Neural-Blockchain-Based Ultrareliable Cachingfor Edge-Enabled UAV Networks; IEEE Transactions on Industrial Informatics; Vol. 15, iss. 10
| Parent link: | IEEE Transactions on Industrial Informatics Vol. 15, iss. 10.— 2019.— [P. 5723-5736] |
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| Collectivité auteur: | |
| Autres auteurs: | , , , , |
| Résumé: | Title screen Mobile edge computing (MEC) reduces the computational distance between the source and the servers by fortifying near-user site evaluations of data for expedited communications, using caching. Caching provides ephemeral storage of data on designated servers for low-latency transmissions. However, with the network following a hierarchical layout, even the near-user site evaluations can be impacted by the overheads associated with maintaining a perpetual connection and other factors (e.g., those relating to the reliability of the underpinning network). Prior solutions study reliability as a factor of throughput, delays, jitters, or delivery ratio. However, with modern networks supporting high data rates, a current research trend is in ultrareliability. The latter is defined in terms of availability, connectivity, and survivability. Thus, in this paper, we focus on the ultrareliable communication in MEC. Specifically, in our setting, we use drones as on-demand nodes for efficient caching. While some existing solutions use cache-enabled drones, they generally focus only on the positioning problem rather than factors relating to ultrareliable communications. We present a novel neural-blockchain-based drone-caching approach, designed to ensure ultrareliability and provide a flat architecture (via blockchain). This neural-model fortifies an efficient transport mechanism, since blockchain maintains high reliability amongst the peers involved in the communications. The findings from the evaluation demonstrate that the proposed approach scores well in the following metrics: the probability of connectivity reaches 0.99; energy consumption is decreased by 60.34%; the maximum failure rate is affected by 13.0%; survivability is greater than 0.90; reliability reaches 1.0 even for a large set of users. Режим доступа: по договору с организацией-держателем ресурса |
| Langue: | anglais |
| Publié: |
2019
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| Sujets: | |
| Accès en ligne: | https://doi.org/10.1109/TII.2019.2922039 |
| Format: | MixedMaterials Électronique Chapitre de livre |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=663871 |
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| 200 | 1 | |a Neural-Blockchain-Based Ultrareliable Cachingfor Edge-Enabled UAV Networks |f Sharma Vishal, Ilsun You, D. N. K. Dzhayakodi (Jayakody) Arachshiladzh [et al.] | |
| 203 | |a Text |c electronic | ||
| 300 | |a Title screen | ||
| 320 | |a [References: p. 5734-5735 (35 tit.)] | ||
| 330 | |a Mobile edge computing (MEC) reduces the computational distance between the source and the servers by fortifying near-user site evaluations of data for expedited communications, using caching. Caching provides ephemeral storage of data on designated servers for low-latency transmissions. However, with the network following a hierarchical layout, even the near-user site evaluations can be impacted by the overheads associated with maintaining a perpetual connection and other factors (e.g., those relating to the reliability of the underpinning network). Prior solutions study reliability as a factor of throughput, delays, jitters, or delivery ratio. However, with modern networks supporting high data rates, a current research trend is in ultrareliability. The latter is defined in terms of availability, connectivity, and survivability. Thus, in this paper, we focus on the ultrareliable communication in MEC. Specifically, in our setting, we use drones as on-demand nodes for efficient caching. While some existing solutions use cache-enabled drones, they generally focus only on the positioning problem rather than factors relating to ultrareliable communications. We present a novel neural-blockchain-based drone-caching approach, designed to ensure ultrareliability and provide a flat architecture (via blockchain). This neural-model fortifies an efficient transport mechanism, since blockchain maintains high reliability amongst the peers involved in the communications. The findings from the evaluation demonstrate that the proposed approach scores well in the following metrics: the probability of connectivity reaches 0.99; energy consumption is decreased by 60.34%; the maximum failure rate is affected by 13.0%; survivability is greater than 0.90; reliability reaches 1.0 even for a large set of users. | ||
| 333 | |a Режим доступа: по договору с организацией-держателем ресурса | ||
| 461 | |t IEEE Transactions on Industrial Informatics | ||
| 463 | |t Vol. 15, iss. 10 |v [P. 5723-5736] |d 2019 | ||
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| 610 | 1 | |a электронный ресурс | |
| 610 | 1 | |a drones | |
| 610 | 1 | |a reliability | |
| 610 | 1 | |a servers | |
| 610 | 1 | |a blockchain | |
| 610 | 1 | |a computer network reliability | |
| 610 | 1 | |a cloud computing | |
| 610 | 1 | |a energy consumption | |
| 610 | 1 | |a дроны | |
| 610 | 1 | |a надежность | |
| 610 | 1 | |a серверы | |
| 610 | 1 | |a блокчейн | |
| 610 | 1 | |a компьютерные сети | |
| 610 | 1 | |a облачные вычисления | |
| 610 | 1 | |a энергопотребление | |
| 701 | 0 | |a Sharma Vishal | |
| 701 | 0 | |a Ilsun You | |
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