Article
Computer Science, Theory & Methods
Anjula Mehto, Shashikala Tapaswi, K. K. Pattanaik
Summary: This paper proposes a squirrel search algorithm-based rendezvous points selection (SSA-RPS) method to choose optimal RPs for reliable data collection under non-uniform data generation and limited buffer capacity constraints. The SSA-RPS outperforms existing methods in terms of dropped packets, data gathering ratio, energy consumption, and network lifetime according to simulation results.
Article
Computer Science, Hardware & Architecture
Anjula Mehto, Shashikala Tapaswi, K. K. Pattanaik
Summary: This paper addresses the issues of data acquisition latency, data load among RPs, and the number of RPs by proposing a Multi-Objective Particle Swarm Optimization based RPs Selection method. It utilizes Particle Swarm Optimization to solve multi-objective optimization problems, and introduces an improved ant colony optimization for faster convergence towards the optimal solution.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2021)
Article
Mathematics
Giresse Franck Noudjiep Djiepkop, Senthil Krishnamurthy
Summary: This study developed a Discrete Particle Swarm Optimization (DPSO) method to solve the problem of distribution system feeder reconfiguration. The method is capable of meeting power demand in both steady-state and dynamic power system operations, and outperforms other optimization algorithms in terms of actual power loss reduction and load balancing.
Article
Computer Science, Interdisciplinary Applications
Rajesh Himanshu, Rajesh Khanna, Anil Kumar
Summary: The precise location of target nodes in wireless sensor networks is crucial, but can be affected by anisotropy. This study proposes a fusion method for distance and angle information, using virtual anchor nodes and artificial intelligence algorithms to estimate target node positions. Simulation results show that the proposed methods outperform existing techniques in terms of accuracy, energy, scalability, and convergence time.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Thermodynamics
Hielfarith Suffri Shamsuddin, Patrice Estelle, Javier Navas, Normah Mohd-Ghazali, Maziah Mohamad
Summary: This study investigates the influence of surfactant Triton X-100 on boron nitride nanotubes nanofluid in microchannel heat sink, showing that the surfactant can improve thermal performance at 30 degrees Celsius and reduce pressure drop at 50 degrees Celsius. Optimized MCHS dimensions given by MOPSO technique result in improved overall performance for MCHS systems.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2021)
Article
Automation & Control Systems
Xuxun Liu, Tian Wang, Weijia Jia, Anfeng Liu, Kaikai Chi
Summary: The article proposes a quick convex hull-based rendezvous planning scheme to improve the performance of wireless sensor networks. This scheme aims to achieve full connectivity for disjoint WSNs, construct a shorter trip tour, and minimize the data delivery latency. The benefits of this new scheme include being designed for disjoint WSNs, suitable for delay-harsh applications, and having lower computational complexity compared to existing methods.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Computer Science, Information Systems
Qian Dong, Feng Zhu, Jinbao Xia, Mi Lu
Summary: This paper proposes a particle swarm optimization-enabled seamless handoff mechanism for wireless sensor networks to tackle deteriorating link quality. By designing a static receiver-triggered protocol and particle swarm optimization method, the paper achieves seamless handoff for data transmission and reduces latency.
HUMAN-CENTRIC COMPUTING AND INFORMATION SCIENCES
(2023)
Article
Mathematics
Omer Ali, Qamar Abbas, Khalid Mahmood, Ernesto Bautista Thompson, Jon Arambarri, Imran Ashraf
Summary: This study introduces a competitive coevolution process to enhance the capability of Phasor PSO (PPSO) for global optimization problems. Experimental results show that the improved competitive multi-swarm PPSO (ICPPSO) algorithm achieves a dominating performance, with average improvements of 15%, 20%, 30%, and 35% over PPSO and FMPSO.
Article
Computer Science, Artificial Intelligence
Xiangyu Wang, Bingran Zhang, Jian Wang, Kai Zhang, Yaochu Jin
Summary: This paper proposes a novel cluster-based competitive particle swarm optimizer equipped with a sparse truncation operator for solving sparse multi-objective optimization problems. Experimental results show that the proposed algorithm outperforms its peers on sparse test instances and neural network training tasks.
SWARM AND EVOLUTIONARY COMPUTATION
(2022)
Article
Computer Science, Artificial Intelligence
Mohammadali Saniee Monfared, Sayyed Ehsan Monabbati, Atefeh Rajabi Kafshgar
Summary: This paper discusses noncooperative multi-objective optimization problems where the objective holders are independent humans or human-based entities, suggesting a new solution concept of the Pareto-optimal Equilibrium point. The interplay between game problems and multi-objective optimization problems is investigated, with illustrative examples provided to deepen the understanding of when a POE solution is achievable.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Telecommunications
Rebeca Estrada, Rabeb Mizouni, Hadi Otrok, Azzam Mourad
Summary: This paper addresses the task allocation problem in Mobile Crowdsensing (MCS) by forming a coalition of task publishers considering workers' route preferences. Two coalition formation models are proposed, which effectively increase worker payment and improve the quality of task information.
VEHICULAR COMMUNICATIONS
(2021)
Article
Computer Science, Information Systems
Chaya Shivalinge Gowda, P. V. Y. Jayasree
Summary: In wireless sensor networks, data collection is conducted using a mobile sink to prevent energy hole and hotspot issues, while a new hybrid neural network algorithm and clustering method are employed to optimize energy utilization through selected RPs.
Article
Automation & Control Systems
Shi Dong, Yuanjun Xia, Joarder Kamruzzaman
Summary: Mobile edge computing (MEC) deploys servers on the edge of the mobile network to reduce data transmission delay and meet the computing demand of mobile computing tasks. However, limited resources and bandwidth of MEC servers require efficient task offloading and scheduling. This article proposes particle swarm optimization (PSO) and quantum PSO based strategies to optimize task offloading, showing significant improvements compared to advanced strategies.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Engineering, Multidisciplinary
Amar Jukuntla, Venkatesulu Dondeti
Summary: This article introduces a novel protocol called EEMSDC that aims to address the energy consumption issue in Wireless Sensor Networks (WSNs). The protocol optimizes the tour of a mobile sink by using predetermined TDMA slots for efficient data transmission with rendezvous nodes (RNs). Simulation results show that the proposed protocol outperforms existing protocols in terms of network lifetime, energy consumption, and data loss.
Article
Computer Science, Artificial Intelligence
Claudiu Pozna, Radu-Emil Precup, Erno Horvath, Emil M. Petriu
Summary: This article presents a hybrid metaheuristic optimization algorithm that combines particle filter (PF) and particle swarm optimization (PSO) algorithms. The algorithm is applied to the optimal tuning of proportional-integral-fuzzy controllers for position control of integral-type servo systems, resulting in reduced energy consumption. A comparison with other metaheuristic algorithms is provided at the end of the article.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Kumar Nitesh, Amar Kaswan, Prasanta K. Jana
MICROSYSTEM TECHNOLOGIES-MICRO-AND NANOSYSTEMS-INFORMATION STORAGE AND PROCESSING SYSTEMS
(2019)
Article
Computer Science, Hardware & Architecture
Amar Kaswan, Abhinav Tomar, Prasanta K. Jana
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2018)
Article
Computer Science, Information Systems
Vishakha Singh, Indrajeet Gupta, Prasanta K. Jana
JOURNAL OF GRID COMPUTING
(2020)
Article
Computer Science, Information Systems
Lalatendu Muduli, Devi Prasad Mishra, Prasanta K. Jana
IEEE SYSTEMS JOURNAL
(2020)
Article
Computer Science, Information Systems
Abhinav Tomar, Lalatendu Muduli, Prasanta K. Jana
Summary: This study proposes a novel on-demand charging scheduling scheme for WRSNs, which improves charging performance by efficiently distributing multiple mobile chargers with network attributes blended using fuzzy logic, and determining charging thresholds based on energy consumption rates.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2021)
Article
Computer Science, Information Systems
Amar Kaswan, Prasanta K. Jana, Madhusmita Dash, Anupam Kumar, Bhabani P. Sinha
Summary: This article proposes a game theory-based distributed mobile charging protocol, called DMCP, to address the on-demand charging problem in wireless rechargeable sensor networks. Through simulations and hypothesis testing, it is shown that DMCP reduces charging delay and improves charging coverage and survival rate.
ACM TRANSACTIONS ON SENSOR NETWORKS
(2023)
Article
Computer Science, Information Systems
Deepak Kumar Rakesh, Prasanta K. Jana
Summary: This article introduces a new feature selection method called class-label specific mutual information (CSMI), which selects a specific subset of features for each class label. The proposed method maximizes the information shared among the selected features and the target class label while minimizing the same with all classes. Experimental results show that the CSMI method outperforms traditional and state-of-the-art ITFS methods in multiple benchmark datasets.
IEEE TRANSACTIONS ON INFORMATION THEORY
(2022)
Article
Computer Science, Artificial Intelligence
Vishakha Singh, Sameer Shrivastava, Sanjay Kumar Singh, Abhinav Kumar, Sonal Saxena
Summary: The shortage of effective antibiotics and the high incidence of diseases caused by multi-drug resistant pathogens have led to the development of in-silico machine and deep learning tools for rapid drug discovery. A robust deep learning-based model, MSTCN-ABPpred (BL), was developed using multi-scale temporal convolutional networks to classify antibacterial peptides with 98% accuracy. This model incorporates a continual learning module for dynamic adaptation through re-training on new data points.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Nishant Jain, Prasanta K. Jana
Summary: This paper proposes a logically randomized forest (LRF) algorithm, which improves traditional tree-based ensemble algorithms (TEAs) by incorporating two enhancements. The first enhancement addresses biasness by performing feature-level engineering, while the second enhancement selects more informative feature sub-spaces. Experimental results demonstrate that the LRF algorithm outperforms existing TEAs.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Nidhi Kumari, Prasanta K. Jana
Summary: Fog computing is a three-tier architecture that aims to reduce delay and energy consumption between IoT devices and the cloud. In this paper, a scheme based on the multilevel Multiple Criteria Decision Making (MCDM) technique is proposed for fog node selection and task scheduling. The proposed scheme incorporates delay, energy, and reliability to rank the fog nodes and tasks, outperforming existing algorithms according to extensive simulations.
DISTRIBUTED COMPUTING AND INTELLIGENT TECHNOLOGY, ICDCIT 2023
(2023)
Article
Computer Science, Hardware & Architecture
Anirudh Yadav, Prasanta K. Jana, Shashank Tiwari, Abhay Gaur
Summary: In this paper, a novel clustering based delay aware energy efficient task offloading scheme is proposed for device to fog nodes. Extensive simulations show that the use of explicit clustering in the proposed algorithm improves FN participation and reduces activity time and energy levels, thereby increasing the sustainability of the FNs and TNs. Moreover, cluster size distribution also lowers the running time of our algorithm.
IEEE TRANSACTIONS ON SUSTAINABLE COMPUTING
(2023)
Article
Multidisciplinary Sciences
Vishakha Singh, Sanjay Kumar Singh
Summary: The COVID-19 pandemic has accelerated the process of therapeutic drug discovery, leading to the development of computational tools through collaboration between biomedical scientists and AI experts. The DeepAVPiden model proposed in this study, along with its corresponding web app, aims to discover novel antiviral peptides in proteomes of living organisms.
SCIENTIFIC REPORTS
(2023)
Article
Computer Science, Information Systems
Amar Kaswan, Prasanta K. Jana, Sajal K. Das
Summary: This paper presents a detailed survey on mobile charging techniques in wireless rechargeable sensor networks, filling the research gap in this field. The paper first introduces network models, WPT techniques, system design issues, and performance metrics. Then, it categorizes the MCTs based on design attributes and reviews the literature. Finally, potential directions for future research are highlighted.
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS
(2022)
Article
Computer Science, Hardware & Architecture
Raj Anwit, Prasanta K. Jana, Abhinav Tomar
Summary: This paper proposes a novel data collection scheme for delay-harsh applications, addressing the issues of existing works focusing only on connected networks, ignoring realistic propagation models, and optimizing the number of RPs and MSs.
IEEE TRANSACTIONS ON SUSTAINABLE COMPUTING
(2022)
