Haydar Abdulameer Marhoon^1,2,*, Rafid Sagban^3,4, Atheer Y. Oudah^1,5, Saadaldeen Rashid Ahmed^6,7

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 4181-4218, 2025, DOI:10.32604/cmc.2025.058822 - 06 March 2025

Abstract In order to address the critical security challenges inherent to Wireless Sensor Networks (WSNs), this paper presents a groundbreaking barrier-based machine learning technique. Vital applications like military operations, healthcare monitoring, and environmental surveillance increasingly deploy WSNs, recognizing the critical importance of effective intrusion detection in protecting sensitive data and maintaining operational integrity. The proposed method innovatively partitions the network into logical segments or virtual barriers, allowing for targeted monitoring and data collection that aligns with specific traffic patterns. This approach not only improves the diversit. There are more types of data in the training set,… More >

Ramadan Abdul-Rashid¹, Mohd Amiruddin Abd Rahman^1,*, Kar Tim Chan¹, Arun Kumar Sangaiah^2,3,4

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 2585-2616, 2025, DOI:10.32604/cmes.2025.060548 - 03 March 2025

Abstract This study proposes a novel time-synchronization protocol inspired by stochastic gradient algorithms. The clock model of each network node in this synchronizer is configured as a generic adaptive filter where different stochastic gradient algorithms can be adopted for adaptive clock frequency adjustments. The study analyzes the pairwise synchronization behavior of the protocol and proves the generalized convergence of the synchronization error and clock frequency. A novel closed-form expression is also derived for a generalized asymptotic error variance steady state. Steady and convergence analyses are then presented for the synchronization, with frequency adaptations done using least More >

Soyoung Joo^#, So-Hyun Park^#, Hye-Yeon Shim, Ye-Sol Oh, Il-Gu Lee^*

CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 2475-2494, 2025, DOI:10.32604/cmc.2025.058963 - 17 February 2025

Abstract As the density of wireless networks increases globally, the vulnerability of overlapped dense wireless communications to interference by hidden nodes and denial-of-service (DoS) attacks is becoming more apparent. There exists a gap in research on the detection and response to attacks on Medium Access Control (MAC) mechanisms themselves, which would lead to service outages between nodes. Classifying exploitation and deceptive jamming attacks on control mechanisms is particularly challengingdue to their resemblance to normal heavy communication patterns. Accordingly, this paper proposes a machine learning-based selective attack mitigation model that detects DoS attacks on wireless networks by More >

Shumin Li¹, Qifang Luo^1,2,*, Yongquan Zhou^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 1955-1994, 2025, DOI:10.32604/cmes.2025.059738 - 27 January 2025

Abstract Wireless sensor network deployment optimization is a classic NP-hard problem and a popular topic in academic research. However, the current research on wireless sensor network deployment problems uses overly simplistic models, and there is a significant gap between the research results and actual wireless sensor networks. Some scholars have now modeled data fusion networks to make them more suitable for practical applications. This paper will explore the deployment problem of a stochastic data fusion wireless sensor network (SDFWSN), a model that reflects the randomness of environmental monitoring and uses data fusion techniques widely used in… More >

Gajjala Savithri^1,2, N. Raghavendra Sai^1,*

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2547-2569, 2024, DOI:10.32604/cmc.2024.055827 - 18 November 2024

Abstract In the world of wireless sensor networks (WSNs), optimizing performance and extending network lifetime are critical goals. In this paper, we propose a new model called DTLR-Net (Deep Temporal LSTM Regression Network) that employs long-short-term memory and is effective for long-term dependencies. Mobile sinks can move in arbitrary patterns, so the model employs long short-term memory (LSTM) networks to handle such movements. The parameters were initialized iteratively, and each node updated its position, mobility level, and other important metrics at each turn, with key measurements including active or inactive node ratio, energy consumption per cycle,… More >

Adisa Hasković Džubur^*, Samir Čaušević, Belma Memić, Muhamed Begović, Elma Avdagić-Golub, Alem Čolaković

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1059-1084, 2024, DOI:10.32604/cmc.2024.055386 - 15 October 2024

Abstract Wireless sensor networks (WSNs) are characterized by heterogeneous traffic types (audio, video, data) and diverse application traffic requirements. This paper introduces three traffic classes following the defined model of heterogeneous traffic differentiation in WSNs. The requirements for each class regarding sensitivity to QoS (Quality of Service) parameters, such as loss, delay, and jitter, are described. These classes encompass real-time and delay-tolerant traffic. Given that QoS evaluation is a multi-criteria decision-making problem, we employed the AHP (Analytical Hierarchy Process) method for multi-criteria optimization. As a result of this approach, we derived weight values for different traffic… More >

Chandraumakantham Om Kumar^1,*, Sudhakaran Gajendran², Suguna Marappan¹, Mohammed Zakariah³, Abdulaziz S. Almazyad⁴

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 471-501, 2024, DOI:10.32604/cmc.2024.054966 - 15 October 2024

Abstract The security of the wireless sensor network-Internet of Things (WSN-IoT) network is more challenging due to its randomness and self-organized nature. Intrusion detection is one of the key methodologies utilized to ensure the security of the network. Conventional intrusion detection mechanisms have issues such as higher misclassification rates, increased model complexity, insignificant feature extraction, increased training time, increased run time complexity, computation overhead, failure to identify new attacks, increased energy consumption, and a variety of other factors that limit the performance of the intrusion system model. In this research a security framework for WSN-IoT, through… More >

Muhammad Aamer Ejaz^1,*, Kamalrulnizam Abu Bakar¹, Ismail Fauzi Bin Isnin¹, Babangida Isyaku^1,2,*, Taiseer Abdalla Elfadil Eisa³, Abdelzahir Abdelmaboud⁴, Asma Abbas Hassan Elnour³

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1511-1528, 2024, DOI:10.32604/cmc.2024.054938 - 15 October 2024

Abstract Localization is crucial in wireless sensor networks for various applications, such as tracking objects in outdoor environments where GPS (Global Positioning System) or prior installed infrastructure is unavailable. However, traditional techniques involve many anchor nodes, increasing costs and reducing accuracy. Existing solutions do not address the selection of appropriate anchor nodes and selecting localized nodes as assistant anchor nodes for the localization process, which is a critical element in the localization process. Furthermore, an inaccurate average hop distance significantly affects localization accuracy. We propose an improved DV-Hop algorithm based on anchor sets (AS-IDV-Hop) to improve… More >

Wen-Tsai Sung¹, Indra Griha Tofik Isa^1,2, Sung-Jung Hsiao^3,*

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 3733-3759, 2024, DOI:10.32604/cmc.2024.053634 - 12 September 2024

Abstract Mango fruit is one of the main fruit commodities that contributes to Taiwan’s income. The implementation of technology is an alternative to increasing the quality and quantity of mango plantation product productivity. In this study, a Wireless Sensor Networks (“WSNs”)-based intelligent mango plantation monitoring system will be developed that implements deep reinforcement learning (DRL) technology in carrying out prediction tasks based on three classifications: “optimal,” “sub-optimal,” or “not-optimal” conditions based on three parameters including humidity, temperature, and soil moisture. The key idea is how to provide a precise decision-making mechanism in the real-time monitoring system.… More >

Syed Kamran Haider^1,2, Abbas Ahmed², Noman Mujeeb Khan², Ali Nauman^3,*, Sung Won Kim^3,*

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4085-4110, 2024, DOI:10.32604/cmc.2024.052997 - 12 September 2024

Abstract In recent advancements within wireless sensor networks (WSN), the deployment of unmanned aerial vehicles (UAVs) has emerged as a groundbreaking strategy for enhancing routing efficiency and overall network functionality. This research introduces a sophisticated framework, driven by computational intelligence, that merges clustering techniques with UAV mobility to refine routing strategies in WSNs. The proposed approach divides the sensor field into distinct sectors and implements a novel weighting system for the selection of cluster heads (CHs). This system is primarily aimed at reducing energy consumption through meticulously planned routing and path determination. Employing a greedy algorithm More >