FLIHSBC: Fuzzy Logic and Improved Harmony Search Based Clustering Algorithm for Wireless Sensor Networks to Prolong the Network Lifetime

2017 ◽  
pp. 570-578 ◽  
Author(s):  
Deepika Agrawal ◽  
Sudhakar Pandey
Keyword(s):  
Wireless Sensor Networks ◽  
Fuzzy Logic ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Clustering Algorithm ◽  
Harmony Search ◽  
Wireless Sensor ◽  
Improved Harmony Search

scholarly journals Energy Efficient Clustering in Wireless SensorNetworks Using Fuzzy Approach to Improve LEACH Protocol

2016 ◽  
Vol 11 (2) ◽  
pp. 2641-2656
Author(s):  
Basim Abood ◽  
Aliaa Hussien ◽  
Yu Li ◽  
Desheng Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Fuzzy Logic ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Energy Efficient ◽  
Wireless Sensor ◽  
Inference System ◽  
Multiple Parameters ◽  
Leach Protocol ◽  
Energy Efficient Clustering

The most important consideration in designing protocols for wireless sensor networks is the energy constraint of nodes because in most cases battery recharging is inconvenient or impossible. Therefore, many researches have been done to overcome this demerit. Clustering is one of the main approaches in designing scalable and energy-efficient protocols for wireless sensor networks. The cluster heads take the task of data aggregation and data routing to decrease the amount of communication and this prolongs the network lifetime. LEACH protocol is one of the famous of them. In this paper, we proposed a novel scheme to investigate the cluster, the Fuzzy Logic Cluster Leach Protocol (FUZZY-LEACH), which uses Fuzzy Logic Inference System (FIS) in the cluster process. We demonstrate that using multiple parameters in cluster reduces energy consumption. We compare our technique with the LEACH protocol to show that using a multi parameter FIS enhances the network lifetime significantly. Simulation results demonstrate that the network lifetime achieved by the proposed method could be increased by nearly 28.5% more than that obtained by LEACH protocol in  scenario, and by nearly 26.4% more than that LEACH protocol in  scenario.

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.

Genetic optimization of hybrid clustering algorithm in mobile wireless sensor networks

Sensor Review ◽  
2018 ◽  
Vol 38 (4) ◽  
pp. 526-533 ◽  
Author(s):  
Sangeetha M. ◽  
Sabari A.
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Clustering Algorithm ◽  
Wireless Sensor ◽  
Mobile Wireless ◽  
Content Type ◽  
Mobile Wireless Sensor

Purpose This paper aims to provide a prolonging network lifetime and optimizing energy consumption in mobile wireless sensor networks (MWSNs). MWSNs have characteristics of dynamic topology due to the factors such as energy consumption and node movement that lead to create a problem in lifetime of the sensor network. Node clustering in wireless sensor networks (WSNs) helps in extending the network life time by reducing the nodes’ communication energy and balancing their remaining energy. It is necessary to have an effective clustering algorithm for adapting the topology changes and improve the network lifetime. Design/methodology/approach This work consists of two centralized dynamic genetic algorithm-constructed algorithms for achieving the objective in MWSNs. The first algorithm is based on improved Unequal Clustering-Genetic Algorithm, and the second algorithm is Hybrid K-means Clustering-Genetic Algorithm. Findings Simulation results show that improved genetic centralized clustering algorithm helps to find the good cluster configuration and number of cluster heads to limit the node energy consumption and enhance network lifetime. Research limitations/implications In this work, each node transmits and receives packets at the same energy level throughout the solution. The proposed approach was implemented in centralized clustering only. Practical implications The main reason for the research efforts and rapid development of MWSNs occupies a broad range of circumstances in military operations. Social implications The research highly gains impacts toward mobile-based applications. Originality/value A new fitness function is proposed to improve the network lifetime, energy consumption and packet transmissions of MWSNs.

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