由于无线局域网(wireless local area network,WLAN)接入用户日渐增多、无线带宽资源日益稀缺,IEEE 802.11介质访问控制(media access control,MAC)层协议已经无法保证无线局域网中接入用户的服务质量(quality of service,QoS)。为了能...由于无线局域网(wireless local area network,WLAN)接入用户日渐增多、无线带宽资源日益稀缺,IEEE 802.11介质访问控制(media access control,MAC)层协议已经无法保证无线局域网中接入用户的服务质量(quality of service,QoS)。为了能在网络过载或者负载较重的情况下保证用户的QoS性能,呼叫接纳控制(call admission control,CAC)的引入是非常必要的。文章提出了一种联合权重系数和带宽降级策略的CAC算法。通过对策略前后不同类型业务性能仿真,验证了该算法对提高QoS性能的有效性。展开更多
Home energy management systems （HEMs） are used to provide comfortable life for consumers as well as to save energy. An essential component of HEMs is a home area network （HAN） that is used to remotely control the ...Home energy management systems （HEMs） are used to provide comfortable life for consumers as well as to save energy. An essential component of HEMs is a home area network （HAN） that is used to remotely control the electric devices at homes and buildings. Although HAN prices have dropped in ~ecent years but they are still expensive enough to prohibit a mass scale deployments. In this paper, a very low cost alternative to the expensive HANs is presented. We have applied a combination of non-intrusive load monitoring （NILM） and very low cost one-way HAN to develop a HEM. By using NILM and machine learning algorithms we find the status of devices and their energy consumption from a central meter and communicate with devices through the one-way HAN. The evaluations show that the proposed machine learning algorithm for NILM achieves up to 99% accuracy in certain cases. On the other hand our radio frequency （RF）-based one-way HAN achieves a range of 80 feet in all settings.展开更多
文摘由于无线局域网(wireless local area network,WLAN)接入用户日渐增多、无线带宽资源日益稀缺,IEEE 802.11介质访问控制(media access control,MAC)层协议已经无法保证无线局域网中接入用户的服务质量(quality of service,QoS)。为了能在网络过载或者负载较重的情况下保证用户的QoS性能,呼叫接纳控制(call admission control,CAC)的引入是非常必要的。文章提出了一种联合权重系数和带宽降级策略的CAC算法。通过对策略前后不同类型业务性能仿真,验证了该算法对提高QoS性能的有效性。
文摘Home energy management systems （HEMs） are used to provide comfortable life for consumers as well as to save energy. An essential component of HEMs is a home area network （HAN） that is used to remotely control the electric devices at homes and buildings. Although HAN prices have dropped in ~ecent years but they are still expensive enough to prohibit a mass scale deployments. In this paper, a very low cost alternative to the expensive HANs is presented. We have applied a combination of non-intrusive load monitoring （NILM） and very low cost one-way HAN to develop a HEM. By using NILM and machine learning algorithms we find the status of devices and their energy consumption from a central meter and communicate with devices through the one-way HAN. The evaluations show that the proposed machine learning algorithm for NILM achieves up to 99% accuracy in certain cases. On the other hand our radio frequency （RF）-based one-way HAN achieves a range of 80 feet in all settings.
