退休社区卫生保健网络的吞吐量改进

Nagarjuna R Vatti, R. Vatti
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引用次数: 0

摘要

退休社区是为远离兄弟姐妹的富裕老年人提供的住房协会。退休社区的养老院是为了满足老年人的生理需要而建造的。他们配备了保健网络,以持续监测居民的健康参数。这类养老院的传统保健网络存在严重的服务能力下降问题。由于丢包导致吞吐量降低。报文丢失的主要原因有三:1.报文丢失;2. WiFi网络共存干扰;2 .在小地理区域内部署多个传感器节点导致的碰撞;由于大量节点同时向协调器发送数据而导致的拥塞。干扰、碰撞和拥塞是开放系统互连(OSI)参考模型中三个不同层的参数。以前大多数提高医疗网络吞吐量的工作都集中在控制其中一层的数据包丢失上。然而,通过同时控制所有这三个参数,可以有效地控制吞吐量下降。同时减少所有三层的丢包是一项非常复杂的任务,需要跨层的方法。作者开发了一种层间算法来同时减少三层的丢包。该算法在IEEE 802.1S标准上实现。基于4个无线传感器节点。通过实验分析了该算法的性能。该算法的吞吐量提高了40%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Throughput Improvement of Health Care Networks in Retirement Communities
Retirement Communities are the housing societies for the well-off elderly people, who are staying away from their siblings. The homes in retirement communities are built to cater to physiological needs of the elderly people. They are equipped with health care networks to monitor the health parameters of the residents continuously. The conventional health care networks in such retirement homes suffering a severe throughput degradation problem. Throughput degradation happens due to packet loss. The packets are lost mainly because of three factors-: 1. interference due to co-existing WiFi networks, 2. collisions due to deployment of many sensor nodes in the small geographical area, and 3. congestion due to large number of nodes transmitting data to the coordinator simultaneously. Interference, collision and congestion are parameters belong to three different layers of the Open System Interconnection (OSI) reference model. Most previous works to improve the throughput of health care networks have focused on controlling packet loss only in one of the layers. However, throughput degradation can be controlled effectively by controlling all the three parameters simultaneously. Reducing the packet loss in all the three layers simultaneously is very complex task and requires cross-layer approach. The Authors have developed an interlayer algorithm to reduce the packet loss simultaneously in all three layers. The proposed algorithm is implemented on IEEE 802.1S.4-based wireless sensor nodes. Experiments were conducted to analyze the performance of the algorithm. A 40% improvement in throughput was achieved with the proposed algorithm.
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