.png){kind=icon}
.png){kind=icon}
Return
EESCM: Energy Efficient and Secure Cluster Management in IoT networks through convex-hull driven SSA-WWOA algorithms
.png){kind=icon}
PRE
AI
R
D
A
R
DOI：10.1007/s10586-026-06073-1.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In dynamic IoT networks, it is challenging to minimize energy consumption while preserving security. In response, this work Energy Efficient and Secure Cluster Management algorithm, integrates Salp Swarm Algorithm (SSA) with Wagging-based Whale Optimization Algorithm (WWOA) in conjunction with Convex-Hull algorithm. EESCM uses a hierarchical approach whereby SSA investigates possible cluster head candidates, WWOA chooses optimal cluster heads based on the parameters like residual energy, node degree, intra-cluster distance, and trust. It also ensures that the selected nodes provide maximum coverage of the network nodes. Cluster Heads selection is done based on the average of each of these parameters and their standard deviation. Convex Hull repositions cluster heads and Base Station, reducing transmission distance and communication delay in the network. With 20.7% less dead nodes, 14.2% higher Packet Delivery Ratio, 4.8% increased throughput, and 17.2% more residual energy, simulations show notable advancements of EESCM over state-of-the-art-algorithms.
Keywords:
Energy efficiency
Security
Clustering
IoT networks
Convex-hull
Salp swarm algorithm
Wagging whale optimization algorithm
Journal
C
IF:
0
Papers:
691
Citations:
1
Organization
Cited Papers