Hindustan Institute of Technology and Science, Chennai, India.
Department of Game Media, College of Future Industry, Gachon University, Republic of Korea.
Med Eng Phys. 2022 Dec;110:103922. doi: 10.1016/j.medengphy.2022.103922. Epub 2022 Nov 17.
Healthcare, sports, the military, location monitoring and wireless body networks are emerging as technology of major relevance. As a result of the widespread usage of biomedical sensor networks in medical applications, it is essential that data packets containing vital signs be reliably and effectively supplied to the medical center. Because of its mobility, real-time monitoring, cheap cost, and real-time feedback, it may be used in a broad variety of applications. Effective data transport and a limited energy supply are the main challenges in WBAN. Uses genetic heuristics to enhance routing algorithm efficiency. Low-energy adaptive clustering hierarchy (LEACH) and distributed energy efficiency clustering (DEC) are two kinds of clustering algorithms (DEEC). A clustering-based routing protocol may be optimized using this study's optimization approach so that the network's lifetime can be extended.. The cluster heads (CHs) in sensor nodes are picked with the least amount of overhead grading possible. The cluster is being balanced. Passive clustering based on Bioinspired Particle Swarm Optimization (BPSO) should be used for clustering purposes. Routing messages efficiently means sending them quickly and efficiently without using a lot of bandwidth. Using constraints such as distance and residual power, the optimal path for the cluster may be determined with the help of iterative and heuristic chicken swarm optimization (IHCSO) for short. An evaluation of the packet distribution allocation, capacity, and average end-to-end latency illustrates the practicability of the proposed system in research concerning its efficiency. According to the findings of the research, following the technique that was proposed leads to much better outcomes.
医疗保健、体育、军事、位置监控和无线体域网正在成为具有重要相关性的技术。由于生物医学传感器网络在医疗应用中的广泛使用，因此必须可靠有效地将包含生命体征的数据报传送到医疗中心。由于其移动性、实时监测、低成本和实时反馈，它可以应用于广泛的各种应用中。有效的数据传输和有限的能源供应是 WBAN 的主要挑战。使用遗传启发式算法来提高路由算法的效率。低功耗自适应聚类层次结构（LEACH）和分布式能量高效聚类（DEC）是两种聚类算法（DEEC）。可以使用本研究的优化方法对基于聚类的路由协议进行优化，以延长网络的生命周期。使用尽可能少的开销分级选择传感器节点中的簇头（CH）。平衡集群。应使用基于生物启发粒子群优化（BPSO）的被动聚类进行聚类。使用约束条件，如距离和剩余电量，通过迭代和启发式鸡群优化（IHCSO）的帮助，可以确定簇的最佳路径。通过研究分组分配、容量和平均端到端延迟的评估，说明了所提出系统在其效率研究方面的实用性。根据研究结果，采用所提出的技术可以带来更好的结果。
