Improving the energy efficiency for biosensor nodes in the WBSN bottleneck zone based on a random linear network coding

Alshaheen, Hisham; Rizk, Haifa Takruri

doi:10.1109/ismict.2017.7891767

Cited by 9 publications

(15 citation statements)

References 14 publications

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“…E.g. network coding (NC) is an example of a network-based data reduction technique, researches such as [16]- [20] use network coding to maximize the life and the reliability of WSNs. They use combined packets as redundant data to improve the E2E error rate.…”

Section: Related Workmentioning

confidence: 99%

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A multi-hop routing algorithm for WSNs based on compressive sensing and multiple objective genetic algorithm

Mazaideh

Levendovszky

2021

J. Commun. Netw.

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Energy-efficiency and reliability are vital metrics of the robustness of Wireless Sensor Networks (WSNs). Various data reduction techniques are used to improve them, among them compressive sensing (CS) is a data reduction technique used to recover extensive data from fewer samples in case of sparse representation of sensor-readings. Unfortunately, energy-efficiency and accuracy are contradictory metrics, as increased accuracy requires a large number of measurements, and data transmissions. Therefore,, in this paper, a CS-based algorithm is proposed for efficient data transfer through WSNs, which uses multiple objective genetic algorithms (MOGA) to optimize the number of measurements, transmission range, and the sensing matrix. The algorithm aims at striking the right balance between energy-efficiency and accuracy. It constructs a path in a multi hop manner based on the optimized values. Numerical simulations and experiments show that Paretofront, which is the output of MOGA, helps the user to select the right combination of the number of measurements and the transmission range fitting the application at hand, and to strike a good balance between energy efficiency and accuracy. The results also demonstrate the existence of measurement matrices which lower mutual coherency improve the accuracy of CS.

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Section: Related Workmentioning

confidence: 99%

“…Some researches concentrate on improving the energy efficiency [20]- [23], others concentrate on improving reconstruction error [27], [28], [34]. In this work, we balance among payload, energy-efficiency, and accuracy of the reconstruction process by minimizing reconstruction error.…”

Section: Related Workmentioning

confidence: 99%

A multi-hop routing algorithm for WSNs based on compressive sensing and multiple objective genetic algorithm

Mazaideh

Levendovszky

2021

J. Commun. Netw.

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“…The second type of WBSNs application is the implantable devices which have the ability to perform wireless communication, as well as analyzing and delivering warnings to ICD (Implanted Cardiac Defibrillators), instance pacemakers, drug and baclofen pumps, and neurostimulators that are put inside the patient's body. 19 The work of Alshaheen and Rizk 22 introduced RLNC (Random Linear Network Coding) for optimizing power effectiveness in biosensor nodes within the WBSN bottleneck zone, mainly through the combination of power-saving and successful data-delivering in case of a deficit in one of the transmitting connections. These nodes can be placed either on the patient's skin or inside their body through an implantation, and their main function is sensing the body's changing health signs and sending the collected medical data through to the sink node on the patient's body or somewhere adjacent.…”

Section: Related Workmentioning

confidence: 99%

“…The work of Alshaheen and Rizk 22 introduced RLNC (Random Linear Network Coding) for optimizing power effectiveness in biosensor nodes within the WBSN bottleneck zone, mainly through the combination of power‐saving and successful data‐delivering in case of a deficit in one of the transmitting connections. These nodes can be placed either on the patient's skin or inside their body through an implantation, and their main function is sensing the body's changing health signs and sending the collected medical data through to the sink node on the patient's body or somewhere adjacent 23 …”

Section: Related Workmentioning

confidence: 99%

Adaptive rate energy‐saving data collecting technique for health monitoring in wireless body sensor networks

Jaber

Idrees

2020

Int J Communication

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SummaryOne of the best and cheapest solutions for continuous and remote monitoring and evaluation of patient health is to use the WBSNs (wireless body sensor networks) due to its great role in decreasing the expenses of the health care system. In this type of network, the sensed vital signs are gathered by biosensor devices then transmitted to the coordinator for further processing and fusion. Since the limited resources for biosensor devices (energy, memory, and processing) in addition to the periodic transmission for the large volume of data, it is essential to optimize the data transmission to save energy while keeping the data accuracy at the coordinator. This work suggests an AREDaCoT (adaptive rate energy‐saving data collecting technique) which aims to energy‐efficient patient health monitoring in periodic WBSNs. The AREDaCoT works in terms of so‐called periods. Each period has two stages: removing redundancy and adapting the sampling rate. The first stage uses improved LED to remove the redundancy in measurement of vital signs, whereas the second stage applies two techniques, assesses the risk score according to the risk level of the patient and the CSr (calibrate sampling rate) fittingly with different ranges of risk level for the sensor sampling ratio to be adapted. The performance of AREDaCoT has been evaluated in light of multiple series of simulations on real health datasets being compared to an existing approach. The acquired results illustrate how AREDaCoT decreases the volume of gathered data; thus, a significant energy saving has been made whilst preserving data accuracy and integrity. Moreover, the percentage results of data reduction over the original data set and the score differences between them are both acceptable.

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“…In [18], the relay first demodulates the received symbols from sensor nodes and then generates a network coded symbol by the XOR operation of selected symbols. In a similar way, the works in [19][20][21][22] also utilize the NC technology in the relay node to improve the transmission efficiency. The authors of [23] focus on the energy efficiency of cooperation transmission; decode-andforward network coding (DF-NC) is proposed to aid relay cooperative transmission.…”

Section: Introductionmentioning

confidence: 99%

A Novel Cooperation-Based Network Coding Scheme for Walking Scenarios in WBANs

Zhang

Safaei

Tran

2017

Wireless Communications and Mobile Computing

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In Wireless Body Area Networks (WBANs), the tradeoff between network throughput and energy efficiency remains a key challenge. Most current transmission schemes try to cope with the challenge from the perspective of general Wireless Sensor Networks (WSNs), which may not take the peculiarities of WBAN channels into account. In this paper, we take advantage of the correlation of on-body channels in walking scenarios to achieve a better tradeoff between throughput and energy consumption. We first analyze the characteristics of on-body channels based on realistic channel gain datasets, which are collected by our customized wireless transceivers in walking scenarios. The analytical results confirm the rationale of our newly proposed transmission scheme A3NC, which explores the combination of the aggregative allocation (AA) mechanism in MAC layer and the Analog Network Coding (ANC) technique in PHY layer. Both theoretical analyses and simulation results show that the A3NC scheme achieves significant improvement in upload throughput and energy efficiency, compared to the conventional approaches.

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Improving the energy efficiency for biosensor nodes in the WBSN bottleneck zone based on a random linear network coding

Cited by 9 publications

References 14 publications

A multi-hop routing algorithm for WSNs based on compressive sensing and multiple objective genetic algorithm

A multi-hop routing algorithm for WSNs based on compressive sensing and multiple objective genetic algorithm

Adaptive rate energy‐saving data collecting technique for health monitoring in wireless body sensor networks

A Novel Cooperation-Based Network Coding Scheme for Walking Scenarios in WBANs

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