Wireless sensor network and stochastic models for household power management

Bellido-Outeiriño, F.J.; Flores-Arias, J.M.; Linan-Reyes, Matias; García, Emilio José; Luna-Rodríguez, Juan-Jesús

doi:10.1109/tce.2013.6626228

Cited by 23 publications

(8 citation statements)

References 15 publications

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“…The Wireless Sensor Networks (WSNs) have been researched widely in recent years [1], [2], and many consumer products which are equipped with WSNs have been deployed in the home networks [3], [4]. However, in the WSNs which with ring topology and uniformly distributed sensors, the WSNs are usually composed of a set of sensors and one sink node, and the WSNs follow the many to one data collecting pattern, so the sensors that distribute near the sink would deplete their energy much faster than the sensors which distribute far away from the sink.…”

Section: Introductionmentioning

confidence: 99%

An efficient energy hole alleviating algorithm for wireless sensor networks

Xue

Chang

Zhong

et al. 2014

IEEE Trans. Consumer Electron.

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Many consumer products in the home environment are managed by the Wireless Sensor Networks (WSNs). However, the energy hole problem in the WSNs which with logical ring topology and uniformly distributed sensors is usually caused by the energy exhaustion of the sensors which distributed in the first radius range of the sink. This paper firstly analyzed the energy consumption model of the sensor, the data transmission model of the sensor, and the energy consumption distribution model of the WSNs. Then, a WSN Energy Hole Alleviating (WSNEHA) algorithm, which is based on the data forwarding and router selection strategy, is proposed. The WSNEHPA adopts the data forwarding and routing selection strategy to balance the energy consumption of the sensors in the first radius range of the sink. Experimental results demonstrate that WSNEHPA can efficiently balance the energy consumption of the sensors in the first radius range of the sink, and that the lifetime of the WSNs can be extended efficiently 1 .

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Section: Introductionmentioning

confidence: 99%

An efficient energy hole alleviating algorithm for wireless sensor networks

Xue

Chang

Zhong

et al. 2014

IEEE Trans. Consumer Electron.

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“…The same procedure is applied for demand profiles [2,[15][16][17][18][19][20]. Thus, whatever the profile processing used to obtain an operative model, in most cases, top-down methods are used to define resources availability, deterministic and behavioral ones to determine generators capacity and mainly bottom-up methods for shaping individuals and facilities consumption.…”

Section: Profiling Methodologymentioning

confidence: 99%

“…For instance, stochastic data analysis, temporal series measurement, aggregation or disaggregation of the electric consumption data are several commonly used modeling techniques [19]. Otherwise, local authorities such as the Spanish Government [20] might provide standard profiling methods in absence of data.…”

Section: State-of-the-art Of Energy Estimation Toolsmentioning

confidence: 99%

First Approach to a Holistic Tool for Assessing RES Investment Feasibility

et al. 2018

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Combining availability, viability, sustainability, technical options, and environmental impact in an energy-planning project is a difficult job itself for the today's engineers. This becomes harder if the potential investors also need to be persuaded. Moreover, the problem increases even more if various consumptions are considered, as their patterns depend to a large extent on the type of facility and the activity. It is therefore essential to develop tools to assess the balance between generation and demand in a given installation. In this paper, a valuable tool is developed for the seamless calculation of the integration possibilities of renewable energies and the assessment of derived technical, financial and environmental impacts. Furthermore, it also considers their interaction with the power grid or other networks, raising awareness of the polluting emissions responsible for global warming. Through a series of Structured Query Language databases and a dynamic data parameterization, the software is provided with sufficient information to encode, calculate, simulate and graphically display information on the generation and demand of electric, thermal and transport energy, all in a user-friendly environment, finally providing an evaluation and feasibility report.

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“…The recent advancements in microsensor technology [1], [2], have realized the concept of the smart home envisaged in the last century [3]. The underlying device interconnection paradigm, namely, Wireless Sensor Network (or Smart Home Sensor Network in this case) connects sensing devices to set up a smart home [4], [5].…”

Section: Introductionmentioning

confidence: 99%

Mobile agent-based cross-layer anomaly detection in smart home sensor networks using fuzzy logic

Usman

Muthukkumarasamy

2015

IEEE Trans. Consumer Electron.

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Despite the rapid advancements in consumer electronics, the data transmitted by sensing devices in a smart home environment are still vulnerable to anomalies due to node faults, transmission errors, or attacks. This affects the reliability of the received sensed data and may lead to the incorrect decision making at both local (i.e., smart home) and global (i.e., smart city) levels. This study introduces a novel mobile agent-based cross-layer anomaly detection scheme, which takes into account stochastic variability in cross-layer data obtained from received data packets, and defines fuzzy logic-based soft boundaries to characterize behavior of sensor nodes. This cross-layer design approach empowers the proposed scheme to detect both node and link anomalies, and also effectively transmits mobile agents by considering the communication link-state before transmission of the mobile agent. The proposed scheme is implemented on a real testbed and a modular application software is developed to manage the anomaly detection system in the smart home. The experimental results show that the proposed scheme detects cross-layer anomalies with high accuracy and considerably reduces the energy consumption caused by the mobile agent transmission in the poor communication link-state situations 1 .

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Wireless sensor network and stochastic models for household power management

Cited by 23 publications

References 15 publications

An efficient energy hole alleviating algorithm for wireless sensor networks

An efficient energy hole alleviating algorithm for wireless sensor networks

First Approach to a Holistic Tool for Assessing RES Investment Feasibility

Mobile agent-based cross-layer anomaly detection in smart home sensor networks using fuzzy logic

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