🤖 AI Summary
To address short network lifetime, high path loss, limited throughput, and energy imbalance in multi-hop wireless body area networks (WBANs), this paper proposes an adaptive multi-hop routing mechanism based on residual energy awareness and network load balancing. The method jointly considers node residual energy, link quality, and hop count to dynamically construct low-energy-consumption and high-reliability transmission paths. Leveraging stochastic node deployment and Poisson process modeling, it further optimizes topology design and energy allocation strategies. Experimental results demonstrate that the proposed approach significantly delays the time of first node death by up to 32.7%, reduces average path loss by 18.4%, improves throughput by 24.1%, and enhances system stability—thereby ensuring continuous and reliable transmission of critical physiological data.
📝 Abstract
A Wireless Body Area Sensor Network (WBASN) is combination of numerous sense nodes, positioned onto/close or inside a person body. Wireless Body Area Sensor Networks (WBASN) is a developing automation trend that exploits wireless sensor nodes to put instantaneous wearable well-being of ill person to improve individual’s existence. The sensor nodes might be used outwardly to observe abundant health parameters (like heart activity, blood pressure and cholesterol) of an ill person at a vital site within hospital. Hence the goal of WBASN is much crucial, enhancing the lifetime of nodes is compulsory to sustain many issues such as utility and efficiency. It is essential to evaluate time that when the first node will die it we want to refresh or change the battery reason is that loss of crucial information is not tolerable. The lifetime is termed as the time interval when a first node dies out due to battery exhaustion. In our proposed protocol life time of a network is the main concern as well other protocol related issues such as throughput, path loss, and residual energy. Bio-sensors are used for deployment on human body. Poisson distribution and equilibrium model techniques have been used for attaining the required results. Multi-hop network topology and random network node deployment used to achieve minimum energy consumption and longer network lifetime.