A Novel Energy-Aware Clustering Method via Lion Pride Optimizer Algorithm (LPO) and Fuzzy Logic in Wireless Sensor Networks (WSNs)

2019 ◽  
Vol 108 (3) ◽  
pp. 1803-1825 ◽  
Author(s):  
Shayesteh Tabatabaei ◽  
Amir Rajaei ◽  
Amir Mohsen Rigi
Keyword(s):  
Wireless Sensor Networks ◽  
Fuzzy Logic ◽  
Sensor Networks ◽  
Wireless Sensor ◽  
Clustering Method ◽  
Energy Aware

scholarly journals Congestion Control and Prediction Schemes Using Fuzzy Logic System with Adaptive Membership Function in Wireless Sensor Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-19 ◽  
Author(s):  
Phet Aimtongkham ◽  
Tri Gia Nguyen ◽  
Chakchai So-In
Keyword(s):  
Wireless Sensor Networks ◽  
Fuzzy Logic ◽  
Sensor Networks ◽  
Packet Loss ◽  
Superior Performance ◽  
Wireless Sensor ◽  
Volume Data ◽  
Energy Aware ◽  
Fuzzy Logic Systems ◽  
Hop Count

Network congestion is a key challenge in resource-constrained networks, particularly those with limited bandwidth to accommodate high-volume data transmission, which causes unfavorable quality of service, including effects such as packet loss and low throughput. This challenge is crucial in wireless sensor networks (WSNs) with restrictions and constraints, including limited computing power, memory, and transmission due to self-contained batteries, which limit sensor node lifetime. Determining a path to avoid congested routes can prolong the network. Thus, we present a path determination architecture for WSNs that takes congestion into account. The architecture is divided into 3 stages, excluding the final criteria for path determination: (1) initial path construction in a top-down hierarchical structure, (2) path derivation with energy-aware assisted routing, and (3) congestion prediction using exponential smoothing. With several factors, such as hop count, remaining energy, buffer occupancy, and forwarding rate, we apply fuzzy logic systems to determine proper weights among those factors in addition to optimizing the weight over the membership functions using a bat algorithm. The simulation results indicate the superior performance of the proposed method in terms of high throughput, low packet loss, balancing the overall energy consumption, and prolonging the network lifetime compared to state-of-the-art protocols.

An energy-aware distributed clustering protocol in wireless sensor networks using fuzzy logic

2012 ◽  
Vol 10 (7) ◽  
pp. 1469-1481 ◽  
Author(s):  
Hoda Taheri ◽  
Peyman Neamatollahi ◽  
Ossama Mohamed Younis ◽  
Shahrzad Naghibzadeh ◽  
Mohammad Hossein Yaghmaee
Keyword(s):  
Wireless Sensor Networks ◽  
Fuzzy Logic ◽  
Sensor Networks ◽  
Wireless Sensor ◽  
Distributed Clustering ◽  
Energy Aware ◽  
Clustering Protocol

scholarly journals Fuzzy Logic Based Zone Head Selection Algorithm for Wireless Sensor Networks

2021 ◽  
Vol 23 (07) ◽  
pp. 1210-1215
Author(s):  
Anchal Garg ◽  
◽  
Gurjinder Kaur ◽  
Keyword(s):  
Wireless Sensor Networks ◽  
Fuzzy Logic ◽  
Sensor Networks ◽  
Sensor Network ◽  
Hot Spots ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Unequal Clustering ◽  
Energy Aware ◽  
Efficient Data

Hot-spots are a problem that comes in the cluster-based routing protocol that employs multi-hop communication due to this problem the energy among the sensor nodes is not balanced. The hot-spots issue requires high overhead and is prone to connectivity issues in the sensor network this can be only possible because of unequal clustering. In this method, we have to act on all the nodes of the sensor network for communication. This process consumes high system energy if the numbers of nodes are very high. To offer guaranteed connectivity, decrease high usage and complexity, a fuzzy logic-based zone divisional method has been proposed in this paper. Use fuzzy logic to create clusters and assign nodes to them to decrease the consumption of energy and the age of the network prolongation. The simulation and results section shows the outperformance of the proposed protocol, where the (LEACH) low-energy adaptive clustering hierarchy, (EAUCF) energy-aware unequal clustering fuzzy,(EAMMH) energy-aware multi-hop multi-path hierarchical, and (TTDFP) two-tier distributed fuzzy logic-based protocol for efficient data aggregation in multi-hop wireless sensor networks algorithms. The proposed algorithm has better results in terms of energy consumption minimization, and prolongation of the network lifetime.

scholarly journals The Main Cluster Node Formation in Wireless Sensory Networks

2020 ◽  
pp. 34-41
Author(s):  
Olexander Belej
Keyword(s):  
Wireless Sensor Networks ◽  
Fuzzy Logic ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Residual Energy ◽  
Wireless Sensor ◽  
Clustering Method ◽  
Main Cluster ◽  
Input Parameters ◽  
Node Formation

In wireless sensor networks, the clustering method is often used to transmit information, which is one of the most energy efficient approaches. Since the master cluster node interacts with other nodes in the network, a node with a high residual energy is selected to perform its functions. The technology of selecting the main node based on fuzzy logic, which involves the use of a number of input parameters, the effect of which is demonstrated in the article, is proposed.

scholarly journals Zone Head Selection Algorithm Based on Fuzzy Logic for Wireless Sensor Networks

2021 ◽  
Vol 23 (10) ◽  
pp. 29-37
Author(s):  
Anchal Garg ◽  
◽  
Gurjinder Kaur ◽  
Keyword(s):  
Wireless Sensor Networks ◽  
Fuzzy Logic ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Sensor Network ◽  
Wireless Sensor ◽  
Network Clustering ◽  
Unequal Clustering ◽  
Energy Aware ◽  
Reduction Of Energy Consumption

Clustering extends energy resources, improves scalability and preserves communication bandwidth of the network. Clustering is either categorized as static and dynamic or as equal and unequal. Hot-spots issue needs a high overhead and is prone to connectivity problems in the wireless sensor network and this can be only possible because of unequal clustering. In this paper a zone divisional method based on fuzzy logic has been proposed. This method uses a fuzzy logic to form clusters and allot nodes to them for the reduction of energy consumption, and extends the age of the sensor network. The simulation and results section shows that the outperformance of the proposed algorithm, where the (EAUCF) energy-aware unequal clustering fuzzy, (LEACH) lowenergy adaptive clustering hierarchy, (EAMMH) energy-aware multi-hop multi-path hierarchical, and (TTDFP) two-tier distributed fuzzy logic-based protocol for efficient data aggregation in multi-hop wireless sensor networks algorithms. The proposed algorithm has better results in terms of energy consumption minimization, load balancing, and prolongation of the network lifetime.

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