scholarly journals Performance evaluation of Focused Beam Routing for IoT applications in underwater environment

2021 ◽  
pp. 100471
Author(s):  
Elis Kulla
2011 ◽  
Vol 7 (4) ◽  
pp. 285-298 ◽  
Author(s):  
P. Nicopolitidis ◽  
K. Christidis ◽  
G. I. Papadimitriou ◽  
P. G. Sarigiannidis ◽  
A. S. Pomportsis

Despite being a fundamental networking primitive, data broadcasting has so far received little attention in the context of underwater networks. This paper proposes an adaptive push system for data broadcasting in underwater acoustic wireless networks with locality of client demands. The proposed system exploits the characteristic relationship between the bandwidth of an underwater acoustic link and the transmitter-receiver distance in order to improve performance in environments with locality of client demands. Simulation results show superior performance of the proposed approach in the underwater environment compared to existing systems.


Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1478 ◽  
Author(s):  
Alireza Hassani ◽  
Alexey Medvedev ◽  
Pari Delir Haghighi ◽  
Sea Ling ◽  
Arkady Zaslavsky ◽  
...  

As IoT grows at a staggering pace, the need for contextual intelligence is a fundamental and critical factor for IoT intelligence, efficiency, effectiveness, performance, and sustainability. As the standardisation efforts for IoT are fast progressing, efforts in standardising context management platforms led by the European Telecommunications Standards Institute (ETSI) are gaining more attention from both academic and industrial research organizations. These standardisation endeavours will enable intelligent interactions between ‘things’, where things could be devices, software components, web-services, or sensing/actuating systems. Therefore, having a generic platform to describe and query context is crucial for the future of IoT applications. In this paper, we propose Context Definition and Query Language (CDQL), an advanced approach that enables things to exchange, reuse and share context between each other. CDQL consists of two main parts, namely: context definition model, which is designed to describe situations and high-level context; and Context Query Language (CQL), which is a powerful and flexible query language to express contextual information requirements without considering details of the underlying data structures. An important feature of the proposed query language is its ability to query entities in IoT environments based on their situation in a fully dynamic manner where users can define situations and context entities as part of the query. We exemplify the usage of CDQL on three different smart city use cases to highlight how CDQL can be utilised to deliver contextual information to IoT applications. Performance evaluation has demonstrated scalability and efficiency of CDQL in handling a fairly large number of concurrent context queries.


2019 ◽  
Vol 52 (24) ◽  
pp. 312-317 ◽  
Author(s):  
Harith Kharrufa ◽  
Naveed Salman ◽  
Ma Lei ◽  
A.H. Kemp

2017 ◽  
Vol 3 (4) ◽  
pp. 50 ◽  
Author(s):  
Lorenzo Incipini ◽  
Alberto Belli ◽  
Lorenzo Palma ◽  
Mauro Ballicchia ◽  
Paola Pierleoni

Author(s):  
Shuhaizar Daud ◽  
Teoh Shi Yang ◽  
Muhamad Asmi Romli ◽  
Zahari Awang Ahmad ◽  
Norfadila Mahrom ◽  
...  

Author(s):  
Christodoulos Asiminidis ◽  
George Kokkonis ◽  
Sotirios Kontogiannis

ACTA IMEKO ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 69
Author(s):  
Alessandro Gallo ◽  
Fabio Bruno ◽  
Loris Barbieri ◽  
Antonio Lagudi ◽  
Maurizio Muzzupappa

<p class="Abstract">3D models of submerged structures and underwater archaeological finds are widely used in various and different applications, such as monitoring, analysis, dissemination, and inspection. Underwater environments are characterised by poor visibility conditions and the presence of marine flora and fauna. Consequently, the adoption of passive optical techniques for the 3D reconstruction of underwater scenarios is a highly challenging task.</p>This article presents a performance analysis conducted on a multi-view technique that is commonly used in air in order to highlight its limits in the underwater environment and then provide guidelines for the accurate modelling of a submerged site in poor visibility conditions. A performance analysis has been performed by comparing different image enhancement algorithms, and the results have been adopted to reconstruct an area of 40 m<sup>2</sup> at a depth of about 5 m at the underwater archaeological site of Baiae (Italy).


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