Aug 2026· International Journal of Wireless and Microwave Technologies· Vol 16, pp. 65-79· 0 citations
TL;DR
A new framework called OptiBC-WSN is proposed that combines Particle Swarm Optimisation (PSO) clustering, AES-128 encryption, Proof of Authority (PoA) blockchain and Random Forest-based Intrusion Detection System (IDS) to improve the scalability and security of IoT.
Abstract
Wireless Sensor Networks (WSNs) are the core of Internet of Things (IoT) applications as they enable energy-efficient and scalable real-time data acquisition. However, WSN-based IoT systems have been facing great challenges in achieving energy efficiency, security and scalability especially in applications like smart agriculture. To tackle these problems, this study proposes a new framework called OptiBC-WSN that combines Particle Swarm Optimisation (PSO) clustering, AES-128 encryption, Proof of Authority (PoA) blockchain and Random Forest-based Intrusion Detection System (IDS). We have implemented PSO for energy efficient clustering, PoA for trust management and a Random Forest based IDS for attack detection on Intel Berkeley and GreenOrbs datasets. OptiBC-WSN consumes 0.25 mJ/node energy, LEACH consumes 5 mJ/node and K-Means+Bee consumes 0.3 mJ/node. It also achieves a breach rate of 0.13% vs. 2% for LEACH and 0.2% for K-Means+Bee and scales to 10,000 nodes with 15,950 bytes overhead (vs. 20,000 bytes for LEACH). Its IDS has 90% accuracy to DDoS, Sybil and Jamming attacks with fairness index 0.92. We perform scale-up tests from 100 to 10K nodes with GreenOrbs dataset and synthetic topology generation, and validate core energy and security metrics with the Intel Berkeley dataset (54 nodes). In smart agriculture it cuts irrigation by 15% and CO2 emissions by 60 kg/1,000 nodes/year. Future work will explore the use of blockchain sharding and adaptive IDS to improve the scalability and security of IoT.
Wireless Sensor Networks (WSNs) use resource-constrained sensor nodes to continuously monitor ambient conditions and serve as data sinks for various Internet of Things (IoT) applications. However, maximizing Energy Efficiency (EE) while maintaining reliable data delivery remains a significant challenge. Existing clustering and routing algorithms struggle with issues such as uneven energy consumption, premature node failures, and poor network performance. Additionally, many existing metaheuristic schemes are not adaptable to dynamic network environments, which leads to ineffective energy management. To address the above issues and enhance the energy efficiency of IoT-based WSN, this research introduced a novel Energy-Aware Cluster-Optimized Intelligent Routing (EACO-IR) protocol. The EACO-IR protocol performs in three stages: stable cluster formation, Cluster Head (CH) selection, and energy-aware route finding. At first, stable clusters are formed using the Hybrid Fuzzy–Density Adaptive Kronecker Clustering (HF-DAC) algorithm. Subsequently, CHs are optimally selected using the Mutation-Enhanced Armadillo–Devil Optimization (MEADO) based on a multi-objective function for the Base Station (BS). Finally, the Multi-level Energy-Aware Attention Transformer- Based Reinforcement Learning is introduced to create intra and inter-cluster data travel ways to minimize communication overhead from SNs to the BS. Experimental results show that the proposed protocol yields an average throughput of 4 Mbps, an average Packet Delivery Ratio (PDR) of 98.71%, and an end-to-end latency of 0.06 seconds, outperforming current state-of-the-art clustering and routing algorithms. Ultimately, this framework establishes a highly adaptable template for deploying self-optimizing, long-lasting IoT architectures capable of supporting real-time data streaming without premature network degradation.
P. Kumbhar, A. Naik· International Journal of Ele...· 0 citations
An Energy-Efficient IoT Sensor Network Framework that integrates intelligent energy harvesting techniques, adaptive sleep scheduling, edge computing, and Artificial Intelligence (AI)-based routing algorithms to optimize power consumption and extend network longevity is proposed.
Dabbeta Ganapathi Dabbeta Ganapathi, Halavath Vijaya Halavath Vijaya, P. K. P Kavitha· International Journal of Sci...· 0 citations
The core research goal of this paper is to optimize dynamic routing protocols to improve the performance of the classic LEACH protocol in heterogeneous WSNs through a real-time adaptive scheme, which relies on two core methods: a cluster head selection mechanism based on the residual energy criterion, and a priority hop count strategy.
Vishwajit K. Barbudhe, Shruti Dixit· International journal of com...· 0 citations
Wireless Sensor Networks (WSNs) are increasingly employed in various applications, that require efficient, energy-saving and secure transmitting mechanisms. Clustering is a key technique in WSN to enhance scalability, reduce energy consumption, and manage communication. However, tradi-tional clustering algorithms often lack adaptability to alterable wireless environments. This study presents an optimized secure clustering scheme for Wireless Sensor Networks that employs a fuzzy inference system to perform adaptive and secure cluster head selection. The proposed scheme is designed for WSN with a static topology, where sensor nodes remain fixed after de-ployment. This assumption matches Internet of Medical Things (IoMT) applications, such as patient monitoring systems and smart hospital infrastructure, where sensors operate in fixed locations. The proposed fuzzy inference system evaluates parameters of sensor nodes to select optimal cluster heads while mitigating malicious node participation. Next, a genetic algorithm was applied to optimize the parameters of the fuzzy inference system, including the membership function shapes and rule base indices, in order to enhance the accuracy of the proposed clustering scheme. MATLAB simulations demonstrate that the proposed scheme effectively identifies compromised sensor nodes and prevents them from assuming the cluster head role. The security validation confirms that the scheme achieves a high detection rate against internal attacks while extending overall network lifetime and maintaining the low latency. This study provides a feasible solution for secure and intelligent clustering in resource- constrained WSN.
Vincent Karovič, Olena O. Semenova, M. Prytula et al.· Infocommunications journal· 0 citations
Internet of Things (IoT) is a technology link to the objects that interact between themselves to provide better services for users in an unbelievable way and makes everything easy. The applications of IOT include healthcare monitoring, smart city, smart retail, smart home and agriculture. Wireless Sensor Networks (WSN) plays a vital role in IoT as it includes data processing, connectivity, sensing, and data acquiring. A wireless, self-configuring, and multi-hop network is called a mobile ad-hoc network (MANET). The node of the MANET acts as a router and is always connected to WSN. Hence, the interface between IoT and MANET opens new ways for service facilities in smart environments. The main challenging issue of MANET-IOT is energy balancing over nodes. The IoT technology works on various wireless sensors and so the main aim of MANET protocols is to find the shortest path to be more efficient. Many researchers have designed energy-efficient routing protocols for improving network lifetime and due to the lack of composite solution over MANET-IoT networks, we plan to review the novel energy-efficient routing protocols that can provide a composite solution for routing over the MANET-IoT networks. This survey reviews the different types of routing protocols based on its topological structure, and energy efficiency characteristics. The performance metrics used to evaluate the efficiency of the routing protocols are also presented.
Mohammed Qayyum, Mohammed Abdul Bari· International journal of com...· 0 citations
Wireless Sensor Networks (WSNs) are increasingly deployed in resource-constrained and hostile environments for critical applications such as environmental monitoring, industrial automation, and structural auditing. However, their real-world efficacy is severely limited by battery energy constraints and high vulnerability to routing-layer security threats. Conventional cryptographic solutions incur excessive computational overhead, while standard energy-efficient routing protocols often neglect security. To resolve this trade-off, this paper proposes an integrated, multi-tier optimization framework combining three novel algorithms: Proficient Secure Cluster Head Selection (PSCH), Total Path Trust Assessment Routing (TPTAR), and Energy-Proficient, Secure, and Trust-Based Shortest Path Optimized Routing (EST-SPOR). The proposed architecture utilizes fuzzy logic for cluster-head selection, a dynamic trust evaluation model combining direct and reference trust metrics, and an optimized shortest-path routing mechanism based on Ant Colony Optimization (ACO) principles. Simulation analyses conducted in NS-3 demonstrate that the framework achieves superior performance in terms of Packet Delivery Ratio (PDR), energy conservation, end-to-end latency, and resilience against malicious routing attacks compared to existing baseline protocols.
Jitendra Kumar, Debasis Mandal· International journal of res...· 0 citations