Improving the Power Consumption of Sensor Networks using Optimization Technique for Sleep Scheduling Mechanism

Wireless sensor networks (WSNs) are used to study data gathering, communication, and physical environments because of their large sensor nodes. The data collected by the sensor nodes are sent to the base station, where it is stored and processed remotely. In wireless sensor networks, the high node density will cause redundancy power consumption and transmission collision. First, the power sleep scheduling protocol (PSSP) for wireless sensor networks is proposed to solve the aforementioned problems. This mechanism will arrange devices into an operational or sleeping mode to efficiently decrease energy usage. To balance energy consumption, all endpoints are divided into some cluster centers, and then the ideal competition radius is determined. Second, a fuzzy matrix may be created to evaluate the level of similarities utilizing the data obtained by the cluster members, as well as a resemblance characteristic based on the hypothesis that can be defended to classify the sensor nodes. The redundant nodes will then be selected to enter sleep mode inside the subsequent round to protect the integrity of the network’s data. Results from simulations and actual use show that our method can provide superior cluster allocation and network energy efficiency improvements while preserving data accuracy.