Handbook of Large-Scale Distributed Computing in Smart Healthcare
Handbook of Large-Scale Distributed Computing in Smart Healthcare
复制标题
智能医疗大规模分布式计算手册
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
Assad Abbas
中科院分区：
文献类型：
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作者：
S. Khan;Albert Y. Zomaya;Assad Abbas
传统的医疗服务已经与普适计算模式无缝集成，因此出现了具有成本效益和可靠性的智能医疗服务和系统。目前，智能医疗系统使用体域网（BAN）和可穿戴设备进行普适健康监测和环境辅助生活。BAN使用智能手机和几种手持设备来确保对医疗保健信息和服务的无处不在的访问。然而，由于在CPU速度、存储和存储器方面的固有架构限制，移动的和其他计算设备似乎不足以处理不断生成的大量传感器数据。此外，传感器数据是高度复杂和多维的。因此，将BAN与大规模和分布式计算范例（如云、集群和网格计算）集成是处理和存储需求的必然选择。此外，当代的研究工作主要集中在健康信息的传递方法，以确保在一个单一的BAN的信息交换。因此，在通过服务器远程互连多个BAN方面的努力非常有限。
Conventional healthcare services have seamlessly been integrated with pervasive computing paradigm and consequently cost-effective and dependable smart healthcare services and systems have emerged. Currently, the smart healthcare systems use Body Area Networks (BANs) and wearable devices for pervasive health monitoring and Ambient Assisted Living. The BANs use smartphones and several handheld devices to ensure ubiquitous access to the healthcare information and services. However, due to the intrinsic architectural limitations in terms of CPU speed, storage, and memory, the mobile and other computing devices seem inadequate to handle huge volumes of sensor data being generated unceasingly. In addition, the sensor data is highly complex and multi-dimensional. Therefore, integrating the BANs with large-scale and distributed computing paradigms, such as the cloud, cluster, and grid computing is inevitable to handle the processing and storage needs. Moreover, the contemporary research efforts mostly focus on health information delivery methods to ensure the information exchange within a single BAN. Consequently, the efforts have been very limited in interconnecting several BANs remotely through the servers.