocol is also a clustering algorithm that assigns one of the four energy levels to the sensor node and uses this energy level for selecting the cluster heads. Enhanced developed distributed energyefficient clustering for heterogeneous network (EDDEEC) [49] classifies nodes as normal nodes and advanced nodes and then changes the probability of becoming cluster heads. ...
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... From Eqs. (17) and (19), To determine E(r), take P i as the average probability. Nodes that have a high attempt to be the leader will have a higher energy than those with a low energy (Qureshi et al. 2013). ...
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There seem to be numerous items which have been developed using IoT devices and are network overhead. We must consider factors like reliability, minimal energy consumption, etc. To advance IoT, solutions must be found for issues with scalability, dependability, network optimization, and quality of service (QoS). The proposed approach considered a heterogeneous network with a long lifespan and high throughput while using less electricity. Specifications such as Area, Nodes, Sink location, and Data Aggregation must be given. Throughput, data communication rate, analysis of live nodes, and a reduction in node energy consumption are all factors in this method’s cluster head selection. But creating an embedded IoT system is complicated. We considered the ADEEC approach for autonomous cellular networks, which improves network performance and durability. It is possible to send messages in heterogeneous contexts more successfully than with current techniques. The experimental results of the proposed ADEEC outperform the throughput with 19% when compared to LEACH, 16.5% when compared to MODLEACH and 9.6% when compared to DEEC. The network life span of ADEEC outperforms 18% when compared to LEACH, 17% when compared to MODLEACH and 13% when compared to DEEC methods.
... with u >b >a. The nodes' selection as CHs is based on their types, their residual energy E i (r), and the rth network average energy E(r) as formulated by equation (10) below [26]: (10) As in EDEEC protocol, each node generates a random value between 0 and 1, if this value is less than the threshold T(S i ) calculated by equation (9) on the corresponding P i of equation (10), then the node becomes a CH. ...
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The design of efficient communication protocols for wireless sensor networks has aroused great interest in the research community, especially in the face of the limited energy of sensor nodes and the frequent change in network topology. Routing remains a challenging problem in wireless communications, as deploying or replacing sensor nodes in hazardous environments is difficult. Many studies have been devoted to alleviate certain limitations, such as clustering to maintain network connectivity, injecting heterogeneity to avoid the rapid death of nodes, or incorporating evolution-based optimization methods to find the best network configuration. This work combined heterogeneity and swarm-based optimization to efficiently balance energy consumption between nodes to increase network reliability. Specifically, this work employed the binary particle swarm optimizer and the binary artificial bees colony optimizer to find approximately the optimal set of cluster heads (CHs) with their optimal number. Based on the probabilistic principle of the heterogeneous protocols: SEP, EDEEC, and BEENISH, a new refined formulation of CHs selection using swarm optimization is proposed. The swarm flight is guided towards the best CHs with an objective function representing a good balance between the initial and residual energy of nodes. Compared to the standard heterogeneous protocols SEP, EDEEC, and BEENISH, the developed protocols significantly perform better in terms of stability (FND), the round of half nodes' death (HND), the network lifetime (LND), and energy saving. Indeed, the BABC-SEP was found 31,66% better than SEP in terms of remaining energy percentage, and CHs selection in EDEEC and BEENISH using BABC improved them by more than 20% in the percentage of remaining energy.
... They have reported the edge of distributed clustering over centralized clustering for WSN routing. Qureshi et al. [40] have designed an improved energy performance-based BEENISH protocol to be for the WSN networks. The reported lifetime is extended beyond the 2000 but at the cost of initial energy. ...
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The size of the wireless sensor network (WSN) is extending continually with use of IOT networks. The main difficulty for design wide area WSN is to maintain the higher stability period and energy efficiency (EE) for the routing protocols. The creation of clustering-based routing protocols was applied to the optimization of overall network energy. But, traditional clustering methods were unable to produce improved node heterogeneity, and extended network lifetime. Distributed clustering-based routing protocols are specially designed for enhancing the EE of the networks. In addition, EE can be improved by enhancing the heterogeneity of the node distribution. This paper aims to design the extended distributed clustering-based EE routing protocol. The heterogeneity of nodes is improved by introducing the additional intermediate advanced nodes layer in the network. Therefore, paper proposed to design the Multi-Level Heterogynous EDEEC rousing protocol called ML-HEDEEC by adapting optimum energy enhancing parameters. The notes are divided to normal, advance, advance-interdicted and supper nodes based on the energy allocated to them. The probability of nodes is modified for better clustering and cluster head election by introducing additional energy enhancement parameter. In addition, it is proposed to automatically adopt the network initial energy based on the scaling of network dimensions. This may lead to enhance EE of the network and may improve stability period. Finally, the results are evaluated for a case of WSN routing under the dynamic sink locations. Performance is compared for various distributed clustering protocols and other state of art protocols viz. LEACH, SEP, zonal- SEP, DEC considering the network scaling. Various performances of the network stability, packets sent to base station, and lifetime,.are defined for result evaluation. The network dimensions are scaled up to four times and proposed protocol is tested under scaling consideration. In addition, sink locations are also varied for dynamic sink locations performance evaluation. Overall paper efficiently designed and test heterogeneous improved routing protocol with extended lifetime and stability.
With the advancement in recent technologies, wireless sensor networks (WSNs) have emerged to become one of the key research areas. Sensor nodes in WSN are deployed randomly to sense the events that occur in an area. Clustering of sensor nodes in a wireless sensor network will result in better energy efficiency and topology management. In many scenarios, wireless sensor networks are deployed in remote areas and in hostile environments where batteries cannot be recharged or replaceable. In real world applications, heterogeneous sensor nodes with different initial energies in a WSN are more preferable to prolong stability period, network lifetime, and throughput. The main objective of this article is to design and develop a cluster‐based energy efficient routing protocol for heterogeneous wireless sensor networks (CEER). The proposed CEER routing protocol is based on the residual energy of all the sensor nodes in each round, distance of each sensor node from the base station, weighted election probabilities and reliability of a sensor node and the network. It is found from the results that, the proposed CEER routing protocol provides better stability, network lifetime, and throughput as compared with the existing routing protocols of heterogeneous wireless sensor networks.
Energy saving is the rudimentary provocation in (WSNs). Energy of the WSNs can be preserved in many ways such as duty-cycling of nodes, clustering, Energy proficient routing, and data Energy etc. Good WSNs work on the principle of two issue firstly Energy saving and secondly good network lifetime. In WSNs protocols are found of two types heterogeneous and homogenous. Different types of nodes are used in this WSNs. Different Energy levels are found in these nodes. Different nodes arrangement, clustering scheme and algorithms are used in these WSNs protocols. Heterogeneity is related to different Energy uses and different nodes clustering. We give a Review on Energy Saving Clustering Based Protocols of HWSN in this study.
Wireless sensor network is considered one of the dominant reformations among all revolutionary emerging technologies. Surplus of research work has been done in past years but still brawls such as power consumption, network lifespan, and stability of network are pestering WSN. For ensuring such credibility of sensor network energy, efficient routing protocol plays a significant role. Usually, there exists two, three, or four energy level of sensor nodes in a routing protocol. But in veracity, WSN comprises of sensor nodes of several energy levels. This paper proposes Enhanced Energy Conservation Routing Protocol (EECRP), where exist five levels of heterogeneity. CH is elected using the residual energy, average energy of sensor nodes, and the number of clusters used per round at the minimum side. Simulation shows that performance of EECRP is far better than SEP, TSEP, and BEENISH. It can be noticed that EECRP enhances the stability of network by 65.18%, 40.36%, and 30.88% in contrast to SEP, TSEP, and BEENISH as well as EECRP enhanced throughput by 66.68, 69.13, and 49.16% in contrast to SEP, TSEP, and BEENISH.KeywordsWireless sensor networksEnergy conservationLEACHDead nodesAlive nodes
Conference Paper
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Typically, a wireless sensor network contains an important number of inexpensive power constrained sensors, which collect data from the environment and transmit them towards the base station in a cooperative way. Saving energy and therefore, extending the wireless sensor networks lifetime, imposes a great challenge. Clustering techniques are largely used for these purposes. In this paper, we propose and evaluate a clustering technique called a Developed Distributed Energy-Efficient Clustering scheme for heterogeneous wireless sensor networks. This technique is based on changing dynamically and with more efficiency the cluster head election probability. Simulation results show that our protocol performs better than the Stable Election Protocol (SEP) by about 30% and than the Distributed Energy-Efficient Clustering (DEEC) by about 15% in terms of network lifetime and first node dies.
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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
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.
Many routing protocols on clustering structure have been proposed in recent years. In recent advances, achieving the energy efficiency, lifetime, deployment of nodes, fault tolerance, latency, in short high reliability and robustness have become the main research goals of wireless sensor network. Many routing protocols on clustering structure have been proposed in recent years based on heterogeneity. We propose EDEEC for three types of nodes in prolonging the lifetime and stability of the network. Hence, it increases the heterogeneity and energy level of the network. Simulation results show that EDEEC performs better than SEP with more stability and effective messages.
Wireless Sensor Networks (WSNs) are expected to find wide applicability and increasing deployment in near future. In this paper, we propose a new protocol, Threshold Sensitive Stable Election Protocol (TSEP), which is reactive protocol using three levels of heterogeneity. Reactive networks, as opposed to proactive networks, respond immediately to changes in relevant parameters of interest. We evaluate performance of our protocol for a simple temperature sensing application and compare results of protocol with some other protocols LEACH, DEEC, SEP, ESEP and TEEN. And from simulation results it is observed that protocol outperforms concerning life time of sensing nodes used.
Wireless Sensor Networks (WSNs) contain numerous sensor nodes having limited power resource, which report sensed data to the Base Station (BS) that requires high energy usage. Many routing protocols have been proposed in this regard achieving energy efficiency in heterogeneous scenarios. However, every protocol is not suitable for heterogeneous WSNs. Efficiency of protocol degrades while changing the heterogeneity parameters. In this paper, we first test Distributed Energy- Efficient Clustering (DEEC), Developed DEEC (DDEEC), Enhanced DEEC (EDEEC) and Threshold DEEC (TDEEC) under several different scenarios containing high level heterogeneity to low level heterogeneity. We observe thoroughly regarding the performance based on stability period, network life time and throughput. EDEEC and TDEEC perform better in all heterogeneous scenarios containing variable heterogeneity in terms of life time, however TDEEC is best of all for the stability period of the network. However, the performance of DEEC and DDEEC is highly effected by changing the heterogeneity parameters of the network.
This work focusses on analyzing the optimization strategies of routing protocols with respect to energy utilization of sensor nodes in Wireless Sensor Network (WSNs). Different routing mechanisms have been proposed to address energy optimization problem in sensor nodes. Clustering mechanism is one of the popular WSNs routing mechanisms. In this paper, we first address energy limitation constraints with respect to maximizing network life time using linear programming formulation technique. To check the efficiency of different clustering scheme against modeled constraints, we select four cluster based routing protocols; Low Energy Adaptive Clustering Hierarchy (LEACH), Threshold Sensitive Energy Efficient sensor Network (TEEN), Stable Election Protocol (SEP), and Distributed Energy Efficient Clustering (DEEC). To validate our mathematical framework, we perform analytical simulations in MATLAB by choosing number of alive nodes, number of dead nodes, number of packets and number of CHs, as performance metrics.
Wireless Sensor Networks (WSNs) are increasing to handle complex situations and functions. In these networks some of the nodes become Cluster Heads (CHs) which are responsible to aggregate data of from cluster members and transmit it to Base Stations (BS). Those clustering techniques which are designed for homogenous network are not enough efficient for consuming energy. Stable Election Protocol (SEP) introduces heterogeneity in WSNs, consisting of two type of nodes. SEP is based on weighted election probabilities of each node to become CH according to remaining energy of nodes. We propose Heterogeneity-aware Hierarchal Stable Election Protocol (HSEP) having two level of energies. Simulation results show that HSEP prolongs stability period and network lifetime, as compared to conventional routing protocols and having higher average throughput than selected clustering protocols in WSNs.