Wearable computing has a great prospect in smart healthcare applications. The emergence of the Internet of Things, Wireless Body Area Networks (WBANs), and big data processing open numerous challenges and opportunities. In healthcare, the monitoring is done by placing/implanting sensor nodes (resource-constrained devices) on a patient’s body to communicate data to a resource-rich node called a sink. The data transmission energy consumption is directly proportional to the distance between the sensor and the sink node. Therefore, it is vital to reduce the energy consumption of the sensor node due to data transmission. In this article, a new Dual Forwarder Selection Technique (DFST) has been proposed to prolong the network lifetime by reducing energy consumption and ultimately improving the stability period and throughput of the network. The DFST works by grouping sensor nodes on a body where both forwarder nodes have been selected through a cost function for relaying data to the sink. The proposed scheme’s efficiency has been evaluated using simulation results in terms of network stability, lifetime, and throughput. Energy consumption of sensor nodes minimized, which, as a result, increased residual network energy. The number of dead nodes of the DFST is about 50% less than that of its counterparts RE-ATTEMPT and iM-SIMPLE. The average throughput of the proposed scheme is 51% and 8% higher than the methods. Similarly, the residual energy of the DFST is approximately 200% and 120% more than iM-SIMPLE and RE-ATTEMPT, respectively.

可穿戴计算在智能医疗保健应用中具有广阔的前景。物联网，无线体域网（WBAN）和大数据处理的出现带来了无数挑战和机遇。在医疗保健中，监视是通过将传感器节点（资源受限的设备）放置/植入患者的身体上，以将数据传送到称为“接收器”的资源丰富的节点来完成的。数据传输的能耗与传感器与接收器节点之间的距离成正比。因此，至关重要的是减少由于数据传输而导致的传感器节点的能耗。在本文中，一种新的双转发器选择技术（DFST）已提出通过减少能耗并最终改善网络的稳定期和吞吐量来延长网络寿命。DFST通过将主体上的传感器节点进行分组来进行工作，在该主体上，通过成本函数将两个转发器节点都选中了，以便将数据中继到接收器。已使用仿真结果对网络稳定性，生命周期和吞吐量进行了评估，从而评估了所提出方案的效率。传感器节点的能耗降至最低，因此增加了剩余网络能量。DFST的死节点数比其对应的RE-ATTEMPT和iM-SIMPLE少约50％。所提出的方案的平均吞吐量比该方法分别高51％和8％。同样，DFST的剩余能量比iM-SIMPLE和RE-ATTEMPT大约高200％和120％，