Article
Remote Sensing
Salil Bharany, Sandeep Sharma, Jaroslav Frnda, Mohammed Shuaib, Muhammad Irfan Khalid, Saddam Hussain, Jawaid Iqbal, Syed Sajid Ullah
Summary: This paper presents a unique clustering approach for forest fire detection, which transfers data to a base station via wireless communication to extend the lifetime of unmanned aerial vehicles. The proposed EE-SS algorithm, which regulates the energy usage of nodes, outperforms other state-of-art algorithms in terms of overall energy usage, network lifetime, and cluster building time.
Article
Computer Science, Artificial Intelligence
Youcef Azzoug, Abdelmadjid Boukra
Summary: This paper presents a recapitulation of the historical evolution and a future overview of all vehicular ad-hoc network (VANET) routing problems, exploring bio-inspired optimization methods for solving various VANET routing issues. It provides insight into the nature of different routing problems, the range of studies, and the types of metaheuristics used for optimization, guiding the future research direction in this field.
ARTIFICIAL INTELLIGENCE REVIEW
(2021)
Article
Computer Science, Hardware & Architecture
Vikas Tyagi, Samayveer Singh
Summary: The main goal of designing SDN-enabled WSNs with limited network resource utilization is to maximize the network lifespan. Clustering and routing techniques are widely used to achieve energy-efficient and stable network performance in SDN-enabled WSNs by balancing the network load. However, selecting optimal control nodes (CNs) is a critical challenge in clustering due to the high computational complexity of global optimization. Therefore, optimizing the CNs selection for the routing process with limited network resources is necessary.
JOURNAL OF SUPERCOMPUTING
(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, Information Systems
Muhammad Yeasir Arafat, Sangman Moh
Summary: This article presents bio-inspired localization (BIL) and clustering (BIC) schemes in UAV networks for wildfire detection and monitoring, which significantly outperform conventional schemes in terms of various performance metrics. The proposed algorithms enhance localization accuracy, clustering efficiency, and data transmission efficiency.
Article
Computer Science, Information Systems
Ali Khan, Somaiya Khan, Athar Shahzad Fazal, Zhongshan Zhang, Adnan Omer Abuassba
Summary: A novel intelligent cluster routing scheme (CRSF) is proposed for flying ad hoc networks, with cluster head selection based on fitness and cluster management inspired by moth flame optimization, improving efficiency and stability of network communication. Additionally, routing mechanism for UAV communication and CH re-selection mechanism are introduced for effective topology management to maintain stable clusters.
SCIENCE CHINA-INFORMATION SCIENCES
(2021)
Article
Chemistry, Analytical
Shadab Khan, Yash Veer Singh, Prasant Singh Yadav, Vishnu Sharma, Chia-Chen Lin, Ki-Hyun Jung
Summary: This paper proposes an intelligent bio-inspired autonomous surveillance system using underwater sensor networks, which improves the energy efficiency and lifespan of the network by employing the tunicate swarm algorithm for cluster head selection.
Article
Computer Science, Hardware & Architecture
N. Anil Kumar, Y. Sukhi, M. Preetha, K. Sivakumar
Summary: Wireless Sensor Networks (WSN) is a novel technology applicable in diverse domains and remains a hot research topic. Energy efficiency is crucial, and clustering is commonly used to achieve it. A new unequal clustering and routing technique using the ant colony optimization (ACO) algorithm is proposed to address the hotspot issue. The experimental results confirmed the superiority of the presented model under various validation parameters.
JOURNAL OF CIRCUITS SYSTEMS AND COMPUTERS
(2023)
Article
Computer Science, Information Systems
Omer T. Abdulhae, Jit Singh Mandeep, M. T. Islam
Summary: Flying Ad-Hoc Network (FANET) is a wireless network composed of interconnected Unmanned Aerial Vehicles (UAVs) that can self-organize and provide low-cost and adaptable flying nodes. Researchers have developed a hierarchical routing technique called clustering to address the challenges posed by the high mobility and dynamic topology of UAV networks. This study conducts a comprehensive survey of cluster-based routing protocols (CBRPs) and reviews 21 CBRPs based FANETs, providing insights into their strengths, weaknesses, and future improvements.
Article
Engineering, Electrical & Electronic
Jayashree Agarkhed, Patil Yogita Dattatraya, Siddarama Patil
Summary: Agriculture is crucial to India's economic growth, which can be enhanced with new technologies. Precision Agriculture and Wireless Sensor Network technology have various applications in agriculture. Proposed protocol using a Decision Support System for intelligent path selection based on traffic rate can address issues like network dynamicity and performance degradation.
INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS
(2021)
Article
Computer Science, Hardware & Architecture
Peeyush Tewari, Sandesh Tripathi
Summary: In this research, a neuro-fuzzy approach to energy-efficient routing (NFEER) for IoT-enabled WSNs is proposed. The NFEER takes into account multiple parameters such as the distance between cluster head and sink, cluster size, and residual energy of cluster head to find the most efficient path across the network, mitigating the hotspot issue. Extensive simulations demonstrate that the NFEER extends the stability period by 27.98%, 13.97%, and 10.91% compared to existing protocols, resulting in enhanced stability duration, residual energy, network lifetime, and throughput.
JOURNAL OF SUPERCOMPUTING
(2023)
Review
Green & Sustainable Science & Technology
Christy Jackson Joshua, Prassanna Jayachandran, Abdul Quadir Md, Arun Kumar Sivaraman, Kong Fah Tee
Summary: This article discusses the issues of network connectivity and optimization methods in vehicular ad hoc networks (VANETs). Research has shown that various difficulties in VANETs can be solved by applying techniques derived from nature and evolution. Additionally, the use of information and communication technologies can reduce accident rates, improve mobility, and mitigate environmental impacts through parameter tuning approaches. Significant research works are presented regarding cluster formation, routing, and scheduling of broadcasts.
Article
Telecommunications
Sharad Saxena, Deepak Mehta
Summary: This research proposed a WSN network design based on a hierarchical structure and energy efficient routing method. Clusters are formed using fuzzy multi-criteria decision approach and the Penguin Search Optimization Algorithm is used for strategic planning, showing better performance compared to existing techniques.
WIRELESS PERSONAL COMMUNICATIONS
(2021)
Article
Computer Science, Information Systems
Radwa Attia, Abeer Hassaan, Rawya Rizk
Summary: The paper proposes an Advanced Greedy Hybrid Bio-Inspired (AGHBI) routing protocol with a greedy forwarding system to enhance the performance of IoV. By utilizing a modified hybrid routing scheme with the help of bee colony optimization, the highest quality of service route is selected and maintained with minimum overflow. Simulation results show that the protocol effectively improves packet delivery ratio and delay, while maintaining acceptable overhead and hops count among all vehicles in both V2V and V2I environments.
Article
Computer Science, Artificial Intelligence
P. Visu, T. Suriya Praba, N. Sivakumar, R. Srinivasan, T. Sethukarasi
Summary: The optimal usage of scarce and inadequate resources in wireless sensor networks is necessary, with a focus on reducing power consumption and increasing WSN's lifetime. Efficient energy algorithms are proposed for effective routing, combining in-network data aggregation and standardized routing. The DC-KHO Routing algorithm aims to overcome challenges in transmission time, residual energy, and computational time, leading to a significant increase in the network's lifespan.
JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING
(2021)
Article
Computer Science, Hardware & Architecture
Kiranbir Kaur, Salil Bharany, Sumit Badotra, Karan Aggarwal, Anand Nayyar, Sandeep Sharma
Summary: Cloud computing is a promising technology that functions as a resource provisioning platform without user participation. This paper presents a middleware in .NET Core for live migration of persistent polyglot data in heterogeneous clouds. The suggested technique outperforms offline migration in terms of migration time, energy usage, and throughput.
JOURNAL OF SUPERCOMPUTING
(2023)
Article
Green & Sustainable Science & Technology
Edeh Michael Onyema, M. Anand Kumar, Sundaravadivazhagn Balasubaramanian, Salil Bharany, Ateeq Ur Rehman, Elsayed Tag Eldin, Muhammad Shafiq
Summary: Due to the latest advancements in networking devices, there is a need to build future intelligent networks. Software-defined networks (SDN) are one of the latest and most trusted technologies. SDN provides network virtualization and has started to replace traditional networks at faster rates. However, SDN also faces security issues.
Article
Chemistry, Analytical
Ibrahim Aqeel, Ibrahim Mohsen Khormi, Surbhi Bhatia Khan, Mohammed Shuaib, Ahlam Almusharraf, Shadab Alam, Nora A. Alkhaldi
Summary: This paper proposes a novel AI-based load balancing model that utilizes the Chaotic Horse Ride Optimization Algorithm and big data analytics for energy and load optimization in cloud-enabled IoT environments. Experimental results demonstrate that the proposed model outperforms existing models and has the potential to address critical challenges in the IoT domain.
Article
Computer Science, Artificial Intelligence
Shamimul Qamar, Mohd Amaan, Mohammed Inamur Rahman, Ibrahim Aqeel, Mohammed Shuaib, Ibrahim Mohsen Khormi, Shadab Alam
Summary: Cloud computing combines a shared environment and the computer paradigm, allowing multiple users to access services and resources. This ecosystem can be globally accessible via the Internet and shared at all levels. This research proposes a novel method in cloud data transmission using hybrid machine learning techniques for security and enhanced routing. The experimental analysis shows that the proposed technique achieves a data transmission ratio of 65%, specificity of 78%, training accuracy of 93%, validation accuracy of 83%, and security analysis of 65%.
Article
Green & Sustainable Science & Technology
Shadab Alam, Surbhi Bhatia, Mohammed Shuaib, Mousa Mohammed Khubrani, Fayez Alfayez, Areej A. Malibari, Sadaf Ahmad
Summary: The Internet of Things (IoT) and blockchain (BC) are reliable technologies widely used in various contexts. IoT devices have potential for data sensing and recording, but also face processing and security issues. Traditional cryptographic techniques face challenges in securely transporting and storing medical records. Blockchain technology ensures data immutability, validity, and confidentiality, making it a powerful tool for creating a dependable electronic health record (EHR) system.
Article
Computer Science, Information Systems
Mahesh Thyluru Ramakrishna, Vinoth Kumar Venkatesan, Rajat Bhardwaj, Surbhi Bhatia, Mohammad Khalid Imam Rahmani, Saima Anwar Lashari, Aliaa M. Alabdali
Summary: The emergence of social media platforms has greatly improved social connections. However, finding the right friends remains a challenge. This study proposes a social and semantic-based collaborative filtering approach to enhance personalized recommendations. The results show that this approach improves recommendation accuracy and addresses the issues of sparsity and cold start.
Article
Computer Science, Information Systems
Mohammed Shuaib, Surbhi Bhatia, Shadab Alam, Raj Kumar Masih, Nayef Alqahtani, Shakila Basheer, Mohammad Shabbir Alam
Summary: The major problems and challenges in IoT systems include load balancing, reducing operational expenses, and energy efficiency. This study proposes a reliable method called Dynamic Energy-Efficient Load Balancing (DEELB) to address these resource allocation issues. Experimental results show that DEELB outperforms other existing techniques in terms of effectiveness and efficiency.
Article
Computer Science, Information Systems
Monika Arya, Hanumat Sastry, Bhupesh Kumar Dewangan, Mohammad Khalid Imam Rahmani, Surbhi Bhatia, Abdul Wahab Muzaffar, Mariyam Aysha Bivi
Summary: Vehicular networks are crucial to smart city development as they improve quality of life, security, and safety. This article presents an approach to intrusion detection in vehicular ad hoc networks (VANETs) using distributed federated learning of heterogeneous neural networks. The proposed method saves time and resources by using an efficient intruder detection approach that involves local deep learning-based IDS classifiers and communication sharing among vehicles.
Article
Chemistry, Multidisciplinary
Nayef Alqahtani, Shadab Alam, Ibrahim Aqeel, Mohammed Shuaib, Ibrahim Mohsen Khormi, Surbhi Bhatia Khan, Areej A. Malibari
Summary: Dementias in older people, particularly Alzheimer's disease (AD), pose significant challenges to modern medicine. Machine learning techniques applied to MRI can accelerate the diagnosis of AD and predict its progression. This research explores the use of longitudinal brain MRI features and a Deep Belief Network trained with the Mayfly Optimization Algorithm for the AD/non-AD classification of dementia patients. Including information about comorbidities and medication characteristics greatly enhances the predictive power of the models, with the random forest model outperforming others in terms of precision.
APPLIED SCIENCES-BASEL
(2023)
Article
Computer Science, Information Systems
Dipen Saini, Rahul Malik, Rachit Garg, Mohammad Khalid Imam Rahmani, Md. Ezaz Ahmed, Deepak Prashar, Sudan Jha, Jabeen Nazeer, Sultan Ahmad
Summary: This study proposes a novel multimodal hybrid bioinspired model for hyperspectral image augmentation, which continuously improves classification performance through iterative learning. The model represents input images in various domains and extracts windowed feature sets via a convolutional filter. It selects high inter-class variance features and reduces intra-class variance levels for improved classification performance. The model intelligently augments the selected images and classifies them using a customized CNN classifier. Through combining these models and incremental accuracy optimizations, the proposed model improves hyperspectral classification accuracy by 10.6% and precision by 10.4% compared to standard deep learning-based augmentation techniques.
Article
Computer Science, Artificial Intelligence
Akashdeep Bhardwaj, Keshav Kaushik, Salil Bharany, SeongKi Kim
Summary: The ease of flexibility, convenience, and smartness has made IoT a popular choice among industries and users, leading to a growing interest in this technology. With the increasing use of IoT, a large number of endpoints, including devices in our homes, are now connected to external networks. Firmware in IoT devices is typically heterogeneous and closed source, making it challenging to detect and evaluate security vulnerabilities. In recent years, similarity-based firmware security detection techniques have gained attention in research. Security concerns and attacks have become prominent in IoT security equipment, particularly IoT cameras. This research proposes a unique twelve-step process for analyzing and assessing the security of firmware in Smart IoT-based Camera devices.
EGYPTIAN INFORMATICS JOURNAL
(2023)
Article
Computer Science, Theory & Methods
Emmanuel Oluwatobi Asani, Godsfavour Biety-Nwanju, Abidemi Emmanuel Adeniyi, Salil Bharany, Ashraf Osman Ibrahim, Anas W. Abulfaraj, Wamda Nagmeldin
Summary: This study develops a robust image cryptographic scheme based on Latin Square Matrix and Logistics Map to effectively secure sensitive data. The integration of these algorithms provides a strong and resilient encryption technique. The study addresses issues such as image volume, different sizes, and misplaced pixel positions, making it an effective method for image encryption. Evaluation results show that the algorithm securely protects image data, making it difficult for unauthorized users to decrypt the information, and can be applied in real-time systems.
INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS
(2023)
Article
Computer Science, Theory & Methods
Rajesh Ramnarayan, Rajesh Singh, Anita Gehlot, Kapil Joshi, Ashraf Osman Ibrahim, Anas W. Abulfaraj, Faisal Binzagr, Salil Bharany
Summary: The use of digital twin technologies in the hospitality industry has gained significant attention due to their effectiveness in evaluation, planning, resource utilization, and improving real-time services. These technologies improve production and customer service in the hospitality industry, creating a fast virtual world space for customers.
INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Mohammad Khalid Imam Rahmani
Summary: In the present era, the storage of large volumes of data in databases is common. Finding and sorting the data quickly is crucial for optimal performance. This paper proposes a smart variant of the bubble sort algorithm called Smart Bubble sort, which adapts dynamically and outperforms other sorting algorithms in best-case and average-case scenarios.
CMC-COMPUTERS MATERIALS & CONTINUA
(2022)
