A comprehensive analysis of improving QoS and IMM traffic of high speed wireless campus network

Yalli, Jameel Shehu; Latif, Suhaimi Abd; Masud, Mosharrof Hussain; Alam, M. K.; Abdallah, A. H.

doi:10.1109/iscaie.2014.7010201

Cited by 4 publications

(4 citation statements)

References 19 publications

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“…The summation of all the packets involved in the transmission having the maximum delay (i.e., 400ms standard) and a regular jitter interval between its consecutive packets (i.e., 1ms interval) should then be able to produce the maximum number of packets received [110].…”

Section: Data Qosmentioning

confidence: 99%

“…A node can either be in a passive state where it remains ideal until it is triggered to send data, this node performs better in such a state since its battery will last longer while an active node is the one that is continuously measuring and sending data, the problem associated with this type of node is called sleep deprivation attack [111].…”

Section: K Node Statementioning

confidence: 99%

“…When data is robust it should be able to accommodate fault tolerance by being resilient as well as quality monitoring [111].…”

Section: R Data Robustnessmentioning

confidence: 99%

“…There are many forms to protect the data but for the sake of this research the most commonly practiced are access control mechanisms, encryption (symmetric and asymmetric), and data masking [110].…”

Section: S Data Securitymentioning

confidence: 99%

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Quality of Data (QoD) in Internet of Things (IOT): An Overview, State-of-the-Art, Taxonomy and Future Directions

Yalli,

Hasan,

Haron

et al. 2023

IJACSA

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The Internet of Things (IoT) data is the main component for finding the basis that allows decisions to be made intelligently and enables other services to be explored and used. Data originates from smart things that have the capabilities to connect and share data enormously with other things in the IoT ecosystem. However, the level of intelligence obtained and the type of services provided, all depend on whether the data is trusted or not. High-quality data is the most trusted;, it can be used to extract meaningful insights from an event and can also be used to provide good services to humans. Therefore, decisions based on high-quality and trusted data could be good, whereas those based on low-quality or untrusted data are not only bad but could also have severe consequences. The term Quality of Data (QoD) is used to represent data trustworthiness and is used throughout this paper. To the best of our knowledge, this work is the first to coin the term QoD. The problems that hinder QoD are identified and discussed. One if it is an outlier, it is a major feature of the data that degrades its overall quality. Several machine-learning techniques that detect outliers have been studied and presented, with few data-cleaning techniques. This paper aims to present the elements necessary to ensure QoD by presenting the overview of the IoT state-of-the-art. Then, data quality, data in IoT, and outliers are studied, and some quality assurance techniques that maintain data quality is presented. A comprehensive taxonomy is shown to provide state-of-the-art data in IoT. Open issues and future directions were suggested at the end of the paper.

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Section: Data Qosmentioning

confidence: 99%

Section: K Node Statementioning

confidence: 99%

“…When data is robust it should be able to accommodate fault tolerance by being resilient as well as quality monitoring [111].…”

Section: R Data Robustnessmentioning

confidence: 99%

Section: S Data Securitymentioning

confidence: 99%

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