Future cloud: spherical processors for realizing low-cost upgrade in underwater data centers

Periola, A. A.; Osanaiye, Opeyemi; Olusesi, Ayobami Taiwo

doi:10.1007/s11227-020-03571-w

Cited by 6 publications

(2 citation statements)

References 15 publications

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“…European cloud storage service providers propose a static directory layering strategy, which mainly adopts a two-tier static object distribution model, alleviating the problem of too centralized data distribution on nodes to a certain extent, but this model still has certain limitations. The even distribution of the corresponding data depends on the corresponding IoT data level [ 20 ]. At the level of corresponding load balancing algorithms, relevant Chinese researchers have proposed a scheme to realize load balancing distribution in a distributed environment.…”

Section: Related Research: Research Status Of Load Balancing Cloud Storage Data Distribution System Of Internet Of Things Terminal Nodes mentioning

confidence: 99%

Load Balancing Cloud Storage Data Distribution Strategy of Internet of Things Terminal Nodes considering Access Cost

Jia-rong

2022

Computational Intelligence and Neuroscience

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With the rapid development of Internet of Things (IoT) technology, IoT terminal nodes are facing many challenges in data storage, distribution, and data management. In particular, in the IoT terminal nodes considering access cost, the corresponding data distribution and storage are professional, complex, and miscellaneous. Based on the abovementioned current situation, this article innovatively proposes a complex sensor data placement algorithm based on the cloud storage distribution of IoT terminal nodes. Under this algorithm, the accurate division of IoT data I/O methods is realized through reasonable configuration. Through the adaptive sensing algorithm, while fully considering the access cost of the algorithm, the performance of the IoT data storage system is further optimized. In the corresponding terminal node load balancing problem, this article innovatively proposes the terminal node data sorting and distribution algorithm through the node data. The sorting and distribution algorithm realizes the precise segmentation of the IoT data to be processed, thereby realizing the improvement of data reading and processing speed. Based on the proposed algorithm, this article designs a load balancing cloud storage data distribution optimization system of IoT terminal nodes considering access cost and carries out experimental verification in a real environment. The experimental results show that the data pattern division accuracy corresponding to the proposed distribution strategy is improved to 97.13% and the corresponding data access efficiency is improved to 98.3%, compared with the traditional distribution strategy. Therefore, the data distribution strategy proposed in this article has obvious performance advantages and further promotion value.

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Section: Related Research: Research Status Of Load Balancing Cloud Storage Data Distribution System Of Internet Of Things Terminal Nodes mentioning

confidence: 99%

Load Balancing Cloud Storage Data Distribution Strategy of Internet of Things Terminal Nodes considering Access Cost

Jia-rong

2022

Computational Intelligence and Neuroscience

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“…Attacks on information transmission cause some nodes to be destroyed by belligerents and to be used to transmit misleading information to prevent the accurate localization of unknown nodes [14][15][16][17]. To determine the sensor nodes' location conveniently and safely, we modified the buoy into a base fixed on the seabed and connected it with an underwater data center with submarine cables [18,19], achieving precise control of the anchor nodes' movement in the vertical direction. Therefore, the cable on the vertical line where the anchor node is located plays the role of adjusting the anchor node's depth and transmitting the information.…”

Section: Introductionmentioning

confidence: 99%

A Secure Localization Scheme for UASNs Based on Anchor Node Self-Adaptive Adjustment

Ding

Zhou

et al. 2023

JMSE

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The UASNs are widely used in underwater communications and monitoring, and many applications require accurate information regarding the position of nodes. However, intentional attacks against devices or information transmission may exist in the network, and the localization process is periodic, so it is necessary to quickly address attacks and optimize the network structure. This paper proposed an anchor node self-adaptive adjustment localization scheme (ASAL), in which the anchor node can adjust the state and depth of its participation. Two filters were used to adjust the states of referable nodes. The first filter was based on the distance difference of reverse information transmission after direct localization based on anchor nodes. The second was based on the error of the anchor node’s reverse localization after network localization was completed. In addition, a depth-adjustment mechanism of anchor nodes was proposed to optimize the network structure, the virtual force vector was introduced to describe the cost of depth adjustment, and the whale optimization algorithm was used to converge to the depth with the minimum total cost. The simulation results showed that the scheme can ensure localization accuracy and coverage in attack scenarios and reduce localization energy consumption.

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Dynamic cost effective solution for efficient cloud infrastructure

Mukhopadhyay

Tewari

2022

J Supercomput

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Future cloud: spherical processors for realizing low-cost upgrade in underwater data centers

Cited by 6 publications

References 15 publications

Load Balancing Cloud Storage Data Distribution Strategy of Internet of Things Terminal Nodes considering Access Cost

Load Balancing Cloud Storage Data Distribution Strategy of Internet of Things Terminal Nodes considering Access Cost

A Secure Localization Scheme for UASNs Based on Anchor Node Self-Adaptive Adjustment

Dynamic cost effective solution for efficient cloud infrastructure

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