Communication protocols for wireless sensor networks: A survey and comparison

Ketshabetswe, Lucia Keleadile; Zungeru, Adamu Murtala; Mangwala, Mmoloki; Chuma, Joseph; Sigweni, Boyce

doi:10.1016/j.heliyon.2019.e01591

Cited by 138 publications

(79 citation statements)

References 106 publications

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“…The energy consumed by a sensor network includes detecting events, receiving packets, aggregating packets and transmitting packets to sinks. Among these activities, the energy consumed for transmitting event packets are much greater than that consumed by the other three sensor activities [24]. The reason is that transmission amplifiers consume more energy.…”

Section: A Network Settings/environmentmentioning

confidence: 99%

Energy-Efficient Cooperative Routing Scheme for Heterogeneous Wireless Sensor Networks

et al. 2020

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Generally, routing techniques are essential for Wireless Sensor Networks (WSNs) to deliver data packets to their destinations (also known as sinks). For a practical application, sensors are deployed to monitor environmental changes and events. Most WSNs detect specific events in their specific environments. But, different WSNs may monitor different events with different sensors in the same area. For example, a smart-home WSN deploys thermal sensors/meters to measure indoor and outdoor temperatures, bodytemperature sensors to detect thief intrusion, etc. Also, in the underlying house, there is a health WSN which utilizes physiological sensors to monitor patients' health condition. In other words, several WSNs of different purposes co-exist in the same geographical area. Currently, each WSN's data delivery is independent from others'. Basically, if all sensors in such a multi-WSNs environment can share their routing paths/nodes and relay event packets for other WSNs, the delivery efficiency can be enhanced since many more sensors can be found there for packet relay. Consequently, the transmission energy can be reduced since energy consumed for wireless transmission is proportional to d 2 where d is the transmission distance between sender and receiver. Therefore, in this study, we propose an energy saving routing mechanism, named Energy-Efficient Cooperative Routing Scheme for Heterogeneous Wireless Sensor Networks (EERH for short), in which several WSNs deployed in the same geographical environment form a heterogeneous sensor network and sensors relay packets for its own WSN and also for other WSNs. Routing paths are dynamically established according to the transmission directions of event packets and the residual energy of the underlying sensors and their neighbors. In addition, the packets routed to the same direction by the same sensors are aggregated to save delivering energy. Moreover, the network parameters of the EERH, like propagation delay of an event packet and the transmission distance of a sensor, are adjustable so as to satisfy the practical environment needs. Simulation results show that the EERH efficiently extends the lifetime of a heterogeneous WSN. INDEX TERMS Wireless sensor networks, heterogeneous wireless sensor networks, energy efficient, cooperative routing.

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Section: A Network Settings/environmentmentioning

confidence: 99%

Energy-Efficient Cooperative Routing Scheme for Heterogeneous Wireless Sensor Networks

et al. 2020

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“…Beyond the metric itself associated with the measurement (i.e., the acoustic measurement in the present case), other elements can also be considered in the deployment and of the optimization of the whole network, such as the connectivity between node/relay/sink, the spatial domain coverage or the network life and energy efficiency [106,107].…”

Section: Optimizing Sensor Locations and Network Deployment (1) Spatimentioning

confidence: 99%

Low-Cost Sensors for Urban Noise Monitoring Networks—A Literature Review

Picaut

Can

Fortin

et al. 2020

Sensors

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Noise pollution reduction in the environment is a major challenge from a societal and health point of view. To implement strategies to improve sound environments, experts need information on existing noise. The first source of information is based on the elaboration of noise maps using software, but with limitations on the realism of the maps obtained, due to numerous calculation assumptions. The second is based on the use of measured data, in particular through professional measurement observatories, but in limited numbers for practical and financial reasons. More recently, numerous technical developments, such as the miniaturization of electronic components, the accessibility of low-cost computing processors and the improved performance of electric batteries, have opened up new prospects for the deployment of low-cost sensor networks for the assessment of sound environments. Over the past fifteen years, the literature has presented numerous experiments in this field, ranging from proof of concept to operational implementation. The purpose of this article is firstly to review the literature, and secondly, to identify the expected technical characteristics of the sensors to address the problem of noise pollution assessment. Lastly, the article will also put forward the challenges that are needed to respond to a massive deployment of low-cost noise sensors.

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“…The fast growth of information technology influences security that almost all data are vulnerable to public access, which happens explicitly to private or sensitive data [1,2]. Consequently, improving security systems for transferring such data is crucial.…”

Section: Introductionmentioning

confidence: 99%

Utilizing Fuzzy Logic in Developing Reversible Data Hiding Method

Amrulloh¹,

Ahmad²

2020

IJIES

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The development of information technology has brought an avoidable consequence for data security. It is because data, specifically those are private or confidential, are vulnerable to illegal access. Therefore, a protection method, such as data hiding, is essential. This protection is done by inserting a secret message (payload) into a medium (cover). One of the media commonly used in this method is audio, where a payload is embedded in audio samples. Nevertheless, this common technique has several disadvantages, including the relatively small insertion space and the significant dissimilarity between stego-audio and its original audio cover. Moreover, there is a risk of payload that cannot be returned to the original file. To overcome these problems, we propose to employ the fuzzification stage in the fuzzy logic algorithm that the samples are grouped into five categories. The binary payload is evenly distributed to the available sample space, which previously was calculated by considering the total payload and the number of interpolated samples. In the case that space is not enough to carry the payload, it is dynamically increased. The results show an increase of about 48% in stego audio quality measured by the Peak Signal-to-Noise Ratio (PSNR). Moreover, the method is reversible, and the size of the sample space can be controlled to specific values.

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Communication protocols for wireless sensor networks: A survey and comparison

Cited by 138 publications

References 106 publications

Energy-Efficient Cooperative Routing Scheme for Heterogeneous Wireless Sensor Networks

Energy-Efficient Cooperative Routing Scheme for Heterogeneous Wireless Sensor Networks

Low-Cost Sensors for Urban Noise Monitoring Networks—A Literature Review

Utilizing Fuzzy Logic in Developing Reversible Data Hiding Method

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