Tactics of handling data in Internet of things

Shi, Wenchong; Maohua, Liu

doi:10.1109/ccis.2011.6045121

Cited by 10 publications

(3 citation statements)

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“…However, once data moves to the Cloud most current limitations disappear [42,[80][81][82]. Storing data in the cloud means that, from a storage point of view, data buffers within devices no longer matter.…”

Section: Machine-to-machine (M2m) Communications In the Cloudmentioning

confidence: 97%

Internet of Intelligent Things: Bringing Artificial Intelligence into Things and Communication Networks

Arsénio

Serra

Francisco

et al. 2013

Inter-Cooperative Collective Intelligence: Techniques and Applications

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Section: Machine-to-machine (M2m) Communications In the Cloudmentioning

confidence: 97%

Internet of Intelligent Things: Bringing Artificial Intelligence into Things and Communication Networks

Arsénio

Serra

Francisco

et al. 2013

Inter-Cooperative Collective Intelligence: Techniques and Applications

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“…For these reasons, Cyber-Physical Systems (CPS), Internet of Things (IoT), and Smart Cities are new research topics based on WSN technologies. All of them are based in a similar infrastructure of every heterogeneous networks, where data must be transmitted and processed, for finally enabling people using any application to monitor or to control objects [1]- [6].…”

Section: Introduction To Wsnmentioning

confidence: 99%

Performance evaluation of a volcano monitoring system using wireless sensor networks

Lara-Cueva

Benítez

Caamaño

et al. 2014

2014 IEEE Latin-America Conference on Communications (LATINCOM)

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A volcano monitoring system plays a key role for launching emergency early warning, and the use of alternative technologies have proven their effectiveness in this setting, which is the case of wireless sensor networks. For surveillance systems, the real-time requirement is mandatory due to the need for immediate access to the signals derived from a natural disaster where the goal is safeguarding lives. Previous works did not report detailed enough performance evaluation of this kind of systems, either by means of using simulation tools or in a test-bed related to real-time metrics. Our aim was to identify the optimum number of sensors to be deployed in a Volcano Monitoring System based on simulation results and corroborated with an in-situ testbed. We used ns-2 as simulation tool, where Random and Tessellation scenarios were evaluated. Our study identified that the optimal scenario in volcano monitoring is Random, with maximum eighteen nodes to satisfy metrics such as throughput, time delay, and packet loss. We deployed sixteen sensors in a strategic area at Cotopaxi Volcano, where the information was obtained during three days of continuous monitoring. This information was sent to a surveillance laboratory located 45 km away from the station placed at the volcano, and WiFi-based long distance technology was used for this purpose. The data obtained with our system allowed to distinguish long period events and volcano tectonic earthquakes.

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“…The most evident consequence of these characteristics is that data itself shapes and influences the design of an IoT system architecture. Organization of data storage and processing technologies and techniques are the two main aspects to consider [24]. In monitoring applications data processing requires real-time or near real-time responses in order to aid systems to make important decisions [25].…”

Section: Introductionmentioning

confidence: 99%

An efficient real-time architecture for collecting IoT data

Loria¹,

Toja²,

Carchiolo³

et al. 2017

Proceedings of the 2017 Federated Conference on Computer Science and Information Systems

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Abstract-IoT applications has some characteristics that set it apart from other fields mainly due to the multitude of different types of sensors producing data. In monitoring applications, data processing requires real-time or soft real-time responses in order to aid systems to make important decisions but also predictive analysis to leverage the potential of IoT by data mining vast datasets. This paper presents an architecture developed to efficiently process and store data coming from an huge number of distributed IoT sensors. The back-end of SeeYourBox services is currently based on the proposed architecture that has proven to be stable and meet all the requirements.

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Tactics of handling data in Internet of things

Cited by 10 publications

References 0 publications

Internet of Intelligent Things: Bringing Artificial Intelligence into Things and Communication Networks

Internet of Intelligent Things: Bringing Artificial Intelligence into Things and Communication Networks

Performance evaluation of a volcano monitoring system using wireless sensor networks

An efficient real-time architecture for collecting IoT data

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