Fuzzy Logic-Based Cluster Heads Percentage Calculation for Improving the Performance of the LEACH Protocol

Fuzzy Systems ◽  
2017 ◽  
pp. 609-627 ◽  
Author(s):  
Omar Banimelhem ◽  
Eyad Taqieddin ◽  
Moad Y. Mowafi ◽  
Fahed Awad ◽  
Feda' Al-Ma'aqbeh
Keyword(s):  
Fuzzy Logic ◽  
Network Lifetime ◽  
Sensor Node ◽  
Base Station ◽  
Sensor Nodes ◽  
Number Of Clusters ◽  
Network Characteristics ◽  
Clustering Protocol ◽  
Proper Number ◽  
Leach Protocol

In wireless sensor networks, cluster-based routing was proven to be the most energy-efficient strategy to deal with the scaling problem. In addition, selecting the proper number of clusters is a critical decision that can impose a significant impact on the energy consumption and the network lifetime. This paper presents FL-LEACH, a variant of the well-known LEACH clustering protocol, which attempts to relax the stringent strategy of determining the number of clusters used by LEACH via fuzzy logic decision-making scheme. This relates the number of clusters to a number of network characteristics such as the number of sensor nodes, the area of the sensing field, and the location of the base station. The performance of FL-LEACH was evaluated via simulation and was compared against LEACH using standard metrics such as network lifetime and remaining network energy. The results depicted that the proposed approach has the potential to substantially conserve the sensor node energy and extend lifetime of the network.

Fuzzy Logic-Based Cluster Heads Percentage Calculation for Improving the Performance of the LEACH Protocol

2015 ◽  
Vol 4 (4) ◽  
pp. 100-118 ◽  
Author(s):  
Omar Banimelhem ◽  
Eyad Taqieddin ◽  
Moad Y. Mowafi ◽  
Fahed Awad ◽  
Feda' Al-Ma'aqbeh
Keyword(s):  
Fuzzy Logic ◽  
Network Lifetime ◽  
Energy Efficient ◽  
Base Station ◽  
Sensor Nodes ◽  
Number Of Clusters ◽  
Network Characteristics ◽  
Clustering Protocol ◽  
Proper Number ◽  
Leach Protocol

In wireless sensor networks, cluster-based routing was proven to be the most energy-efficient strategy to deal with the scaling problem. In addition, selecting the proper number of clusters is a critical decision that can impose a significant impact on the energy consumption and the network lifetime. This paper presents FL-LEACH, a variant of the well-known LEACH clustering protocol, which attempts to relax the stringent strategy of determining the number of clusters used by LEACH via fuzzy logic decision-making scheme. This relates the number of clusters to a number of network characteristics such as the number of sensor nodes, the area of the sensing field, and the location of the base station. The performance of FL-LEACH was evaluated via simulation and was compared against LEACH using standard metrics such as network lifetime and remaining network energy. The results depicted that the proposed approach has the potential to substantially conserve the sensor node energy and extend lifetime of the network.

scholarly journals Optimization of Energy Efficient Advance Leach Protocol

2021 ◽  
Vol 9 (5) ◽  
pp. 07-16
Author(s):  
Sandeep Kaur ◽  
Dr. Rajeev Bedi ◽  
Mohit Marwaha
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Conservation ◽  
Network Lifetime ◽  
Energy Efficient ◽  
Sensor Node ◽  
Cluster Head ◽  
Base Station ◽  
Wireless Sensor ◽  
Cluster Head Selection ◽  
Leach Protocol

In WSNs, the only source to save life for the node is the battery consumption. During communication with other area nodes or sensing activities consumes a lot of power energy in processing the data and transmitting the collected/selected data to the sink. In wireless sensor networks, energy conservation is directly to the network lifetime and energy plays an important role in the cluster head selection. A new threshold has been formulated for cluster head selection, which is based on remaining energy of the sensor node and the distance from the base station. Proposed approach selects the cluster head nearer to base station having maximum remaining energy than any other sensor node in multi-hop communication. The multi hop approach minimizing the inter cluster communication without effecting the data reliability.

scholarly journals An Energy-Aware Method for Selecting Cluster Heads in Wireless Sensor Networks

2020 ◽  
Vol 10 (21) ◽  
pp. 7886
Author(s):  
Atefeh Rahiminasab ◽  
Peyman Tirandazi ◽  
M. J. Ebadi ◽  
Ali Ahmadian ◽  
Mehdi Salimi
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Cluster Head ◽  
Base Station ◽  
Energy Resources ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Dynamic Clustering ◽  
Clustering Protocol

Wireless sensor networks (WSNs) include several sensor nodes that have limited capabilities. The most critical restriction in WSNs is energy resources. Moreover, since each sensor node’s energy resources cannot be recharged or replaced, it is inevitable to propose various methods for managing the energy resources. Furthermore, this procedure increases the network lifetime. In wireless sensor networks, the cluster head has a significant impact on system global scalability, energy efficiency, and lifetime. Furthermore, the cluster head is most important in combining, aggregating, and transferring data that are received from other cluster nodes. One of the substantial challenges in a cluster-based network is to choose a suitable cluster head. In this paper, to select an appropriate cluster head, we first model this problem by using multi-factor decision-making according to the four factors, including energy, mobility, distance to centre, and the length of data queues. Then, we use the Cluster Splitting Process (CSP) algorithm and the Analytical Hierarchy Process (AHP) method in order to provide a new method to solve this problem. These four factors are examined in our proposed approach, and our method is compared with the Base station Controlled Dynamic Clustering Protocol (BCDCP) algorithm. The simulation results show the proposed method in improving the network lifetime has better performance than the base station controlled dynamic clustering protocol algorithm. In our proposed method, the energy reduction is almost 5% more than the BCDCP method, and the packet loss rate in our proposed method is almost 25% lower than in the BCDCP method.

scholarly journals An Area Coverage Scheme Based on Fuzzy Logic and Shuffled Frog-Leaping Algorithm (SFLA) in Heterogeneous Wireless Sensor Networks

Mathematics ◽  
2021 ◽  
Vol 9 (18) ◽  
pp. 2251
Author(s):  
Amir Masoud Rahmani ◽  
Saqib Ali ◽  
Mohammad Sadegh Yousefpoor ◽  
Efat Yousefpoor ◽  
Rizwan Ali Naqvi ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Fuzzy Logic ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Sensor Node ◽  
Area Coverage ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Shuffled Frog Leaping Algorithm ◽  
Shuffled Frog Leaping

Coverage is a fundamental issue in wireless sensor networks (WSNs). It plays a important role in network efficiency and performance. When sensor nodes are randomly scattered in the network environment, an ON/OFF scheduling mechanism can be designed for these nodes to ensure network coverage and increase the network lifetime. In this paper, we propose an appropriate and optimal area coverage method. The proposed area coverage scheme includes four phases: (1) Calculating the overlap between the sensing ranges of sensor nodes in the network. In this phase, we present a novel, distributed, and efficient method based on the digital matrix so that each sensor node can estimate the overlap between its sensing range and other neighboring nodes. (2) Designing a fuzzy scheduling mechanism. In this phase, an ON/OFF scheduling mechanism is designed using fuzzy logic. In this fuzzy system, if a sensor node has a high energy level, a low distance to the base station, and a low overlap between its sensing range and other neighboring nodes, then this node will be in the ON state for more time. (3) Predicting the node replacement time. In this phase, we seek to provide a suitable method to estimate the death time of sensor nodes and prevent possible holes in the network, and thus the data transmission process is not disturbed. (4) Reconstructing and covering the holes created in the network. In this phase, the goal is to find the best replacement strategy of mobile nodes to maximize the coverage rate and minimize the number of mobile sensor nodes used for covering the hole. For this purpose, we apply the shuffled frog-leaping algorithm (SFLA) and propose an appropriate multi-objective fitness function. To evaluate the performance of the proposed scheme, we simulate it using NS2 simulator and compare our scheme with three methods, including CCM-RL, CCA, and PCLA. The simulation results show that our proposed scheme outperformed the other methods in terms of the average number of active sensor nodes, coverage rate, energy consumption, and network lifetime.

scholarly journals Development of Energy Efficient Clustering Protocol in Wireless Sensor Network Using Neuro-Fuzzy Approach

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
E. Golden Julie ◽  
S. Tamil Selvi
Keyword(s):  
Neural Network ◽  
Fuzzy Logic ◽  
Energy Consumption ◽  
Network Lifetime ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Aware ◽  
Cluster Heads ◽  
Clustering Protocol ◽  
Neuro Fuzzy

Wireless sensor networks (WSNs) consist of sensor nodes with limited processing capability and limited nonrechargeable battery power. Energy consumption in WSN is a significant issue in networks for improving network lifetime. It is essential to develop an energy aware clustering protocol in WSN to reduce energy consumption for increasing network lifetime. In this paper, a neuro-fuzzy energy aware clustering scheme (NFEACS) is proposed to form optimum and energy aware clusters. NFEACS consists of two parts: fuzzy subsystem and neural network system that achieved energy efficiency in forming clusters and cluster heads in WSN. NFEACS used neural network that provides effective training set related to energy and received signal strength of all nodes to estimate the expected energy for tentative cluster heads. Sensor nodes with higher energy are trained with center location of base station to select energy aware cluster heads. Fuzzy rule is used in fuzzy logic part that inputs to form clusters. NFEACS is designed for WSN handling mobility of node. The proposed scheme NFEACS is compared with related clustering schemes, cluster-head election mechanism using fuzzy logic, and energy aware fuzzy unequal clustering. The experiment results show that NFEACS performs better than the other related schemes.

scholarly journals LOCATION AWARE CLUSTER BASED ROUTING IN WIRELESS SENSOR NETWORKS

2015 ◽  
pp. 36-41
Author(s):  
S. JERUSHA ◽  
K. KULOTHUNGAN ◽  
A Kannan
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Network ◽  
Network Lifetime ◽  
Minimum Distance ◽  
Sensor Node ◽  
Cluster Head ◽  
Residual Energy ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor

Wireless sensor nodes are usually embedded in the physical environment and report sensed data to a central base station. Clustering is one of the most challenging issues in wireless sensor networks. This paper proposes a new cluster scheme for wireless sensor network by modified the K means clustering algorithm. Sensor nodes are deployed in a harsh environment and randomly scattered in the region of interest and are deployed in a flat architecture. The transmission of packet will reduce the network lifetime. Thus, clustering scheme is required to avoid network traffic and increase overall network lifetime. In order to cluster the sensor nodes that are deployed in the sensor network, the location information of each sensor node should be known. By knowing the location of the each sensor node in the wireless sensor network, clustering is formed based on the highest residual energy and minimum distance from the base station. Among the group of nodes, one node is elected as a cluster head using centroid method. The minimum distance between the cluster node’s and the centroid point is elected as a cluster head. Clustering of nodes can minimize the residual energy and maximize the network performance. This improves the overall network lifetime and reduces network traffic.

scholarly journals E-FLEACH: An Improved Fuzzy Based Clustering Protocol for Wireless Sensor Network

2021 ◽  
Vol 17 (2) ◽  
pp. 190-197
Author(s):  
Enaam Al-Husain ◽  
Ghaida Al-Suhail
Keyword(s):  
Network Lifetime ◽  
Fuzzy Logic Controller ◽  
Cluster Head ◽  
Residual Energy ◽  
Base Station ◽  
Optimal Number ◽  
Wireless Sensor ◽  
Clustering Protocol ◽  
Leach Protocol ◽  
Selection Of

Clustering is one of the most energy-efficient techniques for extending the lifetime of wireless sensor networks (WSNs). In a clustered WSN, each sensor node transmits the data acquired from the sensing field to the leader node (cluster head). The cluster head (CH) is in charge of aggregating and routing the collected data to the Base station (BS) of the deployed network. Thereby, the selection of the optimum CH is still a crucial issue to reduce the consumed energy in each node and extend the network lifetime. To determine the optimal number of CHs, this paper proposes an Enhanced Fuzzy-based LEACH (E-FLEACH) protocol based on the Fuzzy Logic Controller (FLC). The FLC system relies on three inputs: the residual energy of each node, the distance of each node from the base station (sink node), as well as the node’s centrality. The proposed protocol is implemented using the Castalia simulator in conjunction with OMNET++, and simulation results indicate that the proposed protocol outperforms the traditional LEACH protocol in terms of network lifetime, energy consumption, and stability.

scholarly journals An Efficent Coverage and Maximization of Network Lifetime in WSN Through Metaheuristics

2021 ◽  
Vol 10 (3) ◽  
pp. 159
Author(s):  
A. Nageswar Rao ◽  
B. Rajendra Naik ◽  
L. Nirmala Devi
Keyword(s):  
Network Lifetime ◽  
Sensor Node ◽  
Relay Node ◽  
Base Station ◽  
Optimal Number ◽  
Sensor Nodes ◽  
Relay Node Placement ◽  
Data Forwarding ◽  
Relay Nodes ◽  
Node Placement

<span>In wireless sensor networks (WSNs), energy, connectivity, and coverage are the three most important constraints for guaranteed data forwarding from every sensor node to the base station. Due to continuous sensing and transmission tasks, the sensor nodes deplete more quickly and hence they seek the help of data forwarding nodes, called relay nodes. However, for a given set of sensor nodes, finding optimal locations to place relay nodes is a very challenging problem. Moreover, from the earlier studies, the relay node placement is defined as a non-deterministic polynomial tree hard (NP-Hard) problem. To solve this problem, we propose a multi-objective firefly algorithm-based relay node placement (MOFF-RNP) to deploy an optimal number of relay nodes while considering connectivity, coverage, and energy constraints. To achieve network lifetime, this work adopted energy harvesting capabilities to the sensor nodes and backup relay strategy such that every sensor node is always connected to at least one relay to forward the data. The optimal relay placement is formulated as an objective function and MOFF is applied to achieve a better solution. Extensive Simulations are carried out over the proposed model to validate the performance and the obtained results are compared with state-of-art methods)</span>

scholarly journals Mobile Sink in Fuzzy Logic and Meta-heuristic Firefly Algorithm based Routing Scheme to Extend Network Lifetime of WSN (MSFLMFLA)

2021 ◽  
Author(s):  
Pranali Rajendea Navghare ◽  
Sudhakar Pandey ◽  
Deepika Agrawal
Keyword(s):  
Fuzzy Logic ◽  
Network Lifetime ◽  
Firefly Algorithm ◽  
Mobile Sink ◽  
Residual Energy ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Network Clustering ◽  
Routing Scheme

Abstract Nowadays, wireless sensor network (WSN) improves people's lives by assisting them with a variety of applications. The major challenge in WSN is consumption of power as well as lifetime of the network. Clustering is the important method for saving energy in WSN because the separation of the sender and the receiver is related to transmission energy. In this paper we used fuzzy rules for clustering. Wireless sensor networks are susceptible to energy holes, in which sensors nearer to a static sink rapidly lose energy. To solve this problem and extend network life we used a mobile sink (MS). In this paper, a customized mobile sink node called the mobile data sender (MDS) has been tried to introduce for collecting data from the sensors by going to visit every node and then going to send this to the base station. This paper proposes nature inspired heuristic discrete firefly algorithm to optimal way accumulate information from sensor nodes in order to decrease the path travelled by the MDS while doing the tour. So, in this paper, we consider Mobile Sink in Fuzzy Logic and Meta-heuristic Firefly Algorithm based routing scheme to extend network lifetime of WSN (MSFLMFLA). Here we compare throughput and network lifetime with the static sink in FLMFLA and EHR-DC and LEACH protocol. The results of simulation shows that the MSFLMFLA increases the throughput, residual energy and also increases the data received by the sink.

scholarly journals Energy-Balanced Cluster-Routing Protocol Based on Particle Swarm Optimization with Five Mutation Operators for Wireless Sensor Networks

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7217
Author(s):  
Yamin Han ◽  
Heejung Byun ◽  
Liangliang Zhang
Keyword(s):  
Particle Swarm Optimization ◽  
Network Lifetime ◽  
Routing Protocol ◽  
Sensor Node ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Swarm Optimization ◽  
Number Of Clusters ◽  
Mutation Operators ◽  
Node Clustering

Prolonging the network lifetime is one of the fundamental requirements in wireless sensor networks (WSNs). Sensor node clustering is a very popular energy conservation strategy in WSNs, allowing to achieve energy efficiency, low latency, and scalability. According to this strategy, sensor nodes are grouped into several clusters, and one sensor node in each cluster is assigned to be a cluster head (CH). The responsibility of each CH is to aggregate data from the other sensor nodes within its cluster and send these data to the sink. However, the distribution of sensor nodes in the sensing region is often non-uniform, which may lead to an unbalanced number of sensor nodes between clusters and thus unbalanced energy consumption between CHs. This, in turn, may result in a reduced network lifetime. Furthermore, a different number of clusters lead to a different quality of service of a WSN system. To address the problems of unbalanced number of sensor nodes between clusters and selecting an optimal number of clusters, this study proposes an energy-balanced cluster-routing protocol (EBCRP) based on particle swarm optimization (PSO) with five mutation operators for WSNs. The five mutation operators are specially proposed to improve the performance of PSO in optimizing sensor node clustering. A rotation CH selection scheme based on the highest residual energy is used to dynamically select a CH for each cluster in each round. Simulation results show that the proposed EBCRP method performs well in balancing energy consumption and prolonging the network lifetime.

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