Sensor Data Storage Performance: SQL or NoSQL, Physical or Virtual

Veen, Jan Sipke van der; Waaij, Bram van der; Meijer, Robert

doi:10.1109/cloud.2012.18

Cited by 118 publications

(57 citation statements)

References 12 publications

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“…And one of the main topics here is how to embed the database management system such as SQL, and NoSQL. [11] [12] and [13] are examples in this generation. Our study should be identified as one of the second generation from the point of view of loose coupling and service oriented.…”

Section: Related Workmentioning

confidence: 99%

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Analysis of Impactful Factors on Performance in Combining Architectural Elements of IoT

Kikuchi

Watanabe²,

Kondo³

et al. 2017

AIT

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We implemented a generalized infrastructure for Internet of Things (IoT infrastructure) to be applicable in various areas such as Smart Grid. That IoT infrastructure has two methods to store sensor data. They commonly have the features of double overlay structure, virtualization of sensors, composite services as federation using publisher/subscriber. And they are implemented as synthesizing the elemental architectures. The two methods majorly have the common architectural elements, however there are differences in how to compose and utilize them. But we observed the non-negligible differences in their achieved performance by the actual implementations due to operational items beyond these architectural elements. In this paper, we present the results of our analysis about the factors of the revealed differences based on the measured performance. In particular, it is clarified that a negative side effect due to combining independent elemental micro solutions naively could be amplified, if maximizing the level of loose coupling is applied as the most prioritized design and operational policy. Primarily, these combinations should be evaluated and verified during the basic design phase. However, the variation of how to synthesize them tends to be a blind spot when adopting the multiple independent architectural elements commonly. As a practical suggestion from this case, the emphasized importance in carrying out a new synthetization with multiple architectures is to make a balance naturally among architectural elements, or solutions based on them, and there is a certain demand to establish a methodology for architectural synthetization, including verification.

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Section: Related Workmentioning

confidence: 99%

“…Our study should be identified as one of the second generation from the point of view of loose coupling and service oriented. However, [11] and [13] remain at the studies around the storages only, whereas our focus is just on the upper layer of the storages. Therefore, there is a difference of viewpoints between both.…”

Section: Related Workmentioning

confidence: 99%

Analysis of Impactful Factors on Performance in Combining Architectural Elements of IoT

Kikuchi

Watanabe²,

Kondo³

et al. 2017

AIT

View full text Add to dashboard Cite

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“…Also, write performance between Redundant Arrays for Inexpensive Disks (RAID) on hard drives and Solid State Devices (SSD)s have been evaluated [4] [7] [9]. Also, the feasibility of databases and NoSQL stores for data collection has been evaluated [8] [13]. However, the impact of RAID configuration, hard drive speed, and Eucalyptus virtualization on write and database performance hasn't been studied together to the authors' best knowledge, which is the contribution of this paper.…”

Section: Introductionmentioning

confidence: 99%

The implications of disk-based RAID and virtualization for write-intensive services

Pääkkönen

Pakkala

2015

Proceedings of the 30th Annual ACM Symposium on Applied Computing

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Many data-intensive services exist, which create value for different stakeholders. Examples include mobile data analytics services, sensors collecting information for energy management of residences, or network equipment collecting data at high speed for traffic analysis. Such services impose performance requirements for the platform, which is used for implementation of data processing functionalities. This paper focuses on evaluating the impact of disk-based RAID and virtualization, when designing and implementing a platform for write-intensive applications. The results indicate that hard drive speed, and RAID configuration both have a significant impact on performance. However, their effect depends on size of data, and utilization of direct I/O for writing. Virtualization on Eucalyptus cloud platform had a significantly negative effect on write performance.

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“…For storage purposes, our cloud service uses SQL and NoSQL databases. The MongoDB NoSQL database was selected over a relational database due to its higher scalability and better performance when handling large loads of concurrent write operations [30]. This paradigm fits very well with the intrinsically writeintensive characteristic of sensor data collection applications.…”

Section: Mobile Back-end As Amentioning

confidence: 99%

Improving Healthcare Team Collaboration in Hospital Transfers through Cloud-Based Mobile Systems

Neyem

Carrillo

Jerez

et al. 2016

Mobile Information Systems

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It is a clinical fact that better patient flow management in and between hospitals improves quality of care, resource utilization, and cost efficiency. As the number of patients in hospitals constantly grows, the need for hospital transfers is directly affected. Interhospital transfers can be required for several reasons but they are most commonly made when the diagnostic and therapeutic facilities required for a patient are not available locally. Transferring a critical patient between hospitals is commonly associated with risk of death and complications. This raises the question: How can we improve healthcare team collaboration in hospital transfers through the use of emerging information technology and communication services? This paper presents a cloud-based mobile system for supporting team collaboration and decision-making in the transportation of patients in critical condition. The Rapid Emergency Medicine Score (REMS) scale was used as an outcome variable, being a useful scale to assess the risk profile of critical patients requiring transfers between hospitals. This helps medical staff to adopt proper risk-prevention measures when handling a transfer and to react on time if any complications arise in transit.

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Sensor Data Storage Performance: SQL or NoSQL, Physical or Virtual

Cited by 118 publications

References 12 publications

Analysis of Impactful Factors on Performance in Combining Architectural Elements of IoT

Analysis of Impactful Factors on Performance in Combining Architectural Elements of IoT

The implications of disk-based RAID and virtualization for write-intensive services

Improving Healthcare Team Collaboration in Hospital Transfers through Cloud-Based Mobile Systems

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