Wireless Sensor Network for Continuous Temperature Monitoring in Air-Cooled Data Centers: Applications and Measurement Results

Scherer, Thomas; Lombriser, Clemens; Schott, W.; Truong, Hong Linh; Weiss, Beat

doi:10.1007/978-3-642-31638-8_18

Cited by 7 publications

(5 citation statements)

References 5 publications

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“…To monitor the temperature at key locations for project GENiC, a wireless sensor network based on IBM’s DCWSN (Scherer et al, 2012) has been deployed in the C130 DC. The network utilizes MEMSIC’s IRIS sensor nodes that transmit in the 2.4 GHz band according to the IEEE 802.15.4 wireless standard for radio communication.…”

Section: Demonstration Of the Technical Approachmentioning

confidence: 99%

Data centre adaptive numerical temperature models

Tsachouridis

Scherer

2017

Transactions of the Institute of Measurement and Control

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Research results are presented regarding the online derivation of temperature state space models for air cooled data centre rooms. Using exclusively real time temperature measurements from indoor sensors, filter algorithms are programmed for the numerical computation of the parameters of discrete time varying state space models. These control oriented models are adaptive and can predict the temperature distribution across data centre rooms where air-conditioning units are used to compensate heat loads generated by the computing equipment. The research has been conducted for the European Union project GENiC and the adopted approach has been tested and validated on a real data centre facility.

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Section: Demonstration Of the Technical Approachmentioning

confidence: 99%

Data centre adaptive numerical temperature models

Tsachouridis

Scherer

2017

Transactions of the Institute of Measurement and Control

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“…As a key enabling technique of IoT, wireless sensor networks (WSNs) [29,12,28] is a hot research topic nowadays and has been used widely for supporting the applications in many domains [16,20], including habitat monitoring, pollution monitoring [18,5,6], and object tracking [17,10]. Generally, sensors are deployed in a region of interest [1,7], and they collaborate to form a sensor network which is capable of collecting sensory data and reporting the phenomenon to a data collection node called sink or base station [23,9,15].…”

Section: Introductionmentioning

confidence: 99%

Top-k Queries in Wireless Sensor Networks Leveraging Hierarchical Grid Index

Tang

Wang

Sun

et al. 2014

2014 Eighth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing

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In the Internet of Things, smart things communicate with each other, and sensed data are aggregated and queried for satisfying certain requests of end-users. Wireless sensor networks (WSN) is a key enabling technique for achieving the vision of the Internet of Things. In real applications of WSN, such as environmental monitoring and vehicle tracking, they may require to launch spatial queries for collecting sensory data to achieve certain goals. Among various queries, top-k query is one of the fundamental operators in many applications of wireless sensor networks for phenomenon monitoring. In this paper we propose a novel top-k query algorithm based on hierarchical grid index and range filter of head nodes, which is able to filter out as many unlikely top-k results as early as possible within the network from transmission.

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“…For instance, in water-related information systems, inaccurate information in aquatic monitoring may lead to false warnings being issued or harmful situations not being detected early enough (e.g., floods or pollution events). As another example, WSNs are deployed in data centers for flexible temperature monitoring and energy-efficient control of air-cooling equipment [ 3 , 4 ]. Therefore, ensuring the accuracy of collected data is also necessary for effectiveness reasons.…”

Section: Introductionmentioning

confidence: 99%

A Survey on Data Quality for Dependable Monitoring in Wireless Sensor Networks

Jesus

Casimiro

Oliveira

2017

Sensors

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Wireless sensor networks are being increasingly used in several application areas, particularly to collect data and monitor physical processes. Non-functional requirements, like reliability, security or availability, are often important and must be accounted for in the application development. For that purpose, there is a large body of knowledge on dependability techniques for distributed systems, which provide a good basis to understand how to satisfy these non-functional requirements of WSN-based monitoring applications. Given the data-centric nature of monitoring applications, it is of particular importance to ensure that data are reliable or, more generically, that they have the necessary quality. In this survey, we look into the problem of ensuring the desired quality of data for dependable monitoring using WSNs. We take a dependability-oriented perspective, reviewing the possible impairments to dependability and the prominent existing solutions to solve or mitigate these impairments. Despite the variety of components that may form a WSN-based monitoring system, we give particular attention to understanding which faults can affect sensors, how they can affect the quality of the information and how this quality can be improved and quantified.

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Wireless Sensor Network for Continuous Temperature Monitoring in Air-Cooled Data Centers: Applications and Measurement Results

Cited by 7 publications

References 5 publications

Data centre adaptive numerical temperature models

Data centre adaptive numerical temperature models

Top-k Queries in Wireless Sensor Networks Leveraging Hierarchical Grid Index

A Survey on Data Quality for Dependable Monitoring in Wireless Sensor Networks

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