Energy-Aware Routing Protocols for Wireless Sensor Network Based on Fuzzy Logic: A 10-Years Analytical Review

Wireless sensor networks (WSNs) have limited storage capacity, communication bandwidth, processing speed, and battery issues. All these factors affect the lifespan of a WSN. Solving all these issues and increasing the lifespan of the WSN. Energy optimization in WSNs is a demanding issue that drives a huge effort in research and various standardization procedures have been undertaken in this area for the past several years. To deal with the reduction of energy consumption issues in WSNs, various clustering protocols have evolved. In this context, some protocols select an appropriate node as the cluster head to extend the lifespan of the network and also clustering reviewed techniques. In this paper, different fuzzy-based clustering methods are discussed which is helpful in designing novel energy-efficient fuzzy-based routing protocols for WSN. The main purpose of this article is to review different types of routing protocols with their advantages and limitations. In addition, various protocols have been compared graphically with their lifetimes. Various tables are depicted which are helpful for extended studies, graphical comparison between the latest clustering techniques shows the most suitable clustering technique for improving network lifetime.


Introduction
WSN gathered the information from the environment and maintain it for long period.WSN contains the sensor nodes, which can sense, collect, and compute data from surrounding.These SN uses a huge battery power supply, large memory, and powerful processor.So, now this becomes the issue for researches that how to efficiently use the energy of SN.WSN can be categorized into two parts i.e. homogeneous and heterogeneous.In homogeneous n/w the characteristics of all SN are the same but it is not with the heterogeneous network.Sensor nodes are deployed in a large area and communicate with each other via wireless technology.These sensor nodes are small [1], [2], having less memory, limited bandwidth operates on battery, limited speed, and low cost.Due to the restricted resources that each sensor node has, the optimization of energy utilization is a big issue in the field of WSNs.So our research work is mainly centralized to energy-aware MAC protocol, power awareness on system-level, radio communication, and duty cycle issue.There are various challenges facing in developing the routes for data transmission at the network layer.Some of the challenges include are lack of global addressing, not an implementation of traditionally IP based routing, and redundancy of sensed data.By keeping these all challenges in mind, various routing protocols have been proposed.It includes data-centric, location-based protocol; QoS based protocol, and hierarchical protocol.Data-centric is a query-based protocol and it helps in query data and for data redundancy.The location-based protocol transmits the data from source to sink node based on location.Hierarchical protocol collects the data from non-clusterto-cluster nodes and forms cluster.QoS protocol transmits only those data to Sink, which satisfy some of the QoS criteria.Now a days, fuzzy logic based application used in WSNs [3][4] and many more.Various fuzzy logic based system have came out [5][6] [7][8] [9][10] [11][12] [13][14] [15] .In a fuzzy logicbased system, the sensor nodes are position arbitrarily in a real-time environment.The fuzzy logic method takes input as the distance of a node to sink and the node's residual energy and gives the output as the probability of becoming CH.This method gives better result than LEACH.Gupta [14] gave earlier used fuzzy theory.In order to increase lifespan, local information of the node must be known that include distance of node to sink node, the node's energy level as well as local density .Max-min colony optimization [10] [16], [17] are used for balance energy consumption among CHs .To select suitable CHs in real time to reduce energy consumption, Cluster Head Election Mechanism using Fuzzy Logic (CHEF) was came as depict in figure 1.Energy aware distributed clustering protocol which uses fuzzy logic(ECPE) is also developed to diminish energy utilization by sensor nodes [10] [18] along with this ACO(UCFIA) and IFUC were suggested by Mao [5].

Figure 1. Data Routing via Cluster head
In this literature survey show that last 10 year publication report based on energy aware routing protocol for WSN in Figure 2 and also depict sequential distribution of the papers.

Evaluation Matrices for WSN System
In a WSN, there are various parameters used to estimate the throughput of the network.Numerous parameters are as follows.

Network strength
Power consumption by a sensor node in a network is the main issue.To enlarge the lifetime of a WSN network, to manage the energy utilization in a network, the network should be designed such that the sensor node consumes the least energy and transfers more data.The sensor node is either identical or odd.

Scalability
Scalability is the property of a wireless system to handle the performance of a network by adding resources (sensor node) to the wireless network system.Suppose new nodes are added to the network, and then there will be no effect on any output of the network.

Temporal accuracy
The sensor nodes of WSN send the sensed information from time to time to the end-user to take a decision for betterment.Every operation performs within a specific period of time.

Coverage
Coverage in a wireless sensor network means to sense over the target region.This is a primary factor for ensuring the eminence of examination provided by the WSNs or in another way we can say that all sensor nodes are dispersed in the whole region to be observed.

Response time
Any type of wireless sensor network-based application, an application that has a good response time for fire detection scenario response time should be fast with respect to the sensor node.If the sensor node is in an active mode they provide the information quickly when a fire is found.

Security
Security is an important factor in wireless sensor networks.Threats do not allow entering the application and disturbed the application processes a sensor node deployed in a remote or hostile environment and perform their task in an unattended manner.WSN application Energy-Aware Routing Protocols for Wireless Sensor Network Based on Fuzzy Logic: A 10-Years Analytical Review 3 prevents the attack from outside and secures the privacy of collected data.

Clustering and CHs Election
Clustering is one of the energy maximize technique used to increase network lifespan in WSN.These include grouping device nodes for clusters and choosing CHs for all clusters.
Cluster heads collect the information that is sent by the sensor node, and then the cloister head chooses the shortest route to pass the collected information to the sink.
Clustering and choosing a cluster head are both very important approaches that can be used to increase the lifetime of the WSN.

Cluster Component
There are various important cluster components are listed as follows: • Cluster member

Cluster Head
CH plays a significant role to broadcast the message to the sink and they also do data fusion and data aggregation.Apart from CH, all node acts as a non-CH or cluster member.The main challenge in WSNs is to elect the cluster heads on the basis of some input parameter some common parameter used to elect the CHs are as follows: • Remaining energy • Number of neighbors nodes • Farness from sink to nodes

Clustering Objectives
In the cluster technique, there are some objective cluster listed as follows [20]: • Aggregations allow

Classification of Cluster Based Protocol
There are various parameter used in different types protocol.LEACH protocol is one of them and there are numerous variant of LEACH protocol shown in the table.Figure 4 shows that the over view of modified LEACH based protocols according to the classification they are depict here only because of all these technique use to decrease the complexity of the network.

• Election of CH
The selection of CH in any clustering algorithm is a significant task to conserve the energy of SN and to extend the lifetime of WSN. Figure 5 shows the observations for choosing CH based on the criteria given below.merit and limitation discuss in Section III, Fuzzy based clustering protocol are given in Section IV, comparison of the various novel fuzzy-based protocol with their lifetime discuss in Section V and in Section VI describe the conclusion and future direction of this review paper.

Fuzzy Logic
The problem of uncertainty handles by fuzzy logic.Uncertainty arises when cluster are formed and on the basis of variable when select cluster head.Fuzzy play a very important role to select the cluster head [14] in WSNs [21] .Fuzzy input working with predefines set of rule.It maps input space into output space.The membership function of a fuzzy logic requires expert knowledge and creates a set of rules to draw a conclusion from the given data.The membership function may give different values for the same set of rules of the fuzzy logic system.System design requires initial knowledge to select a membership function.Figure 6 indicates that the working version of a fuzzy logic device wherein enter facts is fuzzified into some of the fuzzy sets and then in line with the predefined set of rule inference drawn from the input fuzzy units.Defuzzifier converts the fuzzy sets into a crisp value for the CH selection chance calculated by the output of the crisp value of FIS.In WSN, fuzzy logic systems are used to deal with many issues such as decision-making uncertainty, routing, and network security.

Literature Review
In this segment, a literature review is presented in the form of table1 and various fuzzy based clustering protocol and methods are briefly reviewed.ii) New selection parameters criteria enhance the performance of WSN.
i) CHs are selected randomly.
ii) Hot spots problem.
Novel approach for CH election [14] Novel approach (Gupta et al., 2005) is one of the methods for CH election.The algorithm basically consists of two phases.In the first phase, the sink calculates the chance value which includes concentration, energy and centrality of each of the sensor node along with some other information in order to choose the CH candidate.In the second stage, each of the CH conspired about the time schedule and grouping of data.The algorithm and flowchart are given in the below figure 3 & 4.This stage of the algorithm performs recursively and thus uniformly distributes the load in the network.This algorithm also helps in enhancing the lifetime of the network.But along with these all benefits, the algorithm has the following disadvantages, Sink periodically collects information which increases the pressure on the sink, not any look over the CH failure, more energy required, used for small scale network and at last only one cluster head selected using this approach.

CHEATS [44] protocol
It is also called a Takagi-Sugeno fuzzy system for CH selection, described in

CHEF[45] protocol
Like LEACH protocol, it also formed the cluster in every round & using the energy and local farness as the variables it uses the fuzzy output in order to select the CH. Figure 6 represents the flowchart & figure 5  FBECS [46] protocol FBECS for wireless sensor network uses the fuzzy interference system that uses the residue energy, density of a node to its neighbor's node and distance of node to sink and then calculate the 'Eligibility Index' in order to select the suitable cluster head among all the sensor node.It proves to be better than LEACH & BCSA protocol.It provides the load balancing, extended lifetime of network and also delivered wide-ranging information to the sink.

FLEACH[47] protocol
The formation of cluster in WSN should always be performed in such a way that it should lower energy utilization.Various methods are evolved to reduce energy consumption during formation of cluster, but they all proved to be expensive.This paper describes the FLEEC protocol with two phases and made for optimizing energy utilization.
In the first stage of this algorithm, the sink node uses the following two fuzzy inputs as Node-density & distance to sink in order to find the communication radius for all the sensor nodes.The second stage uses the residual energy and total distance obtained in the first level in order to determine the chances of being CH.Experimentally proved that this protocol is better than LEACH & EFCH in term of utilizing the energy carefully.

CHUFL[40] protocol
The CH selection protocol CHUFL is one of another algorithm for cluster head selection.The CH selection using

SCHFTL[48] protocol
One of the prominent challenges in the WSN is to minimize energy consumption & this can be achieved by choosing the appropriate method for CH selection.One such algorithm is the LEACH algorithm which selects the CH on the basis of some threshold value.In the LEACH algorithm the sensor node transmits the data to their CH and CH collectively transmits the data to sink.This protocol describes another protocol called SCHFTL .This algorithm chooses the super cluster head among all the available CHs with the help of Mamdani interference engine.It is more productive than FMCHEL fuzzy based master CH election leach & CHEF protocol.

E-CAFL[49] protocol
In WSN, the sensor nodes are grouped to form a cluster & each of the sensor nodes transmits information to their CH.The CH finally transmits this information to the sink.The CH plays a vital role in this overall process, so the method of choosing the CH is most important because due to any variance in consumption of energy by the sensor node, the overall network gets failure.This paper introduces one of the algorithms that select the desirable CH called E-CAFL.This algorithm is the advanced form of CAFL algorithm.This algorithm calculates the rank of each sensor nodes using the fuzzy interference system and leftover energy, distance between node to sink & node density are the fuzzy input to the system.This algorithm is more desirable over the CAFL & LEACH algorithm in term of both the network lifetime as well as performance.

MOFCA[50] protocol
Clustering is the well-organized method in WSN.If not only gathered the information from its nearby cluster nodes but also very much efficient in terms of energy utilization.In the multi hop environment of the WSN information is transmitted from one CH to another CH until it reaches to the sink.In this method of transmission the CH which is near to the sink gets die due to sense inter cluster transmission.This situation is called the hotspot problem in WSN.This hotspot problem can be somehow solved by using the unequal clustering approach in which the cluster size reduces as it goes nearer to the sink.Along with the hotspot problem, another problem that occurs in the WSN is the energy hole problem which occurs due to variance in the position of the sensor node distribution.MOFCA protocol is used to solve the hotspot & energy hole problem.Some experiments are done using efficiency metrics like First Node Dies (FND), half of the Node Alive (HNA) and Total Remaining Energy (TRE) shows that MOFCA perform better as compared to few traditional protocols.

FUCA[51]protocol
Unequal clustering is also performed to improve the life span of the WSN.In case of the unequal clustering the sizes of clusters are getting reduces and reach closer to the sink.This fuzzy based unequal clustering algorithm also uses the unequal clustering concept which evenly distributes the consumption of energy.This algorithm uses the leftover energy, density of the nodes & farness of sensor node to its sink as the fuzzy i/p and competition radius & rank as fuzzy output.Mamdani method & the fuzzy logic concept used here for CH selection.This algorithm proved more desirable and improved version in terms of both performance and network lifetime as compared to LEACH, and another energy-aware unequal clustering fuzzy based protocol.

Comparison
In this segment, various clustering methods based on fuzzy logic are comparing.Figure .7 has shown the network lifetime enhancement of the latest cluster-based protocol.LEACH is a traditional protocol that is very useful to enhance the lifespan of the WSNs, apart from LEACH we have to consider the latest protocol which is more useful as compared to LEACH for WSNs.Basically the performance of the clustering technique based on the input parameter which is used in fuzzy logic system [52].With the help of MATLAB, numerous algorithms are implemented with initial parameter a value which is listed in table no.3 to evaluate the performance of WSNs in terms of FND, QND, and LND which is shown in figure 9 and 10 respectively.In this review when the first node dies to start, the network stability period decreases.Figure 9 and 10 shows that the FBECS protocol outperforms all the latest energy-efficient protocols, then SCHFTL, etc.The most important scenario that is used in many protocols is shown in Fig. 8.In this scenario, the Sink position is (50,50) and the sensor node is deployed randomly, some protocols having more than one sink position.Table 3 showed a common simulation factor and their values which is very useful in radio communication.conjointly diminish terribly simply if it's not properly managed.The most reasons for the consumption of energy in wireless sensing element networks square measure communication and process, with communication being the most responsible for the consumption of energy.The energy model consists of 3 main modules: receiver, transmitter, and power electronic equipment.
The receiver consumes energy to run the receiver electronic equipment at the time of reception of information, and therefore the transmitter consumes energy to run the facility electronic equipment and transmitter electronic equipment at the time of transmission of information.Energy dissipation for transmitter and receiver is signify by elec and energy dissipation for transmit amplifier is signified by amp.

Conclusion
Due to limited sources and accessibility, WSN calls for self-employing topology supervision and energy preservation strategies.Numerous strategies have been supplied to solve the energy preservation issue; however, a well-known and satisfying answer is the two-layer hierarchical structure and distributing various control functions, including energy efficiency, non-variance with multiple goals There are many sensor nodes that fail some time due to the worst routing protocols.Fuzzy logic is applied to enhance the performance of a clustering strategy, but the most important challenge is that it calls for initial expert expertise to set a rule and select appropriate membership functions.Thus the various protocols produce different outputs with the same set of rules .The basic difference between the approaches is to become a CH using different participation factors to calculate the likelihood importance of the sensor node.Choosing a progressively effective, less intricate and 13 dependable framework is a significant test since sensor systems are application-arranged where inclinations shift with organized targets to such an extent that data constancy is a higher need than higher fuzzy request frameworks, however, higher-request new difficulties utilizing the framework.But in this review paper, a lot of figures and tables have been told which have been studied from the last ten year papers and explained in detail to help researchers to create a novel approach which is helpful to create real-time applications.In the future, this review paper is very important for researchers and for various organizations, who work to design a real-time application based on the sensor node.

Figure 3 [
19] demonstrate the estimate rise in revenues from the WSN market for the period of 2010-2014.

Figure 2 .
Figure 2. Number of Wireless Sensor Network based article publications by the year.

Figure 4 .
Figure 4. Numerous techniques related to routing protocol of WSN CH selection uses different parameter as an input for the fuzzy system and produces an output to solve the uncertainty of a WSN in terms of energy.Fig. 5 shows in detail the various protocols related to CH selection and the benefit of clustering is: reduces energy utilization by maximizing bandwidth utilization, minimize overhead, maximum connectivity established, reduce delay in data transmission, load balancing, reduce the size of the routing table, and stabilized network topology.The organization of this review paper is as follows.The fuzzybased system described in Section II, literature review of energy-aware routing protocol with clustering method,

Figure 5 .
Figure 5. Multiple cluster head selection scheme and their protocol

Figure 6 .
Figure 6.Fuzzy Logic System4.Fuzzy-Based Clustering ProtocolFuzzy based algorithms help in enhancing the performance of WSN have been given here.All describe protocol is come into the existence after 2010.All are energy efficient and they are very much helpful to maximize the life span of WSN.

Figure 7 .
Figure 7. Lifetime in percentage as compared to various protocols.
If the sensor node starts communication then their life in terms of energy is reduced so for any network FND, QND, HND are important and after each round of communication check what is the node die state.It is the actual fact that the energy accessible to sensing element nodes isn't solely restricted, however it's going to Energy-Aware Routing Protocols for Wireless Sensor Network Based on Fuzzy Logic: A 10-Years Analytical Review EAI Endorsed Transactions on Energy Web 03 2021 -05 2021 | Volume 8 | Issue 33 | e1

Figure 8 .
Figure 8. Common network scenario of WSN

•
Limits data transmission • Enhanced network lifetime • Diminish network traffic • Data fusion takes place in cluster heads •

•
Improve the QoS

Table 1 .
Literature Review Energy-Aware Routing Protocols for Wireless Sensor Network Based on Fuzzy Logic: A 10-Years Analytical Review EAI Endorsed Transactions on Energy Web 03 2021 -05 2021 | Volume 8 | Issue 33 | e1 depicts the pseudo-code of the CHEF algorithm.It has a better performance than LEACH.If two sensor nodes have the same chance value to become CH then this algorithm has not the appropriate Procedure to find which one is better for CH.IF one end of the n/w has a high concentration of CH then as per cluster radius condition the number of CH is reduced and hence increases the chance of CH failure.It somehow overcomes the limitation of a novel approach for CH election.
Issue 33 | e1this algorithm is based on some attribute including a communication link between nodes, surplus energy of the nodes, farness between the neighbor sensor nodes, distance between the sensor nodes & sink.CHUFL is relaxed up to 20% in energy consumption as compared to CHEF by Kim et al. & cluster head selection method for WSN by J. Anno et al. and CHUFL also sends information from the sensor node to sink up to 72% more in contrast with J. Anno et al. protocol.

Table 3 .
Common Simulation Parameters