Answers are grounded in this paper and cite their sources.
Demonstrates energy-efficient data aggregation in heterogeneous wireless sensor networks, suggesting improved network performance.
The paper presents a broadly elaborated, secure, and energy-efficient data aggregation scheme of the heterogeneous wireless sensor networks (HWSNs). This is motivated by two consistent shortcomings of existing work: (i) clustering-based routing algorithms like LEACH, SEP, and FSEP are inadequate on balancing the energy usage when there is a disparity in the node capabilities, and (ii) most ECC-based security systems create too much computation overhead to extend network lifetime. To satisfy such gaps, the given framework integrates the Spider Monkey Optimization Routing Protocol (SMORP) with a compact cryptographic implementer including the Improved Elliptic Curve Cryptography (IECC) and El Gamal Digital Signature (ELGDS) scheme. SMORP gives maximum consideration to cluster forming and multi hop forwarding and the IECC-ELGDS module that provides all the above data confidentiality, authentication and data integrity at a lower cost of computation. As compared to the previous strategies, the combination of routing optimization and elliptic-curve-based secure aggregation facilitates energy efficiency and high-security assurance in the resource- constrained nodes. MATLAB models show that the offered framework can boost network life up to 27 percent, residual energy up to 32 percent, and get a 96 percent packet-delivery ratio relative to LEACH, SEP, and FSEP. Moreover, the IECC-ELGDS module will need less time in encryption/decryption by 22-35 percent in comparison with ECC-HE, IEKC and ECDH-RSA. These findings support the idea that the SMORP-IECC-ELGDS is a viable and fast architecture to secure aggregation in the real-life HWSN deployment.
No takes yet. Share an insight, caveat, or question.
Abbod et al. (2026) studied this question.
Synapse has enriched 8 closely related papers on similar clinical questions. Consider them for comparative context: