Article
Computer Science, Information Systems
Kale Navnath Dattatraya, K. Raghava Rao
Summary: This paper discusses the importance of optimal cluster head selection in wireless sensor networks, proposes a new Fitness based Glowworm swarm with Fruitfly Algorithm (FGF), and compares it with other traditional methods, demonstrating the superiority of the algorithm.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Computer Science, Information Systems
Nikumani Choudhury, Rakesh Matam, Mithun Mukherjee, Jaime Lloret, Ezhil Kalaimannan
Summary: The IEEE 802.15.4 standard specifies two network topologies: 1) star and 2) cluster tree. The role of a cluster head (CH) is to aggregate data from all devices in the cluster and then transmit it to the overall personal area network (PAN) coordinator. In order to prolong network lifetime, a rotation scheme is proposed to address the limitations of existing approaches, showing improvements in network performance.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Duraimurugan Samiayya, S. Radhika, A. Chandrasekar
Summary: This paper proposes a novel 'Hybrid Snake Whale Optimization (HSWO) Algorithm' to select optimal cluster heads in order to improve the network's lifetime and energy utilization.
PEER-TO-PEER NETWORKING AND APPLICATIONS
(2023)
Article
Telecommunications
Akhilesh Panchal, Rajat Kumar Singh
Summary: The article proposes an energy-efficient technique for wireless sensor networks that optimizes network energy consumption, extends network lifetime and coverage by selecting the optimal number of cluster heads and grid heads.
TELECOMMUNICATION SYSTEMS
(2021)
Article
Computer Science, Information Systems
Haider Ali, Umair Ullah Tariq, Mubashir Hussain, Liu Lu, John Panneerselvam, Xiaojun Zhai
Summary: Wireless sensor networks play a vital role in surveillance, healthcare, and industrial automation, with a prime concern being the enhancement of energy efficiency. Clustering is widely adopted to increase network lifetime and reduce energy consumption. The proposed ARSH-FATI-CHS algorithm dynamically switches between exploration and exploitation during runtime, significantly improving network lifetime by approximately 25% compared to state-of-the-art PSO.
IEEE SYSTEMS JOURNAL
(2021)
Article
Chemistry, Analytical
Marcin Lewandowski, Bartlomiej Placzek
Summary: This study introduces a new method to prolong the lifetime of wireless sensor networks by reducing data transmissions between neighboring sensor nodes, improving the accuracy of event detection. Experimental evaluation confirmed that the proposed method significantly extends the network lifetime and is more effective than current algorithms.
Article
Automation & Control Systems
Kawsar Ali, Daniel J. Rogers
Summary: Deploying energy harvesting-based wireless sensor nodes in challenging environments often means lack of control over node placement and orientation. This article introduces a smart WSN that operates independently of placement and orientation, sharing energy and information among cube faces to maximize energy harvesting and signal transmission.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2021)
Article
Chemistry, Analytical
Aiyun Zheng, Zhen Zhang, Weimin Liu, Jiaxin Liu, Yao Xiao, Chen Li
Summary: This article proposes a dual cluster head optimization method, which utilizes fuzzy c-means clustering algorithm and multi-objective particle swarm optimization to determine two cluster heads. The trajectory of the mobile sink is assessed using an improved ant colony algorithm. Comparisons with other algorithms show that this method can improve the network's lifetime and data transmission efficiency.
Article
Telecommunications
S. Muthukumar, D. Hevin Rajesh
Summary: Wireless Sensor Network (WSN) utilizes clustering to reduce internal communication cost and conserve energy. The OC algorithm is used to establish clusters and save electricity, while the improved myopia (IM) algorithm is employed to determine cluster heads and minimize the number of clusters and internal communication expenses. Additionally, a special algorithm is used for route selection to enhance energy efficiency.
WIRELESS PERSONAL COMMUNICATIONS
(2022)
Article
Computer Science, Information Systems
Anna Merine George, S. Y. Kulkarni, Ciji Pearl Kurian
Summary: The paper presents a model predictive approach for evaluating network lifetime and cluster head selection for a wireless sensor network. The study focuses on the effect of various dynamic parameters on network lifetime prediction and combines clustering with the optimal routing protocol using a machine learning approach.
Article
Computer Science, Information Systems
J. Jean Justus, M. Thirunavukkarasan, K. Dhayalini, G. Visalaxi, Adel Khelifi, Mohamed Elhoseny
Summary: Wireless Sensor Network (WSN) plays a crucial role in IoT and various techniques, such as Type II Fuzzy Logic-based Cluster Head selection with Low Complexity Data Aggregation, have been proposed to enhance energy efficiency in WSN. Experimental results show that the proposed technique outperforms compared methods in terms of energy efficiency, lifetime, Compression Ratio (CR), and power saving under different scenarios based on the position of Base Station (BS).
CMC-COMPUTERS MATERIALS & CONTINUA
(2022)
Article
Chemistry, Analytical
Rajathi Natarajan, Geetha Megharaj, Adam Marchewka, Parameshachari Bidare Divakarachari, Manoj Raghubir Hans
Summary: In this paper, an energy-efficient clustering/routing technique called the energy and distance based multi-objective red fox optimization algorithm (ED-MORFO) was proposed to reduce energy consumption in wireless sensor networks (WSNs). The simulation results clearly demonstrate that the proposed ED-MORFO achieves better performance in terms of energy consumption, packet delivery ratio, packet loss rate, end-to-end delay, routing overhead, throughput, and network lifetime, compared to existing methods MCH-EOR and RDSAOA-EECP.
Article
Telecommunications
R. Praveen Kumar, Jennifer S. Raj, S. Smys
Summary: This research proposes a hybrid optimization approach to enhance energy efficiency and network lifetime in wireless sensor networks by combining modified particle swarm optimization with genetic algorithm. The two-level approach selects eligible nodes using genetic algorithm in the first level and selects cluster heads using modified particle swarm optimization algorithm in the second level. The study compares parameters such as energy consumption, delay, throughput, network lifetime, and energy efficiency with conventional optimization algorithms.
WIRELESS PERSONAL COMMUNICATIONS
(2022)
Article
Chemistry, Multidisciplinary
Fatma H. Elfouly, Rabie A. Ramadan, Ahmed Y. Khedr, Kusum Yadav, Ahmad Taher Azar, Mohamed A. Abdelhamed
Summary: This study aims to discover the best deployment plan for WSN considering various constraints. By defining the deployment problem as an optimization problem and mathematically formulating it using Integer Linear Programming, the coverage of a given field is maximized with a network lifetime constraint. The use of Swarm Intelligence as a heuristic algorithm for large-scale deployment problem has proven to be efficient, with over 30% improvement in coverage and network lifetime demonstrated in simulation experiments.
APPLIED SCIENCES-BASEL
(2021)
Review
Computer Science, Interdisciplinary Applications
R. Ramya, T. Brindha
Summary: This article presents a comprehensive analysis of 85 research papers on conventional Cluster Head Selection (CHS) approaches in Wireless Sensor Network based Internet of Things (WSN-IoT). The analysis shows that while these conventional approaches prolong network lifetime and reduce energy depletion, they fail to provide enhanced security, Quality of Service (QoS), and balance the temperature and load of WSN-IoT devices. The article concludes that integrating optimization algorithms with machine learning approaches can achieve QoS, security, temperature, and load balance in addition to energy efficiency and network longevity.
ADVANCES IN ENGINEERING SOFTWARE
(2022)
Article
Telecommunications
Bartlomiej Placzek, Marcin Bernas
WIRELESS PERSONAL COMMUNICATIONS
(2017)
Article
Computer Science, Information Systems
Marcin Lewandowski, Bartlomiej Placzek, Marcin Bernas, Piotr Szymala
WIRELESS COMMUNICATIONS & MOBILE COMPUTING
(2018)
Article
Chemistry, Analytical
Marcin Bernas, Bartlomiej Placzek, Wojciech Korski, Piotr Loska, Jaroslaw Smyla, Piotr Szymala
Article
Chemistry, Analytical
Marcin Bernas, Bartlomiej Placzek, Jaroslaw Smyla
Article
Physics, Multidisciplinary
Marcin Cholewa, Bartlomiej Placzek
Article
Chemistry, Analytical
Marcin Lewandowski, Bartlomiej Placzek, Marcin Bernas
Summary: The recent development of wireless wearable sensor networks has opened up new applications in various fields. A new method based on embedded classifiers has been proposed to extend the network lifetime by avoiding unnecessary data transmissions, which has been shown to significantly prolong network lifetime while maintaining high accuracy in activity recognition.
Article
Chemistry, Analytical
Marcin Lewandowski, Bartlomiej Placzek
Summary: This study introduces a new method to prolong the lifetime of wireless sensor networks by reducing data transmissions between neighboring sensor nodes, improving the accuracy of event detection. Experimental evaluation confirmed that the proposed method significantly extends the network lifetime and is more effective than current algorithms.
Article
Chemistry, Analytical
Marcin Bernas, Bartlomiej Placzek, Marcin Lewandowski
Summary: Nowadays, sensor-equipped mobile devices allow us to accurately detect daily activities. This paper proposes a personal area sensor network model that utilizes information from multiple sensor nodes to improve activity recognition accuracy. Nodes process sensor readings locally and the main node performs a final recognition based on a weighted voting procedure. Experimental results show that the proposed method achieves higher accuracy compared to existing methods.
Article
Chemistry, Analytical
Bartlomiej Placzek
Summary: This paper introduces a method that uses predicted intervals of sensor readings to decrease the amount of transmitted data. The method employs a multi-agent system to explore historical data and evaluate similarity for prediction. Experimental results demonstrate the effectiveness of this method in reducing transmission.
Article
Computer Science, Information Systems
Bartlomiej Placzek, Marcin Bernas, Marcin Cholewa