A Novel Path Recovery Framework to Accurate Data Transmission in Web Sensor Networks
Keywords:
Wireless Sensor Networks, Optimal Path, Node Interference, Path RecoveryAbstract
Wireless Sensor Networks (WSNs) represent a groundbreaking paradigm in the field of distributed sensing and data acquisition. These networks consist of numerous tiny, battery-powered sensor nodes equipped with sensors for measuring physical or environmental parameters. The nodes communicate wirelessly to form a self-organizing and ad-hoc network, enabling real-time data collection and transmission. WSNs find applications in various domains, encompassing smart cities, healthcare, industrial automation, and environmental monitoring. They offer advantages such as flexibility, scalability, and cost-effectiveness. This abstract explores the fundamental principles, challenges, and applications of WSNs, highlighting their crucial role in enabling data-driven decision-making and enhancing our understanding of the physical. In most cases, the network is organized into small clusters to make affordable sensors that collect valuable data from their surroundings. The Cluster Head (CH) node takes responsibility for receiving data from the sensor node forward to Base Station (BS). This existing model uses more energy and causes network data collisions. To solve the issues in traditional networks Harish Goud et al proposed Energy Optimization in Path Arbitrary Wireless Sensor Network. The PAWSN model avoids the traditional CH selection and data transmission to CH. In PAWSN data transmission through the optimal path selection, achieved better performance. The PAWSN network senses a huge amount of data from source to destination and its leads bottleneck the network at a single node. The network bottleneck is called path failure in WSN. To deal with the constraints of previous research, in this paper proposed a framework called Novel Path Recovery in WSN (NPR- WSN). The implementation of the suggested model by making using NS2 simulator. The scientific results demonstrate that the suggested NPR-WSN structure improves data performance transmission in WSN. The PDR, throughput, latency, and energy metrics are used to gauge performance.
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