Big Data Resource Management &amp; Networks: Taxonomy, Survey, and Future Directions

Awaysheh, Feras M.; Alazab, Mamoun; Garg, Sahil; Niyato, Dusit; Verikoukis, Christos

doi:10.1109/comst.2021.3094993

Cited by 44 publications

(13 citation statements)

References 206 publications

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“…The knowledge acquisition database analyzes the relationship between the collected data in detail to identify the types of user needs. More importantly, in the knowledge service process, users not only need the data itself, but also need to pay attention to the high value of data resources [13]. At this stage, library knowledge services need to combine mature machine learning algorithms to deepen the value of resources and form a push-type knowledge service.…”

Section: Application Framework Of Agricultural Digital Resourcesmentioning

confidence: 99%

RETRACTED ARTICLE: Simulation of agricultural digital economy development and policy support system based on resource sensitivity index

Dai¹

2023

Soft Comput

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The development of science and technology has also led to the progress of rural digital economy. In China, the construction of new countryside has always been an important part of economic development. The application of big data technology in rural areas can not only promote the development of rural economy, but also improve the results of environmental protection. Using the matching coe cient method of agricultural water and soil environmental characteristics, it match the rural water and soil environmental characteristics and the impact of the water environment in the autonomous region.An indispensable driving force in the process, agricultural digitalization will update the rural economic development model, weaken the barriers to the dual structure of urban and rural areas, stabilize agricultural production, promote sustainable rural development, and promote rural economic development. The current government policy support, the urgent need for new development momentum for rural economic development, and the advancement of changes in the lifestyle of urban and rural residents are promoting high-quality development of the rural economy. At the same time, we are facing challenges such as the lack of local network coverage, the lack of logistics, sales systems, and the lack of talents with digital skills. Expanding rural network coverage, optimizing rural logistics and distribution, promoting the development of agricultural big data, and strengthening the development of digital human resources are important ways for agricultural digitalization to promote rural economic development. The research focus of this paper is the parallel development of rural digital economy and environmental protection under the big data economy, and its application in the current agricultural development can achieve a win-win situation between man and nature.

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Section: Application Framework Of Agricultural Digital Resourcesmentioning

confidence: 99%

RETRACTED ARTICLE: Simulation of agricultural digital economy development and policy support system based on resource sensitivity index

Dai¹

2023

Soft Comput

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“…Distributed matrix operations. Matrix operations can be parallelized for distributed computing [4] [3]. For example, the authors of [11] proposed Mars which is an approach for hiding the programming complexity of MapReduce on GPU.…”

Section: Related Workmentioning

confidence: 99%

GNN Transformation Framework for Improving Efficiency and Scalability

Maekawa¹,

Sasaki²,

Fletcher³

et al. 2022

Preprint

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We propose a framework that automatically transforms non-scalable GNNs into precomputation-based GNNs which are efficient and scalable for large-scale graphs. The advantages of our framework are two-fold; 1) it transforms various non-scalable GNNs to scale well to large-scale graphs by separating local feature aggregation from weight learning in their graph convolution, 2) it efficiently executes precomputation on GPU for large-scale graphs by decomposing their edges into small disjoint and balanced sets. Through extensive experiments with large-scale graphs, we demonstrate that the transformed GNNs run faster in training time than existing GNNs while achieving competitive accuracy to the state-of-the-art GNNs. Consequently, our transformation framework provides simple and efficient baselines for future research on scalable GNNs.

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“…(ii) Connected vehicles that interact with each other (V2V), the roadside infrastructure (V2I), and beyond (V2X) via wireless communications. (iii) VC is an attractive technology, which takes advantage of big data analytics [25] and cloud computing to support many novel applications. Like any other VANET, data privacy, entity authentication, and resource management are major challenges.…”

Section: Vehicular Cloudmentioning

confidence: 99%

A Blockchain-Based Multi-Factor Authentication Model for a Cloud-Enabled Internet of Vehicles

Kebande

Awaysheh

Ikuesan

et al. 2021

Sensors

Self Cite

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Continuous and emerging advances in Information and Communication Technology (ICT) have enabled Internet-of-Things (IoT)-to-Cloud applications to be induced by data pipelines and Edge Intelligence-based architectures. Advanced vehicular networks greatly benefit from these architectures due to the implicit functionalities that are focused on realizing the Internet of Vehicle (IoV) vision. However, IoV is susceptible to attacks, where adversaries can easily exploit existing vulnerabilities. Several attacks may succeed due to inadequate or ineffective authentication techniques. Hence, there is a timely need for hardening the authentication process through cutting-edge access control mechanisms. This paper proposes a Blockchain-based Multi-Factor authentication model that uses an embedded Digital Signature (MFBC_eDS) for vehicular clouds and Cloud-enabled IoV. Our proposed MFBC_eDS model consists of a scheme that integrates the Security Assertion Mark-up Language (SAML) to the Single Sign-On (SSO) capabilities for a connected edge to cloud ecosystem. MFBC_eDS draws an essential comparison with the baseline authentication scheme suggested by Karla and Sood. Based on the foundations of Karla and Sood’s scheme, an embedded Probabilistic Polynomial-Time Algorithm (ePPTA) and an additional Hash function for the Pi generated during Karla and Sood’s authentication were proposed and discussed. The preliminary analysis of the proposition shows that the approach is more suitable to counter major adversarial attacks in an IoV-centered environment based on the Dolev–Yao adversarial model while satisfying aspects of the Confidentiality, Integrity, and Availability (CIA) triad.

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Big Data Resource Management & Networks: Taxonomy, Survey, and Future Directions

Cited by 44 publications

References 206 publications

RETRACTED ARTICLE: Simulation of agricultural digital economy development and policy support system based on resource sensitivity index

RETRACTED ARTICLE: Simulation of agricultural digital economy development and policy support system based on resource sensitivity index

GNN Transformation Framework for Improving Efficiency and Scalability

A Blockchain-Based Multi-Factor Authentication Model for a Cloud-Enabled Internet of Vehicles

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