American Journal of Sustainable Cities and Society
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Issue 3, Vol. 1 January 2014
ISSN 2319 – 7277
FHEER: FUZZY COST BASED HEER FOR
REACTIVE WSNs
HARNOOR SINGH, M.TECH(E.C.E)
ASST. PROF. HARMANDEEP SINGH SANGHA
G.I.M.E.T COLLEGE AMRITSAR, PANJAB, INDIA
Abstract:
Energy efficiency is a key design purpose in most of the study related to wireless sensor networks because the nodes are
rigorously energy controlled, and battery replacement is often not practical. In this research paper, there is improvement in
the performance of the HEER using improved fuzzy based cluster head selection. The HEER has used different probability
function for cluster head selection for selecting the best cluster head by using the residual energy. The fuzzy cost has been
evaluated on the basis of the residual energy and the node centrality. The fuzzy cost is dynamic in nature as it has been
evaluated in each round. Thus it has provided more better results due to its adaptive nature i.e. has change as the residual
energy changes. The main advantage of the proposed protocol is that the optimum numbers of clusters are formed in every
round, which is almost impossible in LEACH and also not guaranteed in HEER. The overall goal of this work is to
increase the network lifetime by using the integrated HEER protocol which will increase the network life time by using
thresholding and if then rules based algorithm and optimum size cluster formation mechanisms.
Keywords: FUZZY, WSN
1.Introduction
Energy efficiency [1] - [4] is a key design purpose in most of the study related to wireless sensor networks because the
nodes are rigorously energy controlled, and battery replacement is often not practical. Cluster heads also serve as synthesis
points for aggregation of data, so that the amount of data that is actually transmitted to the base station is reduced.
Improving the lifetime in wireless sensor networks is important because the sensor nodes in wireless networks are
controlled by restricted energy [2] . The way to enhance WSN lifetime is to extend energy-efficient protocol for reducing
energy conservation. Sensor nodes usually have limited energy supply and they are impractical to recharge. Energy is a
critical issue in WSN, due of limited energy in sensor nodes, so to save energy clustering method was introduced; in which
out of thousands of nodes few nodes become cluster head and they handle the entire network. This network consists of
huge number of nodes which intellect data from an impossibly unreachable area and sends their information toward a base
station called a sink. Since, sensor nodes are power controlled, numerous and long-distance transmissions should be kept
least in order to expand the network lifetime. Thus, direct interactions between nodes and the base station are not confident.
One efficient move toward is to divide the network into a number of clusters, each electing one node as its cluster head.
The cluster head collects data from sensors in the cluster which will be combined and transmitted to the base station. Thus,
only some nodes are necessary to broadcast data over a long distance and the rest of the nodes will have to do only shortdistance communication. Then, more energy is saved and usually network lifetime can thus be extended. A lot of energyefficient routing protocols are designed on the clustering formation where cluster heads are chosen frequently. HEER
enhances the stable region for clustering hierarchy process for a reactive network in homogeneous and heterogeneous
environment. It does not require any global knowledge of energy at any election round.
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2. Literature Survey
N. Javaid et al. [1] In this examination paper they have proposed a convention intended for the qualities of receptive
homogeneous Wsns, HEER (Hybrid Energy Efficient Reactive) convention. In HEER, Cluster Head (CH) determination is
focused around the degree of leftover vitality of hub and normal vitality of system. Besides, to moderate more vitality, we
present Hard Threshold (HT) and Soft Threshold (ST). At long last, recreations demonstrate that the convention has
delayed the system lifetime as well as altogether expanded the steadiness period. D. Kumar et al. [5] In this paper Energy
Efficient Clustering and Data Aggregation (EECDA) convention for the heterogeneous Wsns that consolidates the plans of
vitality proficient bunch based directing and information total to attain a superior execution regarding lifetime and strength.
EECDA convention incorporates a novel bunch head race method and a way would be chosen with greatest entirety of
vitality deposits for information transmission rather than the way with least vitality utilization. EECDA convention adjusts
the vitality utilization and delays the system lifetime by a variable of 51% when contrasted and Low-Energy Adaptive
Clustering Hierarchy (LEACH), 35% with Energy Efficient Hierarchical Clustering Algorithm (EEHCA) and 10% with
Effective Data Gathering Algorithm (EDGA). Parul Saini et al. [6] This paper examination for attaining the vitality
proficiency, lifetime, organization of hubs, flaw tolerance, dormancy, in short high dependability and vigor have turned
into the primary exploration objectives of remote sensor system. They propose EDEEC for three sorts of hubs in delaying
the lifetime and steadiness of the system. Consequently, it expands the heterogeneity and vitality level of the system.
EDEEC performs better than SEP with more dependability and powerful messages. E-DEEC includes heterogeneity in the
system by presenting the super hubs having vitality more than typical and progressed hubs and separate probabilities. The
result demonstrates that E-DEEC has better execution as contrasted with SEP regarding parameters utilized. It augments
the lifetime and dependability of the system. G.jayaseelan et al. [7] This paper is relies on upon bunch based plan that
augments High Energy First (HEF) grouping calculation and empowers multi-bounce transmissions among the bunches by
joining the choice of helpful sending and getting hubs. The execution of the proposed framework is assessed regarding
vitality effectiveness and unwavering quality. Reproduction results demonstrate that colossal vitality funds could be
attained by embracing hard system lifetime plan among the bunches. The proposed agreeable MIMO plan delays the
system lifetime with 75% of hubs staying alive when contrasted with LEACH convention. HEF calculation demonstrated
that the system lifetime might be effectively drawn out by utilizing fluffy variables (fixation, vitality and thickness). Giving
a dependable framework conduct with an ensured hard system lifetime is a testing undertaking to security discriminating
and exceptionally solid WSN applications. K. Balamurugan et al.[8] This paper centered to maintain a strategic distance
from copy transmission, hub reconfiguration and force utilization in Wireless Sensor Networks (WSN). Remote sensor
system obliges hearty and vitality effective correspondence conventions to minimize the vitality utilization however much
as could reasonably be expected. The plan amplifies High Energy First (HEF) grouping calculation and empowers multibounce transmissions among the groups by joining the choice of agreeable sending and getting hubs. The work proposed
centers to create any hub to go about as bunch head (CH) rather than influenced CH as a result of need to get an
information from CH . To decrease vitality utilization, proposed plan reaches out with the assistance of S-MAC layer to get
the effective vitality sparing. Reproduction results demonstrate that enormous vitality investment funds might be attained
by embracing hard system lifetime plan among the groups. Harneet Kour et al. [9] This paper proposes the convention
named Heterogeneous - Hybrid Energy Efficient Distributed Protocol (H-HEED) for Wireless Sensor Network to delay the
system lifetime. At last the reenactment result shows that H-HEED attains longer lifetime and more compelling information
bundles in examination with the HEED convention. Distinctive level of heterogeneity: 2-level, 3-level and multi-level
regarding the hub vitality. We have assessed the execution of the proposed H-HEED with HEED convention utilizing
Matlab. It is watched that there is critical change in the lifetime in the event of HHEED convention in correlation with
HEED convention in light of the fact that the quantity of rounds is most extreme with multi-level H-HEED. Shilpa Mahajan
et al. [10] In this article an overview of different vitality productive systems in a heterogeneous remote sensor system is
carried out. It is typically arbitrarily sent in difficult to reach landscapes, fiasco territories, or contaminated situations,
where battery substitution or energize is troublesome or even difficult to be performed. Therefore, arrange lifetime is of
vital vitality to a WSN. They first diagram the fundamental system radio model and how this model could be utilized to
study different exchanges off between system sending expenses, bunching approach as far as vitality
effectivenessG.jayaseelan et al. [7] This paper is relies on upon group based plan that expands High Energy First (HEF)
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bunching calculation and empowers multi-jump transmissions among the bunches by fusing the determination of agreeable
sending and accepting hubs. The execution of the proposed framework is assessed as far as vitality proficiency and
unwavering quality. Recreation results demonstrate that huge vitality funds might be accomplished by embracing hard
system lifetime plan among the bunches. The proposed helpful MIMO plan delays the system lifetime with 75% of hubs
staying alive when contrasted with LEACH convention. HEF calculation demonstrated that the system lifetime could be
effectively delayed by utilizing fluffy variables (fixation, vitality and thickness). Giving a reliable framework conduct with
an ensured hard system lifetime is a testing errand to security discriminating and very solid WSN applications. K.
Balamurugan et al.[8] This paper centered to dodge copy transmission, hub reconfiguration and force utilization in Wireless
Sensor Networks (WSN). Remote sensor system obliges vigorous and vitality productive correspondence conventions to
minimize the vitality utilization however much as could be expected. The plan amplifies High Energy First (HEF) bunching
calculation and empowers multi-jump transmissions among the bunches by joining the choice of helpful sending and
getting hubs. The work proposed centers to create any hub to go about as bunch head (CH) rather than influenced CH in
view of need to get an information from CH . To diminish vitality utilization, proposed plan stretches out with the
assistance of S-MAC layer to get the proficient vitality sparing. Recreation results demonstrate that gigantic vitality funds
could be attained by receiving hard system lifetime plan among the groups. Harneet Kour et al. [9] This paper proposes the
convention named Heterogeneous - Hybrid Energy Efficient Distributed Protocol (H-HEED) for Wireless Sensor Network
to delay the system lifetime. At long last the reenactment result shows that H-HEED accomplishes longer lifetime and more
successful information parcels in correlation with the HEED convention. Distinctive level of heterogeneity: 2-level, 3-level
and multi-level regarding the hub vitality. We have assessed the execution of the proposed H-HEED with HEED
convention utilizing Matlab. It is watched that there is critical change in the lifetime in the event of HHEED convention in
correlation with HEED convention on the grounds that the quantity of rounds is greatest with multi-level H-HEED. Shilpa
Mahajan et al. [10] In this article a review of different vitality proficient methods in a heterogeneous remote sensor system
is carried out. It is typically arbitrarily sent in blocked off territories, catastrophe regions, or dirtied situations, where battery
substitution or revive is troublesome or even difficult to be performed. Hence, organize lifetime is of essential significance
to a WSN. They first blueprint the fundamental system radio model and how this model could be utilized to study different
exchanges off between system arrangement expenses, grouping approach regarding vitality productivity. Khalid Hussain et
al. [15] In this study a bunch is regulated by a pioneer hub called Cluster Head (CH). Reason for CH is to keep up the
rundown of associated hubs and correspond with other group heads. CH decision is an imperative process in group based
systems. Numerous parameters might be utilized for choosing the hub as a bunch head, for example, area, versatility,
battery, throughput and so forth. Various methods for selecting bunch head have been proposed via analysts, concentrating
on parameters. Very nearly all the intra group activity must pass through the CH; in this manner it must have the capacity
to handle greatest bundles. K.ramesh et al. [16] In this exploration they considered the Wireless Sensor Network, sensor
hubs life time as the most discriminating parameter. Numerous examines on these lifetime augmentation are roused by
LEACH plan, which by permitting pivot of group head part among the sensor hubs tries to appropriate the vitality
utilization over all hubs in the system. Choice of group head for such pivot significantly influences the vitality effectiveness
of the system. Diverse correspondence conventions and calculations are explored to discover approaches to decrease power
utilization. Correlation of their expenses of CH determination in diverse rounds , transmission system and different impacts
like group development, circulation of CH and formation of groups demonstrates a need of a joined procedure for better
comes about. Ying Huang et al. [17] in this study they considered bunch head that devours more vitality than other part
hubs, in light of the fact that it accumulates information from its part hubs, forms it (e.g. information combination), and
exchanges information to the sink hub or to the base station that perhaps found remotely. In this way, the bunch head ought
to be chosen intermittently inside the group to evade the fast passing of the head hub and make all hub burdens disseminate
equitably. In light of the far reaching investigating of those calculations, for example, LEACH, a group calculation for
choosing bunch heads focused around limit vitality is introduced. The lifetime is proposed to be communicated as to both
the most extreme last hub passing on time and the base time contrast between the last hub biting the dust and the first hub
kicking the bucket. With a specific end goal to acquire the impact, edge vitality was acquired and assessed. The limit
vitality is identified with the beginning vitality of every hub (Eo), number of hubs (n), vitality utilization of bunch head
(Ecch), and vitality utilization of group parts (Eccm). The fundamental intention is to get the most extreme system lifetime.
At the point when the ideal Dynamic limit vitality is adjusted in the calculation, the lifetime could be drawn out while the
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execution of system can keep up unabated. Results exhibit that this calculation which is more compelling directing
convention draws out the system lifetime when bunch heads are chosen with the ideal edge vitality. Ahmed Salim et al.
[18] In this they examined about remote sensor systems (Wsns) that are made out of a lot of people minimal effort, low
power gadgets with sensing, neighborhood transforming and remote correspondence abilities. Late advances in remote
systems have prompted a lot of people new conventions particularly intended for Wsns where vitality mindfulness is a key
attention. The majority of the consideration, then again, has been given to the directing conventions since they may vary
relying upon the application and system construction modeling. Minimizing vitality dispersal and amplifying system
lifetime are critical issues in the outline of steering conventions for Wsns. In this paper, the low-vitality versatile bunching
progression (LEACH) directing convention is considered and made strides. They propose a bunching steering convention
named intra-adjusted LEACH (IBLEACH), which broadens LEACH convention by adjusting the vitality utilization in the
system. The reproduction results demonstrate that IBLEACH outflanks LEACH and the current upgrades of LEACH as far
as system lifetime and vitality utilization minimization.
3. Proposed Algorithm
Figure 1 has shown the flow chart of the proposed algorithm. Here Probabilities of normal (eq.1), advance (eq.2), super
nodes (eq.3) and for all types of nodes having same remaining energy (eq.4) for CH selection for CH selection in are
showing below in the algorithm.
Step 1: Initialize the WSNs with required parameters like nodes position, sink position, initial energy of each kind of nodes
etc.
Fig 1: Proposed Algorithm
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Step 2: for every node i repeat the following steps until all nodes become dead.
Step 3: Select cluster head using following equations i.e. normal (eq.1), advance (eq.2), super nodes (eq.3) and for all types
of nodes having same remaining energy (eq.4).
P opt E i (r)
1+m a+m o b Ē(r)
P opt (1+a)E i (r)
1+m a+m o b Ē(r)
P opt (1+b)(r)
1+m a+m o b Ē(r)
c
∗ Fuzzy_cost
for normal nodes if E i (r)>Tabsolute
(1)
∗ Fuzzy_cost
for advance node if E i (r)>T absolute
(2)
∗ Fuzzy_cost
for super nodes if E i r > Tabsolute
(3)
P opt (1+b)E i (r)
1+m a+m o b Ē(r)
∗ Fuzzy_cost
for nor, adv, sup nodes if E i r ≤ T absolute
(4)
Step 4: Evaluate the energy dissipation and update the remaining energies it. Where distance will be evaluated using eq. 5
and updating of energy will be based upon the eq. 6 and eq. 7.
d toCH =
M
√2πk
, d toBS = 0.765
M
(5)
2
E Tx l , d = Ɩ E elec + Ɩε fs d2 ,
d <d0 (6)
E Tx l , d = Ɩ E elec + Ɩεmp d4 ,
4. Results and Discussions
d ≥ d₀
(7)
The proposed algorithm is evaluated through the performance of the HEER protocol using different bench marked
parameters like network lifetime. As shown in the given figures below, we are comparing the result of parameters. As a
result it shows that our proposed approach results are much better than existing approaches. After the results, we are
comparing the proposed approach against the existing methods. In order to implement the proposed algorithm, design and
implementation has been done.
Table 1: Experimental Setup
Parameter
Value
Area(x,y)
Base station(x,y)
Nodes(n)
Probability(p)
100,100
50,50
100
0.1
Initial Energy(Eo)
0.5
transmiter_energy
receiver_energy
Free space(amplifier)
Multipath(amplifier)
a (energy factor between normal and
advance nodes)
50nJ/bit
50nJ/bit
10nj/bit/m2
0.0013pJ/bit/m4
1
Maximum lifetime
Message size
m (fraction of advanced nodes)
Effective Data aggregation
7500
4000 bits
0.1
5nJ/bit/signal
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Table 1 has shown various constants and variables required to simulate this work. These parameters are standard values
used as benchmark for WSNs.
On applying fuzzy cost functions, following results will be achieved.
Fig.2) when all the sensor nodes are alive
Fig.2 is showing the active environment of fuzzy based HEER. Green diamond is representing the base station. Magenta
circle nodes are representing the normal sensor nodes. Cyan circle nodes are representing the advance sensor nodes and
green circle nodes are representing the super sensor nodes. Red stars are representing the cluster heads. Black lines are
representing how data communicate to the base station. Red lines are showing the Communication between member nodes
to cluster head.
Fig 2) when some of the sensor nodes are dead
Fig. 2 is showing the environment of fuzzy based HEER in which some of the nodes are dead. Dead nodes are representing
by red dot. Magenta circle nodes are representing the normal sensor nodes, cyan circle representing the advance nodes and
green circle nodes representing the super sensor nodes. Green diamond is representing the base station. Red lines are
showing the Communication between member nodes to cluster head.
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Fig.3 is showing the remaining energy. X-axis is representing the energy in joules. Y-axis is representing the number of
rounds.
Fig.3) Remaining energy
Fig. 4) Total number of packets sends to base station
Fig. 4 is showing total number of packet sent to base station. X-axis is representing number of packets. Y-axis is
representing the number of rounds.
Fig. 5) Total number of packets sends to cluster head
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Fig. 5 is showing total number of packet sent to cluster head. X-axis is representing number of packets. Y-axis is
representing the number of rounds.
Fig.6 is showing total number of dead nodes. X-axis is representing dead nodes. Y-axis is representing the number of
rounds. It is showing that the first node dead at 356 round and last node dead at 2107 round.
Fig.6) total number of dead nodes
The proposed algorithm is applied using various performance parameters such as network lifetime Fig 7 has shown the
comparison among HEER and proposed with respect to number of Alive nodes in each round. It has been clearly shown
that the Alive nodes with respect to rounds in case of the proposed are quite more than the HEER. It has obviously
demonstrated that the proposed algorithm is relatively better than the available techniques.
Figure 7: Network lifetime evaluation
5. Conclusion and Future Scope
The review has shown that the HEER does not use the inter cluster data aggregation, but it is not deterministic in nature, as
cluster head selection is based upon the weighted probabilities. So to overcome this problem a deterministic approach has
been proposed to enhance the cluster head selection. The comparative analysis has shown that the proposed HEER
outperforms over the HEER protocol with respect to the stable period and the network lifetime. In near future the work can
be further extended by using the data aggregation techniques which would provide more significant improvement over
energy consumption, stability period and network lifetime.
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