Measuring Sensor to Cloud Energy Consumption

Rahman, Abdul; Halim, Azni Haslizan Ab; Alwi, Najwa Hayaati Mohd; Alwi, Kamaruzzaman Seman; Mohamad, Fatma Susilawati; Taufiq, Mohamad Nasrul; Mohamad, Madihah Zulfa; Abidin, Khairul Azri Zainal

doi:10.1145/3234664.3234672

Cited by 6 publications

(2 citation statements)

References 10 publications

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“…The authors highlight the current trends with future research directions for big-sensing-data processing. Abdul Rahman et al conducted a chain of experiments that measure the energy consumption of two IoT sensor nodes that are transferring data to the cloud [32]. Hence, the experimental result will be useful in comparing IoT sensor nodes implementation in both wired and wireless scenarios.…”

Section: B Rq2:what Are the Contributions Been Proposed By The Selecmentioning

confidence: 99%

Data Collection in Sensor-Cloud: A Systematic Literature Review

et al. 2020

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The integration of cloud computing and Wireless Sensor Networks (WSNs) to create Sensorcloud helps in extending the data processing capability and storage capability of WSNs. Knowing how weak WSNs are with regards to communication ability, how to collect and upload sensory data to the cloud in limited time has become an issue in Sensor-cloud. In the last decade, with increasing interest by researchers in the domain, a considerable amount of research works have been conducted and published in the research domain. The main objective of this study is to systematically review the current research on data collection in Sensor-cloud. Hence, the study also aims at identifying, categorizing, and synthesizing important studies in the field of study. Accordingly, an evidence-based methodology is utilized in this study. By doing so,43 relevant studies were identified and retrieved to answer the formulated research questions. The systematic methodology offers a methodical and rigorous study selection and evaluation process that is repeatable and precise. The result shows that research on data collection in Sensor-cloud is relatively consistent with stable output in the last five years. Ten proposal contributions were identified with System, Framework, and Algorithm being the most used by the selected studies. In conclusion, key research challenges and future research directions were identified and discussed for researchers to propose effective solutions to the existing challenges. Although research on data collection in Sensor-cloud is gaining some traction in recent years, the works in the domain are not sufficient and concrete proposals are needed to improve data collection.

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Section: B Rq2:what Are the Contributions Been Proposed By The Selecmentioning

confidence: 99%

Data Collection in Sensor-Cloud: A Systematic Literature Review

et al. 2020

View full text Add to dashboard Cite

show abstract

“…The authors highlight the current trends with future research directions for big-sensing-data processing. Abdul Rahman et al conducted a chain of experiments that measure the energy consumption of two IoT sensor nodes that are transferring data to the cloud [31]. Hence, the experimental result will be useful in comparing IoT sensor nodes implementation in both wired and wireless scenarios.…”

Section: B Rq2:what Are the Contributions Been Proposed By The Selecmentioning

confidence: 99%

Data Collection in Sensor-Cloud: A Systematic Literature Review

Ali¹

2020

Preprint

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Low Power but High Energy: The Looming Costs of Billions of Smart Devices

Wang,

Sobral,

Billah

et al. 2023

SIGENERGY Energy Inform. Rev.

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Individually, wall-powered Internet of Things devices are small: in form factor, in complexity, in function, and in power draw. However, at scale, and certainly at the scale optimistic forecasters project, these small devices add up to be a big energy problem. Just adding a single two watt sensor to each US building would add to more annual energy consumption than some small countries. Wall-powered IoT devices are also easier to create than their energy-constrained (i.e. battery-powered) counterparts, and marketed as more convenient (no hub required!), leading to their continued growth. Yet, unlike other energy consuming devices, there are no Energy Star (or equivalent) standards for smart devices. Despite having very infrequent active times, they draw power for functions like AC-DC conversion, wireless communication, and wakeup word detection continuously. Further, the discrete nature of devices and siloed nature of IoT ecosystems leads to significant redundancy in IoT devices. We posit that new techniques are needed to reverse this trend. This includes new techniques for auditing devices, systems that leverage existing devices rather than requiring new ones, and architectures that have less reliance on the cloud (and the energy overhead of network usage and cloud compute). The IoT is pitched to improve energy efficiency and reduce users' carbon footprints, but we need a new research agenda to ensure the devices themselves are not the next problem.

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Measuring Sensor to Cloud Energy Consumption

Cited by 6 publications

References 10 publications

Data Collection in Sensor-Cloud: A Systematic Literature Review

Data Collection in Sensor-Cloud: A Systematic Literature Review

Data Collection in Sensor-Cloud: A Systematic Literature Review

Low Power but High Energy: The Looming Costs of Billions of Smart Devices

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