scholarly journals Large-Scale Object Monitoring in Internet-of-Things: Energy-Efficient Perspectives

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 461
Author(s):  
Yongbin Yim ◽  
Euisin Lee ◽  
Seungmin Oh

Recently, the demand for monitoring a certain object covering large and dynamic scopes such as wildfires, glaciers, and radioactive contaminations, called large-scale fluid objects (LFOs), is coming to the fore due to disasters and catastrophes that lately happened. This article provides an analytic comparison of such LFOs and typical individual mobile objects (IMOs), namely animals, humans, vehicles, etc., to figure out inherent characteristics of LFOs. Since energy-efficient monitoring of IMOs has been intensively researched so far, but such inherent properties of LFOs hinder the direct adaptation of legacy technologies for IMOs, this article surveys technological evolution and advances of LFOs along with ones of IMOs. Based on the communication cost perspective correlated to energy efficiency, three technological phases, namely concentration, integration, and abbreviation, are defined in this article. By reviewing various methods and strategies employed by existing works with the three phases, this article concludes that LFO monitoring should achieve not only decoupling from node density and network structure but also trading off quantitative reduction against qualitative loss as architectural principles of energy-efficient communication to break through inherent properties of LFOs. Future research challenges related to this topic are also discussed.

2011 ◽  
Vol 63 (3) ◽  
pp. 691-709 ◽  
Author(s):  
Abhinav Vishnu ◽  
Shuaiwen Song ◽  
Andres Marquez ◽  
Kevin Barker ◽  
Darren Kerbyson ◽  
...  

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4206
Author(s):  
Farhan Nawaz ◽  
Hemant Kumar ◽  
Syed Ali Hassan ◽  
Haejoon Jung

Enabled by the fifth-generation (5G) and beyond 5G communications, large-scale deployments of Internet-of-Things (IoT) networks are expected in various application fields to handle massive machine-type communication (mMTC) services. Device-to-device (D2D) communications can be an effective solution in massive IoT networks to overcome the inherent hardware limitations of small devices. In such D2D scenarios, given that a receiver can benefit from the signal-to-noise-ratio (SNR) advantage through diversity and array gains, cooperative transmission (CT) can be employed, so that multiple IoT nodes can create a virtual antenna array. In particular, Opportunistic Large Array (OLA), which is one type of CT technique, is known to provide fast, energy-efficient, and reliable broadcasting and unicasting without prior coordination, which can be exploited in future mMTC applications. However, OLA-based protocol design and operation are subject to network models to characterize the propagation behavior and evaluate the performance. Further, it has been shown through some experimental studies that the most widely-used model in prior studies on OLA is not accurate for networks with networks with low node density. Therefore, stochastic models using quasi-stationary Markov chain are introduced, which are more complex but more exact to estimate the key performance metrics of the OLA transmissions in practice. Considering the fact that such propagation models should be selected carefully depending on system parameters such as network topology and channel environments, we provide a comprehensive survey on the analytical models and framework of the OLA propagation in the literature, which is not available in the existing survey papers on OLA protocols. In addition, we introduce energy-efficient OLA techniques, which are of paramount importance in energy-limited IoT networks. Furthermore, we discuss future research directions to combine OLA with emerging technologies.


Author(s):  
Akram Al-Hourani ◽  
Sathyanarayanan Chandrasekharan ◽  
Abbas Jamalipour ◽  
Laurent Reynaud ◽  
Sithamparanathan Kandeepan

2019 ◽  
Vol 19 (2) ◽  
pp. 701-714 ◽  
Author(s):  
Dalibor Purkovic ◽  
Marian Honsch ◽  
Tobias Raphael Maria Karl Meyer

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