Architectural Frameworks and Security Challenges in Wireless Sensor Networks: A Critical Review
Abstract
Background: Wireless Sensor Networks (WSNs) are integral to modern data collection, enabling real-time monitoring across diverse fields such as environmental tracking, healthcare, and smart infrastructure. These networks consist of resource-constrained nodes deployed to collect and transmit data, offering unprecedented opportunities for ubiquitous sensing. However, their unique characteristics present significant architectural and security challenges that must be addressed to ensure reliable and widespread adoption.
Methods: This comprehensive review synthesizes and critically analyzes existing literature on WSNs, focusing on their core architectural design and security vulnerabilities. It examines the fundamental components of sensor nodes, explores strategies for enhancing network lifetime through energy-efficient protocols and hardware, and discusses the critical need for reliable data transport. Furthermore, the review identifies key security threats and evaluates specialized security protocols designed to protect these resource-limited systems. The analysis is supported by a wide range of real-world application examples to illustrate the practical implications of these design and security considerations.
Results: The review highlights that WSN architecture is fundamentally defined by the need for low-power, cost-effective operation, with energy efficiency being the most significant constraint [2, 24]. Solutions like power-aware routing and dynamic reconfiguration are crucial for extending network lifetime [17]. Concurrently, the inherent vulnerabilities of WSNs to attacks necessitate specialized security protocols, such as SPINS, to ensure data confidentiality and integrity without exhausting limited resources [8, 11]. The article demonstrates that achieving a balance between robust security, power optimization, and adaptability is key to the long-term resilience of WSNs.
Conclusion: Advances in hardware platforms, algorithmic efficiency, and secure communication protocols are essential to unlock the full potential of WSNs. Future research directions should focus on integrating AI and machine learning for self-healing, autonomous networks that can optimize energy use and enhance security at scale. This holistic approach is vital for the successful deployment of reliable, resilient, and secure WSNs .
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