ARCHITECTURAL AND SECURITY ASPECTS OF WIRELESS SENSOR NETWORKS: A COMPREHENSIVE REVIEW
Abstract
Wireless Sensor Networks (WSNs) have emerged as a pivotal technology for diverse applications, enabling ubiquitous data collection and environmental monitoring. Comprising spatially distributed autonomous devices, WSNs present unique challenges in terms of their architectural design, power management, and inherent security vulnerabilities. This review synthesizes extant literature to explore the fundamental system architectures, critical design considerations for extending network lifetime, and essential security protocols integral to robust WSN deployment and operation. By examining established research, this article aims to provide a comprehensive understanding of the foundational principles and ongoing challenges in engineering reliable and secure wireless sensor systems, informing future research and practical implementations in various domains from environmental monitoring to emergency response.
Keywords
References
Most read articles by the same author(s)
- Prof. Karan M. Bhatia, Mehul A. Rajput, HARNESSING AI FOR PROACTIVE PUBLIC RELATIONS: A FRAMEWORK FOR PREDICTING AND CAPITALIZING ON SOCIAL MEDIA TRENDS , International Journal of Intelligent Data and Machine Learning: Vol. 2 No. 10 (2025): Volume 02 Issue 10
- Daniel K. Hofmann, Designing Low-Latency Web APIs for High-Transaction Distributed Systems: Architectural Strategies, Performance Trade-Offs, and Emerging Paradigms , International Journal of Intelligent Data and Machine Learning: Vol. 3 No. 01 (2026): Volume 03 Issue 01
- Dr. Tashi Wangchuk, Karma Lhendup, Data-Driven Model Supporting Defect Analysis through Vision Techniques in Press-Formed Vehicle Components , International Journal of Intelligent Data and Machine Learning: Vol. 3 No. 04 (2026): Volume 03 Issue 04
- Mr. Himanshu Barhaiya, A Comprehensive Review of Machine Learning Techniques for Retail Supply Chain Optimizations , International Journal of Intelligent Data and Machine Learning: Vol. 3 No. 07 (2026): Volume 03 Issue 07
- Dr. Tanay Deshpande, Dr. Kavita Sharma, ADVANCING ARTIFICIAL INTELLIGENCE: AN IN-DEPTH LOOK AT MACHINE LEARNING AND DEEP LEARNING ARCHITECTURES, METHODOLOGIES, APPLICATIONS, AND FUTURE TRENDS , International Journal of Intelligent Data and Machine Learning: Vol. 2 No. 01 (2025): Volume 02 Issue 01
- Dr. Lucas Vermeulen, Sophie De Smet, Dr. Thomas Dubois, Integrated Temporal Analytics and AI-Based Approaches for Predicting Culinary Ingredient Consumption Patterns: Evidence from Thai Markets , International Journal of Intelligent Data and Machine Learning: Vol. 3 No. 04 (2026): Volume 03 Issue 04
- Dr. Isabella MĂŒller, Samuel Moyo, UNLOCKING SYNERGIES: A FRAMEWORK FOR INTEGRATING ARTIFICIAL INTELLIGENCE AND BLOCKCHAIN TECHNOLOGIES , International Journal of Intelligent Data and Machine Learning: Vol. 2 No. 07 (2025): Volume 02 Issue 07
- Dr. Elias R. Hoffmann, Predictive Behavioral Cybersecurity for Smart Healthcare and Mobile Ecosystems: An Ensemble Machine Learning Framework for Dynamic Malware Intelligence , International Journal of Intelligent Data and Machine Learning: Vol. 3 No. 01 (2026): Volume 03 Issue 01
- Dr. Hannah Brown, Ahmed Al-Farsi, BRIDGING DEEP LEARNING AND ADAPTIVE SYSTEMS: A PERFORMANCE STUDY ON CIFAR-10 IMAGE CLASSIFICATION , International Journal of Intelligent Data and Machine Learning: Vol. 2 No. 03 (2025): Volume 02 Issue 03
- Prof. Elena M. Petrova, A Python Framework for Causal Discovery in Non-Gaussian Linear Models: The PyCD-LiNGAM Library , International Journal of Intelligent Data and Machine Learning: Vol. 2 No. 08 (2025): Volume 02 Issue 08
Similar Articles
- Dr. Eleanor Vance, Dr. Kenji Sato, Architectural Frameworks and Security Challenges in Wireless Sensor Networks: A Critical Review , International Journal of Intelligent Data and Machine Learning: Vol. 2 No. 10 (2025): Volume 02 Issue 10
- Dr. Alejandro Moreno, Architectural Paradigms, Protocol Dynamics, And Security Implications In Wireless Sensor Networks: An Integrative And Critical Research Synthesis , International Journal of Intelligent Data and Machine Learning: Vol. 3 No. 01 (2026): Volume 03 Issue 01
- Elias J. Vance, Clara M. Soto, High-Frequency Data Driven Network Learning for Systemic Risk Analysis in Financial Markets , International Journal of Intelligent Data and Machine Learning: Vol. 2 No. 09 (2025): Volume 02 Issue 09
- Isabella Rossi, Elena Petrova, LEVERAGING QUANTUM CONVOLUTIONAL LAYERS FOR ENHANCED IMAGE CLASSIFICATION: AN EXAMINATION OF QUANVOLUTIONAL NEURAL NETWORK CHARACTERISTICS , International Journal of Intelligent Data and Machine Learning: Vol. 2 No. 06 (2025): Volume 02 Issue 06
- Yuki Nakamura, Isabella Romano, HYBRID DEEP LEARNING FOR TEXT CLASSIFICATION: INTEGRATING BIDIRECTIONAL GATED RECURRENT UNITS WITH CONVOLUTIONAL NEURAL NETWORKS , International Journal of Intelligent Data and Machine Learning: Vol. 2 No. 04 (2025): Volume 02 Issue 04
- Dr. Elias R. Hoffmann, Predictive Behavioral Cybersecurity for Smart Healthcare and Mobile Ecosystems: An Ensemble Machine Learning Framework for Dynamic Malware Intelligence , International Journal of Intelligent Data and Machine Learning: Vol. 3 No. 01 (2026): Volume 03 Issue 01
- Dr. Oliver Henry Mitchell, A Comprehensive Framework for Intelligent Data Analytics in Modern Intelligent Systems: Design, Methods, and Applications , International Journal of Intelligent Data and Machine Learning: Vol. 3 No. 05 (2026): Volume 03 Issue 05
- Dr. James William Carter, Dr. Emily Rose Thompson, A Hybrid QuantumâClassical Deep Learning Approach for Image Recognition: Performance Analysis of Quanvolution-Based Convolutional Models , International Journal of Intelligent Data and Machine Learning: Vol. 3 No. 06 (2026): Volume 03 Issue 06
- Ripunjay Kumar, Sentiment Analysis of Social Network Comments for Identifying Opinion Leaders Using Machine Learning , International Journal of Intelligent Data and Machine Learning: Vol. 3 No. 06 (2026): Volume 03 Issue 06
- Mateo Laurent Dufour, Architecting Secure and Scalable Production Machine Learning Systems: Integrating Model Management, High Performance Computing, and Cloud Native Infrastructure , International Journal of Intelligent Data and Machine Learning: Vol. 3 No. 03 (2026): Volume 03 Issue 03
You may also start an advanced similarity search for this article.