Affiliations:
School of Information Engineering, Hangzhou Dianzi University, Hangzhou, Zhejiang, China
Correspondence:
[*]
Corresponding author. Xiaopeng Wu, School of Information Engineering, Hangzhou Dianzi University, Hangzhou, Zhejiang, 311305, China. E-mail: [email protected].
Abstract: In wireless-sensing networks (WSNs), the energy economy has lately emerged as the main problem. Since sensor networks run on batteries, they eventually run out of power. To increase the packet transmission ratio for sensing devices, it becomes more difficult to enhance data loss in an energy-efficient manner. In WSNs, the mobile drain causes high network energy usage and data delay. This paper suggests an Improved Ant Colony Clustering-Based Data Transmission Algorithm (EACODT) that first develops the network nodes’ energy density function before allocating sensing nodes with higher residual energy as cluster leaders using the energy density function. The EACODT is thoroughly modeled for different WSN situations with variable numbers of sensing nodes and CHs, and the findings are contrasted with some recently developed meta-heuristic algorithms. As a consequence, it is discovered that EACODT gets 34% of energy usage, 98.8% of network lifespan, 95% of packet delivery ratio, 854 kbps of transmission, and a 98% convergence rate.
Keywords: Wireless sensor networks, optimization, energy efficiency, packet delivery, data transmission
