论文标题
WBAN中质量驱动的节能大数据聚合
Quality-Driven Energy-Efficient Big Data Aggregation in WBANs
论文作者
论文摘要
在The Internet（IoT）时代，无线身体区域网络（WBAS）的发展及其在大数据基础设施中的应用引起了医学研究界的广泛关注。由于传感器节点是需要异质服务质量（QoS）的低功率设备，因此管理大量医疗数据在WBAN中至关重要。因此，有效汇总大量医疗数据很重要。在这种情况下，我们为云辅助的WBAN提出了一种质量驱动和节能的大数据聚合方法。对于BAN（I阶段）和Ban Inter-Ban（II期）通信，聚合方法具有成本效益。广泛的仿真结果表明，与现有方案相比，提出的方法DEBA在聚合延迟和成本方面大大提高了网络效率。
In the Internet-of-Things (IoT) era, the development of Wireless Body Area Networks (WBANs) and their applications in big data infrastructure has gotten a lot of attention from the medical research community. Since sensor nodes are low-powered devices that require heterogeneous Quality-of-Service (QoS), managing large amounts of medical data is critical in WBANs. Therefore, effectively aggregating a large volume of medical data is important. In this context, we propose a quality-driven and energy-efficient big data aggregation approach for cloud-assisted WBANs. For both intra-BAN (Phase I) and inter-BAN (Phase II) communications, the aggregation approach is cost-effective. Extensive simulation results show that the proposed approach DEBA greatly improves network efficiency in terms of aggregation delay and cost as compared to existing schemes.
