Improving power allocation and installation in WSN using novel nature-inspired optimization for cyber security applications

Wireless Sensor Network (WSN) installation and power allocation optimization for cyber security purposes are difficult tasks which include a well-thought-out method that strikes a balance between goals like energy efficiency, connectivity and cyber threat resistance while improving overall system performance and cyber security. A novel Multi-Task Walrus Optimization (MTWO) technique is offered in this study. The Installation and Power Allocation Problem (IPAP) with several jobs is established in this research. The suggested MTWO is used to split the IPAP into numerous scalar components, which are consequently grouped and treated by their desired goals. We evaluate the proposed MTWO approach using simulations and show that it works well in practice. The findings demonstrate that power distribution and installation for cyber security activities on WSNs can be improved by the MTWO. The superiority of the problem specific MTWO over the MOGA has been demonstrated by simulation outcome in several network cases, offering a wide range of excellent network designs to aid in the decision-maker selection.