Prediction and Monitoring Agents using Weblogs for improved Disaster Recovery in Cloud

Javed, Rushba; Anwar, Sidra; Bibi, K. Fathima; Ashraf, M. Usman; Siddique, Samia

doi:10.5815/ijitcs.2019.04.02

Cited by 8 publications

(5 citation statements)

References 5 publications

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“…And we witness that morethe model is deeper network, its accuracy will be higher. As the ResNet152 has much higher accuracy than ResNet101 [65][66][67][68][69][70][71][72]. Even though the depth has increased significantly the ResNet152 layer architectures having 11.4 billion FLOPS (floating point operations per second) which has minimum complexity than other models.…”

Section: Discussion and Recommendationmentioning

confidence: 99%

COVID Detection Using Chest X-ray Images & Deep Learning CNN Mechanism

Aljahdali¹

2023

IJETAE

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As we know that how rapidly is corona virus spreading, starting from China, to all over the world. There are more than 5 million suspected cases and almost 0.33 million deaths according to the statistics of world meterinfo, and there are limited test kits available in hospitals because of cases are increasing rapidly on the daily bases. So, it is compulsory to build an authentic automatic detection system which gives maximum high performance to check whether the patient is Covid-19 suspect or not as an alternative to slow down the spread of coronavirus among people.In this research, we have used deep learning’s (DL) Convolutional neural network (CNN) and ResNet models. With a critical analysis, we conclude that every ResNet layered model has the high performance with error rate less than 3% on approximately all kinds of datasets of chest Xray images whether it includes rib shadow & clivade or after segmentation. We have proposed a new solution for existing model and to enhance the ResNet model by applying layered architecture style by adding more layers to our ResNet which will help to minimize the error rate. Further, to boost the performance of ResNet by tune up the batch size and learning rate, we achieve the learning rate 0.00001 that has higher accuracy as compared to the other learning rates 0.1, 0.01, 0.001 and 0.0001. The proposed study is promising framework for the covid detection that assist us to deal the COVID decease

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Section: Discussion and Recommendationmentioning

confidence: 99%

COVID Detection Using Chest X-ray Images & Deep Learning CNN Mechanism

Aljahdali¹

2023

IJETAE

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“…Generally, the cloud offers services such as security, storage, networking, massively parallel computing [52], artificial intelligence [43], etc. To make use of these facilities, different companies are renting out to cloud service providers [1,45].…”

Section: Figure 1: CC Models and Storage Typesmentioning

confidence: 99%

“…While it allows a secure peer-peer transaction between the node, expanding blockchain technology to IoT environments thus enhanced the security of systems, but it increases the system's complexity. The opposite of engaging blockchain technology in a resource-inhibited setting is doubtful, but the desired protected peer-peer functionality can be realized if the correct balance is maintained between cloud storage, IoT environments, and the benefits of blockchain technology [5,42,43,49].…”

Section: Literature Reviewmentioning

confidence: 99%

A Survey on Data Security in Cloud Computing Using Blockchain: Challenges, Existing-State-Of-The-Art Methods, And Future Directions

Ashraf

2021

Research Journal Of Computer Science And Information Technology

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Cloud computing is one of the ruling storage solutions. However, the cloud computing centralized storage method is not stable. Blockchain, on the other hand, is a decentralized cloud storage system that ensures data security. Cloud environments are vulnerable to several attacks which compromise the basic confidentiality, integrity, availability, and security of the network. This research focus on decentralized, safe data storage, high data availability, and effective use of storage resources. To properly respond to the situation of the blockchain method, we have conducted a comprehensive survey of the most recent and promising blockchain state-of-the-art methods, the P2P network for data dissemination, hash functions for data authentication, and IPFS (InterPlanetary File System) protocol for data integrity. Furthermore, we have discussed a detailed comparison of consensus algorithms of Blockchain concerning security. Also, we have discussed the future of blockchain and cloud computing. The major focus of this study is to secure the data in Cloud computing using blockchain and ease for researchers for further research work.

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“…There are still managerial issues to address, despite the widespread use of technology. Effective catastrophe management is the most pressing issue in the future of cloud computing [13]. Keeping IT assets and processes available, functioning, and resilient to meet the organization's overall business continuity goals is the primary emphasis of IT business continuity [14].…”

Section: Introductionmentioning

confidence: 99%

Efficient and robust disaster recovery system using cloud-based algorithms with data integrity

Gurulakshmanan,

Amarnath

2024

IJEECS

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Incorporating cloud-based algorithms for disaster recovery (DR), it explores data replication, failover, virtual machine (VM) migration, and consistency algorithms. These algorithms play a pivotal role in safeguarding data and system continuity during unforeseen disruptions. Data replication ensures redundancy, failover algorithms swiftly transition to backup resources, VM migration facilitates resource optimization, and consistency algorithms maintain data integrity. Leveraging cloud technology enhances the effectiveness of these algorithms, providing robust DR solutions critical for business continuity in today's digital landscape. The recent growth in popularity of internet services on a massive scale has also raised the demand for stable underpinnings. Despite the fact that DR for big data is frequently overlooked in security research, the majority of existing approaches use a narrow, endpoint-centric approach. The significance of DR strategies has grown as cloud storage has become the norm for more data. But traditional cloud-centric DR techniques may be expensive, thus less expensive alternatives are being sought. There is persistent concern in the information technology (IT) community about whether or not cloud service providers (CPs) can guarantee data and service continuity in the event of a disaster.

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Prediction and Monitoring Agents using Weblogs for improved Disaster Recovery in Cloud

Cited by 8 publications

References 5 publications

COVID Detection Using Chest X-ray Images & Deep Learning CNN Mechanism

COVID Detection Using Chest X-ray Images & Deep Learning CNN Mechanism

A Survey on Data Security in Cloud Computing Using Blockchain: Challenges, Existing-State-Of-The-Art Methods, And Future Directions

Efficient and robust disaster recovery system using cloud-based algorithms with data integrity

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