Distributed cross-layer optimization for healthcare monitoring applications

Alaa Awad, Amr M. Mohamed
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引用次数: 2

Abstract

Mobile Health (mHealth) systems leverage wireless and mobile communication technologies to provide healthcare stakeholders with innovative tools and solutions that can revolutionize healthcare provisioning. Body Area Sensor Networks (BASNs) is part of the mHealth system that focuses on the acquisition by a group of biomedical sensors of vital signals. However, the design and operation of BASNs are challenging, because of the limited power and small form factor of biomedical sensors. The source encoding and data transmission are the two dominant power-consuming operations in wireless monitoring system. Therefore, in this paper, a cross-layer framework that aims at minimizing the total energy consumption subject to delay and distortion constraints is proposed. The optimal encoding and transmission energy are computed to minimize the energy consumption in a delay constrained wireless BASN. This cross-layer framework is proposed, across Application-MAC-Physical layers. At large scale networks and due to heterogeneity of wireless BASNs, centralized cross-layer optimization becomes less efficient and more complex. Therefore, a distributed cross-layer optimization has been considered in this paper. The proposed solution has close-to-optimal performance with lower complexity. Simulation results show that the distributed scheme achieves the compromise between complexity and efficiency in energy consumption compared to centralized scheme.
针对医疗监控应用程序的分布式跨层优化
移动医疗(mHealth)系统利用无线和移动通信技术为医疗保健利益相关者提供创新的工具和解决方案,从而彻底改变医疗保健供应。身体区域传感器网络(BASNs)是移动医疗系统的一部分,其重点是通过一组生物医学传感器获取生命信号。然而,由于生物医学传感器的功率有限和体积小,basn的设计和操作具有挑战性。在无线监控系统中,源编码和数据传输是两大主要的功耗操作。因此,本文提出了一种以延迟和失真约束下总能耗最小为目标的跨层框架。为了使延迟受限的无线BASN的能量消耗最小化,计算了最佳的编码和传输能量。提出了跨应用- mac -物理层的跨层框架。在大规模网络中,由于无线basn的异构性,集中式跨层优化变得低效和复杂。因此,本文考虑了分布式跨层优化。该方案具有接近最优的性能和较低的复杂度。仿真结果表明,与集中式方案相比,分布式方案在能耗复杂度和效率之间取得了折衷。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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