Task Allocation and Re-allocation for Big Data Applications in Cloud Computing Environments

Haque, Rafita; Sarwar, Hasan; Kabir, S. Rayhan; Forhat, Rokeya; Sadeq, Muhammad Jafar; Akhtaruzzaman, Md.; Haque, Nafisa

doi:10.1007/978-981-15-3284-9_73

Cited by 7 publications

(4 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The framework utilized smart contracts in an Ethereum-based blockchain for heightened access control and obfuscation of data and employed advanced cryptographic techniques for further security [ 10 ]. Haque et al used the SHA256 secure hash algorithm for generating a unique and identical 256-bit or 32-byte hash value for a particular medical record and focused on five mechanisms (i.e., digital access rules, data aggregation, data immutability, data liquidity, and patient identity) of data transition for securing the medical records at the proposed blockchain model [ 11 ].…”

Section: Introductionmentioning

confidence: 99%

Design and Application of Electronic Rehabilitation Medical Record (ERMR) Sharing Scheme Based on Blockchain Technology

Zhang

Tan

et al. 2021

BioMed Research International

View full text Add to dashboard Cite

As the value of blockchain has been widely recognized, more and more industries are proposing their blockchain solutions, including the rehabilitation medical industry. Blockchain can play a powerful role in the field of rehabilitation medicine, bringing a new research idea to the management of rehabilitation medical data. The electronic rehabilitation medical record (ERMR) contains rich data dimensions, which can provide comprehensive and accurate information for assessing the health of patients, thereby enhancing the effect of rehabilitation treatment. This paper analyzed the data characteristics of ERMR and the application requirements of blockchain in rehabilitation medicine. Based on the basic principles of blockchain, the technical advantages of blockchain used in ERMR sharing have been studied. In addition, this paper designed a blockchain-based ERMR sharing scheme in detail, using the specific technologies of blockchain such as hybrid P2P network, block-chain data structure, asymmetric encryption algorithm, digital signature, and Raft consensus algorithm to achieve distributed storage, data security, privacy protection, data consistency, data traceability, and data ownership in the process of ERMR sharing. The research results of this paper have important practical significance for realizing the safe and efficient sharing of ERMR, and can provide important technical references for the management of rehabilitation medical data with broad application prospects

show abstract

Section: Introductionmentioning

confidence: 99%

Design and Application of Electronic Rehabilitation Medical Record (ERMR) Sharing Scheme Based on Blockchain Technology

Zhang

Tan

et al. 2021

BioMed Research International

View full text Add to dashboard Cite

show abstract

“…Moreover, Blockchain is an innovative technology that is used in the decentralized and distributed network. This technology has been created as an important role in price intelligence [167], electronic medical records [168], and remote database access protocol-based database [169]. So, it is possible reducing the security issues by using Blockchain at the distributed load forecasting system.…”

Section: E Implementation and Barriersmentioning

confidence: 99%

HSIC Bottleneck Based Distributed Deep Learning Model for Load Forecasting in Smart Grid With a Comprehensive Survey

et al. 2020

View full text Add to dashboard Cite

Load forecasting is a vital part of smart grids for predicting the required electrical power using artificial intelligence (AI). Deep learning is broadly used for load forecasting in the smart grid using the artificial neural network (ANN). Generally, computing the deep learning in the smart grid requires massive data aggregation or centralization and significant computational time. This paper presents a survey of deep learning-based load forecasting techniques from 2015 to 2020. This survey discusses the studies based on their deep learning techniques, Distributed Deep Learning (DDL) techniques, Back Propagation (BP) based works, and non-BP based works in the load forecasting process. Consequent to the survey, it was determined that data aggregation dependency would be beneficial for reducing computational time in load forecasting. Therefore, a conceptual model of DDL for smart grids has been presented, where the HSIC (Hilbert-Schmidt Independence Criterion) Bottleneck technique has been incorporated to provide higher accuracy.

show abstract

“…The blockchain has a wider range of applications such as healthcare, as the health data exchange in the decentralized system protects the health information [3]. An advantage of using blockchain in the medical field is that it eliminates the burden and the cost issues associated with data reconciliation, and therefore enables easy access to real-time applications using blockchain technologies [4]. The preservation and sharing of health records are necessary tasks performed in all healthcare systems.…”

Section: Introductionmentioning

confidence: 99%

“…Figure 4. The graphical representation for the proposed SHA256-VK with respect to total execution time (s)…”

mentioning

confidence: 99%

Blockchain for Secure Medical Records Storage and Medical Service Framework using SHA 256 – Verifiable Key

2021

IJIES

View full text Add to dashboard Cite

Task Allocation and Re-allocation for Big Data Applications in Cloud Computing Environments

Cited by 7 publications

References 21 publications

Design and Application of Electronic Rehabilitation Medical Record (ERMR) Sharing Scheme Based on Blockchain Technology

Design and Application of Electronic Rehabilitation Medical Record (ERMR) Sharing Scheme Based on Blockchain Technology

HSIC Bottleneck Based Distributed Deep Learning Model for Load Forecasting in Smart Grid With a Comprehensive Survey

Blockchain for Secure Medical Records Storage and Medical Service Framework using SHA 256 – Verifiable Key

Contact Info

Product

Resources

About