Kinetic Gas Molecule Optimization based Cluster Head Selection Algorithm for minimizing the Energy Consumption in WSN

As the amount of low-cost and low-power sensor nodes increases, so does the size of a wireless sensor network (WSN). Using self-organization, the sensor nodes all connect to one another to form a wireless network. Sensor gadgets are thought to be extremely difficult to recharge in unfavourable conditions. Moreover, network longevity, coverage area, scheduling, and data aggregation are the major issues of WSNs. Furthermore, the ability to extend the life of the network, as well as the dependability and scalability of sensor nodes' data transmissions, demonstrate the success of data aggregation. As a result, clustering methods are thought to be ideal for making the most efficient use of resources while also requiring less energy. All sensor nodes in a cluster communicate with each other via a cluster head (CH) node. Any clustering algorithm's primary responsibility in these situations is to select the ideal CH for solving the variety of limitations, such as minimising energy consumption and delay. Kinetic Gas Molecule Optimization (KGMO) is used in this paper to create a new model for selecting CH to improve network lifetime and energy. Gas molecule agents move through a search space in pursuit of an optimal solution while considering characteristics like energy, distance, and delay as objective functions. On average, the KGMO algorithm results in a 20% increase in network life expectancy and a 19.84% increase in energy stability compared to the traditional technique Bacterial Foraging Optimization Algorithm (BFO)

A collision aware priority level medium access control protocol for underwater acoustic sensor networks

The Underwater Acoustic Sensor Network (UASN) plays a significant role in many application areas like surveillance, security, commercial and industrial applications. In UASN routing, propagation delay and collision are perennial problems due to data transfers from various sensor nodes to the Sink Node (SN) at the same time. In this paper, we propose a Collision Aware Priority Level mechanism based on Medium Access Control protocol (CAPL-MAC) for transferring data from the Sensor Head (SH) to the SN. In the proposed protocol, we use Parallel Competition Scheme (PCS) for high channel utilization and energy saving of battery. In each Competition Cycle (CC), the data packet produced by each SH in a different time slot can join in CC for data packet transmission in parallel with high channel utilization. In CAPL-MAC, each SH is assigned with a different Priority Level Number (PLN) during every CC. Instead of broadcasting, each SH sends its respective PLN to each SH with the help of the nearest SH to save battery energy. Based on the highest PLN, each SH communicates with SN without collision, and it will also reduce propagation delay as well as improve timing efficiency. Finally, Quality of Service is also improved. We adopt the single-layer approach with the handshaking protocol for communication. We carried out the simulation utilizing Aqua-Sim Network Simulator 2. The simulation results showed that the proposed CAPL-MAC protocol achieved the earlier stated performance rather than by existing protocols such as Competitive Transmission-MAC and Channel Aware Aloh