A Resilient Energy-Efficient Framework for Jamming Mitigation in Cluster-Based Wireless Sensor Networks

This paper presents a resilient and energy-efficient framework for jamming mitigation in cluster-based wireless sensor networks (WSNs), addressing a critical vulnerability in hostile or interference-prone environments. The proposed approa ch integrates dynamic cluster reorganization, adaptive MAC-layer behavior, and multipath routing strategies to restore communication capabilities and sustain network functionality under jamming conditions. The framework is evaluated across heterogeneous topologies using Zigbee and Bluetooth Low Energy (BLE); both stacks were validated in a physical testbed with matched jammer and traffic conditions, while simulation was used solely to tune parameters and support sensitivity analyses. Results demonstrate significant improvements in Packet Delivery Ratio, end-to-end delay, energy consumption, and retransmission rate, with BLE showing particularly high resilience when combined with the mitigation mechanism. Furthermore, a comparative analysis of routing protocols including AODV, GAF, and LEACH reveals that hierarchical protocols achieve superior performance when integrated with the proposed method. This framework has broader applicability in mission-critical IoT domains, including environmental monitoring, industrial automation, and healthcare systems. The findings confirm that the framework offers a scalable and protocol-agnostic defense mechanism, with potential applicability in mission-critical and interference-sensitive IoT deployments.

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Publication Details

Journal
Algorithms
Published
2025-09-29
DOI
https://doi.org/10.3390/a18100614
Primary Topic
Security in Wireless Sensor Networks
Type
article
Field-Weighted Citation Impact
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article

A Resilient Energy-Efficient Framework for Jamming Mitigation in Cluster-Based Wireless Sensor Networks

J. Alberto Del Puerto-Flores, Paolo Visconti, A. Lay-Ekuakille, Carolina Del-Valle-Soto et al.
Algorithms
Security in Wireless Sensor Networks
article

A Resilient Energy-Efficient Framework for Jamming Mitigation in Cluster-Based Wireless Sensor Networks

J. Alberto Del Puerto-Flores, Paolo Visconti, A. Lay-Ekuakille, Carolina Del-Valle-Soto, Leonardo Jesus Valdivia
article en

Abstract

This paper presents a resilient and energy-efficient framework for jamming mitigation in cluster-based wireless sensor networks (WSNs), addressing a critical vulnerability in hostile or interference-prone environments. The proposed approa ch integrates dynamic cluster reorganization, adaptive MAC-layer behavior, and multipath routing strategies to restore communication capabilities and sustain network functionality under jamming conditions. The framework is evaluated across heterogeneous topologies using Zigbee and Bluetooth Low Energy (BLE); both stacks were validated in a physical testbed with matched jammer and traffic conditions, while simulation was used solely to tune parameters and support sensitivity analyses. Results demonstrate significant improvements in Packet Delivery Ratio, end-to-end delay, energy consumption, and retransmission rate, with BLE showing particularly high resilience when combined with the mitigation mechanism. Furthermore, a comparative analysis of routing protocols including AODV, GAF, and LEACH reveals that hierarchical protocols achieve superior performance when integrated with the proposed method. This framework has broader applicability in mission-critical IoT domains, including environmental monitoring, industrial automation, and healthcare systems. The findings confirm that the framework offers a scalable and protocol-agnostic defense mechanism, with potential applicability in mission-critical and interference-sensitive IoT deployments.

AlgorithmsVol. 18(10)
University of Salento (IT), Innovation Engineering (Italy) (IT), Universidad Panamericana (MX)
Openalex Percentile: Top 69%
Security in Wireless Sensor Networks
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A Resilient Energy-Efficient Framework for Jamming Mitigation in Cluster-Based Wireless Sensor Networks — J. Alberto Del Puerto-Flores, Paolo Visconti, et al. · Algorithms (2025) | TGRS Research Map | TGRS