Article Open Access

Investigating the Energy Cost for n Wireless Sensor Network using IoT by Implementing RMP Algorithm

Kishore Kumar K, G. Srinivasulu

Abstract


Internet of Things (IoT) sensor networks frequently see energy savings since the nodes in the network are powered by their own finite batteries. While data processing uses a lot less energy than data transmission in IoT sensor nodes is expensive & energy-intensive. Over the last few years, wireless sensor systems based on IoT has witnessed an evolutionary breakthrough across several industries  various sectors. The Internet of Things, or IoT, is a network that allows physical items, machinery, sensors, and other devices to communicate with one another without the need for human intervention. The WSN (Wireless Sensor Network) is a central component of the IoT, which has proliferated into several different applications in real-time. Nowadays, the critical and non-critical applications of the IoT and WSNs affect nearly every part of our daily life. WSN nodes are usually small, battery-powered machines. Therefore, Energy-efficient data aggregation techniques that prolong the network's lifespan are crucial. Reducing data transmission is the primary goal of many energy-saving techniques and concepts. As a result, significant energy savings can be achieved in IoT sensor networks by reducing data transfers. The proliferation of IoT-based Wireless Sensor Network has triggered a paradigm shift in the business, necessitating the use of dependable and efficient routing techniques. A compression-based data reduction (CBDR) method that operates at the level of IoT sensor nodes was proposed in this study. To recover the data at the sink or BS end, we suggest using a Randomised Matching Pursuit algorithm. Additionally, beneficial is the use of CLH and relay routing.


Keywords


Internet of Things, Energy Saving, Compression Based Data Reduction, Randomized Matched Pursuit, Cluster Head

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DOI: https://doi.org/10.52088/ijesty.v5i4.1243

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