A Study on Data Aggregation and Reliability in Managing Wireless Sensor Networks

Brown, Stephen; Sreenan, Cormac J.

doi:10.1109/mobhoc.2007.4428743

Cited by 9 publications

(4 citation statements)

References 17 publications

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“…The maximum number of transmits is set to an integer value that enables the non-aggregated case to meet the required reliability of delivery of all the data to the root node (of 99%). The maximum transmissions is increased by a factor consisting of the number of data elements*the policy factor for aggregated data (to reflect the increased value of the data) as shown in [10]. In each case, the data delivered by the sensing nodes is 1 Byte long, and a packet overhead of Table III), the results show the large number of packets required for every data packet to be delivered separately up the tree in the non-aggregated case.…”

Section: A Numerical Resultsmentioning

confidence: 99%

“…As shown in [10], packets containing multiple, aggregated data values require an increased retransmission limit in order to provide high reliability (i.e. high percentage of data delivery).…”

Section: A Variables and Equationsmentioning

confidence: 99%

“…As shown in a previous study by the author, aggregation can be used to increase the reliability of data delivery from the sensing nodes to the gateway [10]. This results from using the energy saved by the traffic reduction to increase the retransmit limit (and thus the reliability) of the packets sent containing aggregated data.…”

Section: Introductionmentioning

confidence: 97%

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An analysis of loss-free data aggregation for high data reliability in wireless sensor networks

Brown

2017

2017 28th Irish Signals and Systems Conference (ISSC)

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Data aggregation is am important feature in Wireless Sensor Networks, used primarily to reduce energy use. This paper extends our previous results, which showed that data aggregation can improve the reliability of data delivery rather than degrading it as previously assumed. These previous results were based on the use of scaleable aggregation functions, such as SUM, COUNT, MIN, MAX which work independently of the network size. In this paper we extend these results to consider the reliability and energy efficiency of lossless data delivery with the semi-scaleable aggregation function APPEND, and determine the boundary conditions under which the data reliability can be maintained without an increase in the energy cost. These new results show that lossless aggregation using the APPEND aggregation function can provide improved reliability with reduced energy usage in certain conditions.

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Section: A Numerical Resultsmentioning

confidence: 99%

Section: A Variables and Equationsmentioning

confidence: 99%

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An analysis of loss-free data aggregation for high data reliability in wireless sensor networks

Brown

2017

2017 28th Irish Signals and Systems Conference (ISSC)

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“…For example, in free space, it is shown that the power a receiver receives is proportional to the wavelength of the signal (λ) and the height of antennas (H) [17]. The distance (D) between the transmitter and receiver also influences the reliability of the WSNs [15]. The environment coefficient (C E ) parameter was chosen to resolve the complex influence of environmental factors in the communications quality for the WSNs [16,17].…”

Section: Selected Parametersmentioning

confidence: 99%

Reliability Measure Model for Assistive Care Loop Framework Using Wireless Sensor Networks

Balasubramanian

Hoang

2000

Journal of Healthcare Engineering

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Body area wireless sensor networks (BAWSNs) are time-critical systems that rely on the collective data of a group of sensor nodes. Reliable data received at the sink is based on the collective data provided by all the source sensor nodes and not on individual data. Unlike conventional reliability, the definition of retransmission is inapplicable in a BAWSN and would only lead to an elapsed data arrival that is not acceptable for time-critical application. Time-driven applications require high data reliability to maintain detection and responses. Hence, the transmission reliability for the BAWSN should be based on the critical time. In this paper, we develop a theoretical model to measure a BAWSN's transmission reliability, based on the critical time. The proposed model is evaluated through simulation and then compared with the experimental results conducted in our existing Active Care Loop Framework (ACLF). We further show the effect of the sink buffer in transmission reliability after a detailed study of various other co-existing parameters.

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Robust estimation of incorrect data using relative correlation clustering technique in wireless sensor networks

Nisha

Maheswari

Venkatesh

et al. 2014

2014 International Conference on Communication and Network Technologies

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Data inaccuracy is an important problem in wireless sensor networks, since the accuracy is affected by harsh environments and malicious nodes. The reason for this data inaccuracy is the improper identification of outliers. To detect exact outliers in the wireless sensor networks, we propose the relative correlation based clustering (RCC) technique with high data accuracy and low computational overhead. Identifying spatial, temporal correlation and attribute correlation is the first phase of the proposed algorithm. The second phase is optimal cluster formation and outlier classification based on two correlation levels. The inference of the proposed idea shows high outlier detection rate with different outlier corruption level. Moreover, our results when compared with previous approach taking the same data into consideration clearly outperform them, identifying high level of detection rate(99.87% ) in the top-line with near to the ground false alarm rate.

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A Study on Data Aggregation and Reliability in Managing Wireless Sensor Networks

Abstract: Using data aggregation to reduce power consumption is a well studied area. In this paper we show a new result: data aggregation can also be used to increase reliability.In

Cited by 9 publications

References 17 publications

An analysis of loss-free data aggregation for high data reliability in wireless sensor networks

An analysis of loss-free data aggregation for high data reliability in wireless sensor networks

Reliability Measure Model for Assistive Care Loop Framework Using Wireless Sensor Networks

Robust estimation of incorrect data using relative correlation clustering technique in wireless sensor networks

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