Abstract
The lifetime of a node in wireless sensor networks (WSN) is directly responsible for the longevity of the wireless network. The routing of packets is the most energy-consuming activity for a sensor node. Thus, finding an energy-efficient routing strategy for transmission of packets becomes of utmost importance. The opportunistic routing (OR) protocol is one of the new routing protocol that promises reliability and energy efficiency during transmission of packets in wireless sensor networks (WSN). In this paper, we propose an intelligent opportunistic routing protocol (IOP) using a machine learning technique, to select a relay node from the list of potential forwarder nodes to achieve energy efficiency and reliability in the network. The proposed approach might have applications including e-healthcare services. As the proposed method might achieve reliability in the network because it can connect several healthcare network devices in a better way and good healthcare services might be offered. In addition to this, the proposed method saves energy, therefore, it helps the remote patient to connect with healthcare services for a longer duration with the integration of IoT services.
Highlights
wireless sensor networks (WSN) is a network of spatially dispersed tiny sensor nodes responsible for the collection of data from the physical environment
As it is clear from the literature that energy consumption of a sensor node had a considerable impact on the lifetime and quality of the wireless sensor network, it becomes vital to design energy-efficient opportunistic routing protocols to maximize the overall lifetime of the network and to enhance the quality of the sensor network
We proposed a new routing protocol (IOP) for intelligently selecting the potential relay node using naïve Baye’s classifier to achieve energy efficiency and reliability among sensor nodes
Summary
WSN is a network of spatially dispersed tiny sensor nodes responsible for the collection of data from the physical environment. Another approach that regulates the challenge of energy optimization in sensor-enabled IoT techniqueswith were proposed and developed in the past to address the issue of energy optimization in the use of quantum-based green computing, makes routing efficient and reliable [5]. The constraint of energy in sensor nodes has affected the transmission of data from one node to WSN is significantly addressed by another network-based routing protocol known as GreeDi [6]. It is another and requires boundless methods, policies, and strategies to overcome this imperativechallenge to mention [7].
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