2016
DOI: 10.1109/access.2016.2635941
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QoI-Aware Unified Framework for Node Classification and Self-Reconfiguration Within Heterogeneous Visual Sensor Networks

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Cited by 4 publications
(4 citation statements)
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“…There are many works to detect botnets using the honeypots, such as Kippo [46], Cowry [47], Dionaea [48], Telnet-Internet of Things (IoT)-Honipat [49], and IoTPOT [50]. However, this paper focuses more on utilizing honeypots to monitor the P2P botnets.…”
Section: Passive Monitoring Approachesmentioning
confidence: 99%
“…There are many works to detect botnets using the honeypots, such as Kippo [46], Cowry [47], Dionaea [48], Telnet-Internet of Things (IoT)-Honipat [49], and IoTPOT [50]. However, this paper focuses more on utilizing honeypots to monitor the P2P botnets.…”
Section: Passive Monitoring Approachesmentioning
confidence: 99%
“…Image content can be measured in terms of entropy, a metric related to the image's exposure to the correct amount of light, avoiding over and under-exposure [48,49]. It is also possible to quantify the quality of the data gathered from a visual node through peak signal-to-noise ratio (PSNR) based metric, evaluating the ratio between the maximum possible value of a signal, which is the information of each pixel, and the power of noise that affects the accuracy of the signal representation [77,78]. These are some interesting ways to assess visual monitoring quality in WVSN.…”
Section: Miscellaneousmentioning
confidence: 99%
“…Finally, the application performance reliability can be described through the required and provided Quality of Information (QoI) thresholds. QoI is defined as data suitability for a given application or a decision making process, and it can be quantified by a peak signal-to-noise ratio [78].…”
Section: Reviewing Dependable Qualitymentioning
confidence: 99%
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