2014
DOI: 10.1109/tim.2014.2326272
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Timestamp Validation Strategy for Wireless Sensor Networks Based on IEEE 802.15.4 CSS

Abstract: Network time distribution relies on timestamping, which is employed by local nodes to assign a time value to incoming timing packets. Clearly, any error affecting the timestamp has a direct impact on the final synchronization accuracy of the system. In wireless sensor networks (WSNs), impairments affecting the wireless physical layer are the primary cause of such timestamping errors, and it would be advantageous to flag suspect timestamp values before feeding them into a synchronization algorithm. This paper d… Show more

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Cited by 9 publications
(3 citation statements)
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“…This makes it prone to a replay attack; thus, security should be provided by using timestamps for data. The network time distribution is highly dependent on the time stamp, which means that all factors that affect the time stamp have a direct impact on the final synchronization accuracy of the system [75].…”
Section: Data Freshnessmentioning
confidence: 99%
“…This makes it prone to a replay attack; thus, security should be provided by using timestamps for data. The network time distribution is highly dependent on the time stamp, which means that all factors that affect the time stamp have a direct impact on the final synchronization accuracy of the system [75].…”
Section: Data Freshnessmentioning
confidence: 99%
“…Another wireless synchronization scheme based on the interpolation of the cross-correlation peak but over IEEE 802.15.4 Chirp Spread Spectrum (CSS) is shown in [22], [23] and [24]. In [21] it is developed a theoretical analysis of the feasibility of the CSS modulation to perform precise timestamping and an early experimental validation is presented.…”
Section: Background and Related Workmentioning
confidence: 99%
“…In this case, quantization is not more the prevailing source of uncertainty. Experimental analyses (see, for instance, [23]- [25]) have shown that the timestamping noise is actually due to the contribution of several mechanisms. Under these assumptions v t (t) can be modeled by a zero-mean Gaussian process with variance σ 2 v,t .…”
Section: B Timestampingmentioning
confidence: 99%