Wireless sensor networks are envisioned to be an integral part of cyber-physical systems, yet wireless networks are inherently dynamic and come with various uncertainties. One such uncertainty is wireless communicatio...Wireless sensor networks are envisioned to be an integral part of cyber-physical systems, yet wireless networks are inherently dynamic and come with various uncertainties. One such uncertainty is wireless communication itself which assumes complex spatial and temporal dynamics. For dependable and predictable performance, therefore, link estimation has become a basic element of wireless network routing. Several approaches using broadcast beacons and/or unicast MAC feedback have been proposed in the past years, but there is still no systematic characterization of the drawbacks and sources of errors in bea- con-based link estimation in low-power wireless networks, which leads to ad hoc usage of beacons in rout- ing. Using a testbed of 98 XSM motes （an enhanced version of MICA2 motes）, we characterize the negative impact that link layer retransmission and traffic-induced interference have on the accuracy of beacon-based link estimation, and we show that data-driven link estimation and routing achieve higher event reliability （e.g. by up to 18.75%） and transmission efficiency （e.g., by up to a factor of 1.96） than beacon-based approaches These findings provide solid evidence for the necessity of data-driven link estimation and demonstrate the importance of addressing the drawbacks of beacon-based link estimation when designing protocols for low-power wireless networks of cyber-physical systems.展开更多
This paper proposes a chip correlation indicator （CCI）-based link quality estimation mechanism for wireless sensor networks under non-perceived packet loss. On the basis of analyzing all related factors, it can be c...This paper proposes a chip correlation indicator （CCI）-based link quality estimation mechanism for wireless sensor networks under non-perceived packet loss. On the basis of analyzing all related factors, it can be concluded that signal-to-noise rate （SNR） is the main factor causing the non-perceived packet loss. In this paper, the relationship model between CCI and non-perceived packet loss rate （NPLR） is established from related models such as SNR versus packet success rate （PSR）, CCI versus SNR and CCI-NPLR. Due to the large fluctuating range of the raw CCI, Kalman filter is introduced to do de-noising of the raw CCI. The cubic model and the least squares method are employed to fit the relationship between CCI and SNR. In the experiments, many groups of comparison have been conducted and the results show that the proposed mechanism can achieve more accurate measurement of the non-perceived packet loss than existing approaches. Moreover, it has the advantage of decreasing extra energy consumption caused by sending large number of probe packets.展开更多
文摘Wireless sensor networks are envisioned to be an integral part of cyber-physical systems, yet wireless networks are inherently dynamic and come with various uncertainties. One such uncertainty is wireless communication itself which assumes complex spatial and temporal dynamics. For dependable and predictable performance, therefore, link estimation has become a basic element of wireless network routing. Several approaches using broadcast beacons and/or unicast MAC feedback have been proposed in the past years, but there is still no systematic characterization of the drawbacks and sources of errors in bea- con-based link estimation in low-power wireless networks, which leads to ad hoc usage of beacons in rout- ing. Using a testbed of 98 XSM motes （an enhanced version of MICA2 motes）, we characterize the negative impact that link layer retransmission and traffic-induced interference have on the accuracy of beacon-based link estimation, and we show that data-driven link estimation and routing achieve higher event reliability （e.g. by up to 18.75%） and transmission efficiency （e.g., by up to a factor of 1.96） than beacon-based approaches These findings provide solid evidence for the necessity of data-driven link estimation and demonstrate the importance of addressing the drawbacks of beacon-based link estimation when designing protocols for low-power wireless networks of cyber-physical systems.
基金supported by the National Natural Science Foundation of China (61262020)Aeronautical Science Foundation of China (2010ZC56008)Nanchang Hangkong University Postgraduate Innovation Foundation (YC2011030)
文摘This paper proposes a chip correlation indicator （CCI）-based link quality estimation mechanism for wireless sensor networks under non-perceived packet loss. On the basis of analyzing all related factors, it can be concluded that signal-to-noise rate （SNR） is the main factor causing the non-perceived packet loss. In this paper, the relationship model between CCI and non-perceived packet loss rate （NPLR） is established from related models such as SNR versus packet success rate （PSR）, CCI versus SNR and CCI-NPLR. Due to the large fluctuating range of the raw CCI, Kalman filter is introduced to do de-noising of the raw CCI. The cubic model and the least squares method are employed to fit the relationship between CCI and SNR. In the experiments, many groups of comparison have been conducted and the results show that the proposed mechanism can achieve more accurate measurement of the non-perceived packet loss than existing approaches. Moreover, it has the advantage of decreasing extra energy consumption caused by sending large number of probe packets.
