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云计算及其新技术在未来教育中的运用
* * * * * * * Here is a wireless sensor network of homogenous active sensors with a far away base station. The network is deployed to monitor some phenomenon to detect any abnormalities in the underlying phenomenon. Examples are chemical plant monitoring, machine fault detection etc in which the underlying phenomena exhibits spatio-temporal correlation. For example, all sensors in the small area r measure the same phenomenon in a spatially correlated environment. Now, requirements of such applications depend on the phases of the application. Typically, during normal phase of operation, we expect the network to be energy efficient, however, when some abnormality occur in the phenomenon it is more important to ensure low latency and high responsiveness than energy efficiency.. * Here is a wireless sensor network of homogenous active sensors with a far away base station. The network is deployed to monitor some phenomenon to detect any abnormalities in the underlying phenomenon. Examples are chemical plant monitoring, machine fault detection etc in which the underlying phenomena exhibits spatio-temporal correlation. For example, all sensors in the small area r measure the same phenomenon in a spatially correlated environment. Now, requirements of such applications depend on the phases of the application. Typically, during normal phase of operation, we expect the network to be energy efficient, however, when some abnormality occur in the phenomenon it is more important to ensure low latency and high responsiveness than energy efficiency.. * Here is a wireless sensor network of homogenous active sensors with a far away base station. The network is deployed to monitor some phenomenon to detect any abnormalities in the underlying phenomenon. Examples are chemical plant monitoring, machine fault detection etc in which the underlying phenomena exhibits spatio-temporal correlation. For example, all sensors in the small area r measure the same phenomenon in a spatially co
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