Article
Computer Science, Theory & Methods
Salim El Khediri
Summary: This paper provides a comprehensive review of clustering protocols applied to WSNs in recent years. The protocols are categorized into four classes, and their efficiency is evaluated based on features, performance, and clustering methodologies.
Article
Engineering, Electrical & Electronic
Yadong Gong, Guoming Lai
Summary: In this paper, a centralized clustering protocol called Low-Energy Dynamic Clustering (LEDC) is proposed to enhance the energy efficiency in query-based wireless sensor networks (WSNs). LEDC utilizes prediction-based scheme and centralized optimal dynamic cluster formation algorithms to match the distribution of clusters with that of query targets, and suggests an energy-aware forwarding strategy and a parallel processing algorithm to improve energy efficiency and network throughput.
IEEE SENSORS JOURNAL
(2022)
Article
Computer Science, Information Systems
Ikram Daanoune, Baghdad Abdennaceur, Abdelhakim Ballouk
Summary: The paper introduces the popular hierarchical routing protocol LEACH in Wireless Sensor Networks (WSN), which reduces energy consumption by grouping sensor nodes into clusters and electing CHs. The study provides a detailed exploration of LEACH descendant clustering protocols, comparisons with other surveys, comparative analysis, and recommendations for future research in WSN.
Article
Engineering, Electrical & Electronic
Yadong Gong, Xiaoyun Guo, Guoming Lai
Summary: In this article, a centralized energy-efficient clustering (CEEC) protocol is proposed to enhance energy efficiency in wireless sensor networks (WSNs) through node energy balancing schemes. The CH-rotation approach is used for intracluster energy balancing, while four sequential algorithms are suggested for intercluster energy balancing. Simulation results demonstrate that the CEEC protocol outperforms classical clustering mechanisms in terms of network lifetime, energy consumption, and network throughput.
IEEE SENSORS JOURNAL
(2023)
Article
Computer Science, Information Systems
Shaha Al-Otaibi, Amal Al-Rasheed, Romany F. Mansour, Eunmok Yang, Gyanendra Prasad Joshi, Woong Cho
Summary: The paper presents a hybrid metaheuristic cluster-based routing technique for wireless sensor networks, incorporating BSO-LD clustering and WWO-HC routing processes for improved energy efficiency and network lifetime performance. Experimental analysis confirms the superiority of the HMBCR technique over other methods in various aspects.
Article
Computer Science, Artificial Intelligence
Carolina Del-Valle-Soto, Alma Rodriguez, Cesar Rodolfo Ascencio-Pina
Summary: This paper reviews the most recent clustering routing protocols for Wireless Sensor Networks (WSNs) based on metaheuristic techniques, aiming to provide clear and meaningful information about state-of-the-art approaches. Due to a lack of comprehensive survey studies in this field, a more in-depth study is presented, focusing on different metaheuristic-based strategies for selecting optimal cluster heads. The primary objective is to review approaches that have developed novel cluster-based routing protocols primarily for reducing energy consumption in WSNs. The survey examines each protocol considering its methodology, properties, and provides a comparative analysis of the reviewed approaches based on network structure, characteristics, metaheuristic algorithm used, search strategy, metrics, and results reported.
ARTIFICIAL INTELLIGENCE REVIEW
(2023)
Review
Computer Science, Hardware & Architecture
Swati Gupta, Niraj Pratap Singh
Summary: Wireless transmission of information using water as a communication channel has potential applications in underwater observation systems. However, underwater wireless sensor networks face challenges such as node movement, limited bandwidth, low data rates, limited battery power, and failures due to pollution and corrosion. Sophisticated signal processing methods are needed for acoustic communications. Routing protocols need to be designed to optimize energy expenditure and bandwidth utilization in the complex underwater environment.
JOURNAL OF SUPERCOMPUTING
(2023)
Article
Engineering, Electrical & Electronic
Dipak Kumar Sah, Abhishek Hazra, Nabajyoti Mazumdar, Tarachand Amgoth
Summary: This study proposes an efficient routing awareness scheduling (ERAS) algorithm to address the energy shortage and network load issues in wireless sensor networks. The algorithm employs a solar harvesting system as a hierarchical clustering-based routing protocol and utilizes synchronization-based scheduling to improve throughput. The ERAS algorithm performs efficiently while considering various performance matrices, including network lifetime, packet delivery ratio, energy consumption, and network sustainability.
IEEE SENSORS JOURNAL
(2023)
Article
Computer Science, Information Systems
Shreya Khisa, Sangman Moh
Summary: Underwater wireless sensor networks face challenges such as energy restrictions, routing protocol delays, and energy consumption, requiring an energy-efficient routing mechanism to improve network lifetime.
Article
Computer Science, Information Systems
Bo Zeng, Chaofeng Zhao, Yongxin Zhang, Jie Sun, Xiaofeng Gao
Summary: This study proposes a lightweight and flexible clustering algorithm based on sectors to optimize energy efficiency by dividing the area into virtual sectors and creating even sector clusters using the sector decomposition method.
Article
Engineering, Electrical & Electronic
Mohammad Ali Alharbi, Mario Kolberg
Summary: This paper presents an unequal clustering approach with the BS at the center of a circular area, where the cluster size is computed based on node density, and the number of clusters increases from outwards to inwards towards the BS, showing considerable performance gain over selected benchmark works.
IEEE SENSORS JOURNAL
(2021)
Article
Engineering, Electrical & Electronic
Samayveer Singh, Aridaman S. Nandan, Aruna Malik, Neeraj Kumar, Ahmed Barnawi
Summary: To address the challenges of energy consumption in wireless sensor networks (WSN), especially in the context of applications for disaster management in smart cities, an improved Genetic Algorithm (GA) called ModifyGA is proposed to optimize the selection of cluster-head nodes. By incorporating dynamic sensing range and developing fitness functions, ModifyGA enhances energy efficiency and satisfies various constraints for intra-cluster optimization, energy utilization, hop-count reduction, and node selection. Simulation analysis of ModifyGA shows promising results when operating with different types of sinks, providing an impartial comparative analysis.
IEEE SENSORS JOURNAL
(2021)
Article
Computer Science, Information Systems
Lilian C. Mutalemwa, Seokjoo Shin
Summary: The proposed ReRR protocol introduces long-term source location privacy protection compared to fake packet-based protocols, with an energy-efficient routing algorithm ensuring reliability and improved network lifetime. The ReRR protocol outperforms existing fake packet-based routing techniques in terms of SLP reliability.
Article
Engineering, Electrical & Electronic
C. Jothi Kumar, V. Deeban Chakravarthy, Kadiyala Ramana, Praveen Kumar Reddy Maddikunta, Qin Xin, G. Surya Narayana
Summary: This system achieves the clustering and data transmission of nodes in a sensor network through clustering and multi-hop routing methods. It proposes the Ordered Transmission Paradigm-Effective Routing (OTP-ER) protocol for selecting cluster head nodes and extends the network lifetime through optimized energy management.
OPTICAL AND QUANTUM ELECTRONICS
(2022)
Article
Engineering, Electrical & Electronic
Yun Xu, Wanguo Jiao, Mengqiu Tian
Summary: Energy optimization is crucial for energy-limited wireless sensor networks deployed in three-dimensional space. This study proposes an energy-efficient routing protocol for 3D WSN, aiming to find the minimum set of sensor nodes for full coverage of key points of interest using an improved genetic algorithm. The proposed adaptive clustering routing scheme includes selecting cluster heads, setting intra-cluster communication modes, and deciding inter-cluster communication modes, ultimately maximizing network energy utilization.
IEEE SENSORS JOURNAL
(2021)
Article
Computer Science, Artificial Intelligence
Dinesh Kumar Anguraj, Venkata Naresh Mandhala, Debnath Bhattacharyya, Tai-hoon Kim
Summary: The study proposes an automatic Smart data mining based Irrigation Support Scheme utilizing WSN and CNSVMHC to efficiently manage irrigation, avoiding the need for weekly irrigation.
JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING
(2021)
Article
Computer Science, Artificial Intelligence
Sk. Meeravali, Debnath Bhattacharyya, N. Thirupathi Rao, Yu-Chen Hu
Summary: The paper presents a forked communication network model based on a queuing model, with equations developed for a better understanding. Results were calculated using MATLAB and MathCAD software, and compared with previous network models for performance evaluation.
CONNECTION SCIENCE
(2021)
Article
Telecommunications
S. NagaMallik Raj, Debnath Bhattacharyya, Divya Midhunchakkaravarthy, Tai-hoon Kim
Summary: This study introduces a new Multi-hop in Clustering with Mobility (MCM) model and demonstrates its effectiveness in saving energy consumption of sensor nodes through comparison with other techniques.
WIRELESS PERSONAL COMMUNICATIONS
(2021)
Article
Computer Science, Information Systems
Bhanu Prakash Doppala, Debnath Bhattacharyya, Midhun Chakkravarthy, Tai-hoon Kim
Summary: In this study, a hybrid method using genetic algorithm and radial basis function was proposed to improve the accuracy of coronary disease detection. Through feature selection mechanism, the proposed system achieved an accuracy of 85.40% and 94.20%.
DISTRIBUTED AND PARALLEL DATABASES
(2023)
Article
Computer Science, Software Engineering
Kalaipriyan Thirugnanasambandam, M. Rajeswari, Debnath Bhattacharyya, Jung-yoon Kim
Summary: The Artificial Bee Colony algorithm is an optimization algorithm inspired by the foraging behavior of honeybees. This paper proposes an improved solution search strategy to balance the diversification and intensification processes in the algorithm. Experimental results demonstrate that the proposed algorithm outperforms the original ABC algorithm in solving numerical optimization problems.
AUTOMATED SOFTWARE ENGINEERING
(2022)
Article
Computer Science, Theory & Methods
K. Satyanarayana, N. Thirupathi Rao, Debnath Bhattacharyya, Yu-Chen Hu
Summary: This paper focuses on the decomposition of image quality assessment study using Three Parameter Logistic Mixture Model and k-means clustering (TPLMM-k). The proposed algorithm outperforms previous techniques in terms of image decomposition and segmentation, as demonstrated by various performance metrics such as VOI, GCE, and PRI.
MULTIDIMENSIONAL SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Computer Science, Artificial Intelligence
Bandi Vamsi, Debnath Bhattacharyya, Divya Midhunchakkravarthy, Jung-yoon Kim
Summary: The research focuses on using deep learning techniques with VGG-16 architecture and Random Forest algorithm for detecting hemorrhagic stroke in brain CT images. A lightweight two-step convolution model is proposed, showing better results compared to existing heavyweight models, with a promising dice coefficient of 72.92 and an accuracy of 97.81%.
TRAITEMENT DU SIGNAL
(2021)
Article
Computer Science, Hardware & Architecture
N. Thirupathi Rao, Debnath Bhattacharyya, S. K. Meeravali, Seung-phil Hong
Summary: This paper evaluates the performance of a distributed energy model with compound poisson arrivals. It discusses the usage and operations on communication networks, and demonstrates that combining energy preservation with end-user performance can decrease energy consumption.
SUSTAINABLE COMPUTING-INFORMATICS & SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Stephen Neal Joshua Eali, Debnath Bhattacharyya, Thirupathi Rao Nakka, Seng-Phil Hong
Summary: To build a flexible and efficient brain tumour segmentation system, the researchers proposed a preprocessing method based on U-Net and Support Vector Machine (SVM). This method allows for faster training with less overfitting and can identify both local and global features. Extensive testing showed that the model performed well in segmenting brain tumors.
TRAITEMENT DU SIGNAL
(2022)
Article
Health Care Sciences & Services
Bhanu Prakash Doppala, Debnath Bhattacharyya, Midhunchakkaravarthy Janarthanan, Namkyun Baik
Summary: Machine intelligence plays a crucial role in the medical field, improving the accuracy of disease diagnosis and prediction, thereby enhancing the treatment of cardiovascular diseases. The proposed ensemble model performs well on multiple datasets, promising to ensure the safety and health security of individuals.
JOURNAL OF HEALTHCARE ENGINEERING
(2022)
Article
Computer Science, Software Engineering
Debnath Bhattacharyya, N. Thirupathi Rao, Eali Stephen Neal Joshua, Yu-Chen Hu
Summary: Lung nodules are abnormal growths and lesions in the lungs, which are usually harmless but can sometimes indicate lung cancer. This study aims to develop a deep learning algorithm called DB-NET to identify lung nodules using the LUNA-16 dataset and explore the prevalence of lung nodules. The DB-NET architecture, incorporating Mish nonlinearity function and mask class weights, shows promising results in lung nodule segmentation and achieves a high level of accuracy.
Article
Agronomy
Debnath Bhattacharyya, Eali Stephen Neal Joshua, N. Thirupathi Rao, Tai-hoon Kim
Summary: ICT breakthroughs have played a vital role in global social and economic development. Rural Indians heavily rely on agriculture for income, and the increasing population demands modernized farming practices. ICT is essential for educating farmers on environmentally friendly techniques, enhancing food production by solving various challenges. This research focuses on predicting soil moisture and categorizing sugarcane output, aiming to assist farmers and agricultural authorities in boosting production.
Article
Agronomy
Jampani Satish Babu, Smitha Chowdary Ch, Debnath Bhattacharyya, Yungcheol Byun
Summary: Estimating the acreage of menthol mint using remote sensing technology can reduce uncertainty in menthol mint output. The Bheemunipatnam taluk in the Vishakhapatnam district is the most productive area for growing menthol mint. The total acreage of menthol mint crop in the study region is estimated to be around 58,000,284.70 ha.
Article
Engineering, Multidisciplinary
P. Chandra Sekhar, N. Thirupathi Rao, Debnath Bhattacharyya, Tai-hoon Kim
Summary: In this paper, the performance of image segmentation algorithms with the addition of the Pearsonian Type III mixture model was analyzed. By using the Type III Pearsonian system of distributions, the image segmentation process was conducted, and performance parameters PRI, GCE, and VOI were estimated. The proposed method showed more precise results for input images compared to other existing models.
JOURNAL OF SCIENTIFIC & INDUSTRIAL RESEARCH
(2021)
Article
Computer Science, Information Systems
Kalaipriyan Thirugnansambandam, Debnath Bhattacharyya, Jaroslav Frnda, Dinesh Kumar Anguraj, Jan Nedoma
Summary: This paper addresses the multiobjective problem in target-based Wireless Sensor Networks using a Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) to efficiently solve coverage and connectivity challenges. NSGA-II preserves better solutions in different objectives simultaneously, and balances exploration and exploitation phases through density estimation and crowd comparison.
CMC-COMPUTERS MATERIALS & CONTINUA
(2021)
