scholarly journals A Cuckoo Search Based Heuristic for Replicating IoT Data in Cloud Edge System

2020 ◽  
Vol 8 (4S5) ◽  
pp. 227-235
Keyword(s):  
Information Technology ◽  
Cloud Computing ◽  
Radio Frequency Identification ◽  
Cloud Storage ◽  
Large Scale ◽  
Rapid Development ◽  
Storage System ◽  
Cuckoo Search ◽  
Data Volume ◽  
High Degree

The rapid development in information technology has rendered an increase in the data volume at a speed which is surprising. In recent times, cloud computing and the Internet of Things (IoT) have become the hottest among the topics in the industry of information technology. There are many advantages to Cloud computing such as scalability, low price, and large scale and the primary technique of the IoTs like the Radio-Frequency Identification (RFID) have been applied to a large scale. In the recent times, the users of cloud storage have been increasing to a great extent and the reason behind this was the cloud storage system bringing down the issues in maintenance and also has a low amount of storage when compared to other methods. This system provides a high degree of reliability and availability where redundancy is introduced to the systems. In the replicated systems, objects get to be copied many times and every copy resides in a different location found in distributed computing. So, replication of data has been posing some threat to the cloud storage for users and also for the providers since it has been a major challenge providing efficient storage of data. So, the work has been analysing different strategies of replication of data and have pointed out several issues that are affected by this. For the purpose of this work, replication of data has been presented by employing the Cuckoo Search (CS) and the Greedy Search. The research is proceeding in a direction to reduce the replications without any adverse effect on the reliability and the availability of data.

Based on Cloud-Technology Data Storage Security

2014 ◽  
Vol 556-562 ◽  
pp. 6179-6183
Author(s):  
Zhi Gang Chai ◽  
Ming Zhao ◽  
Xiao Yu
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Cloud Storage ◽  
Rapid Development ◽  
Storage System ◽  
Storage Space ◽  
It Industry ◽  
Storage Security ◽  
The Cost ◽  
Space Requirements

With the rapid development of information technology, the extensive use of cloud computing promotes technological change in the IT industry. The use of cloud storage industry is also one solution to the problem of an amount of data storing, which is traditionally large, and unimaginably redundant. The use of cloud computing in the storage system connects the user's data with network clients via the Internet. That is to say, it not only solves a lot of data storage space requirements in request, but also greatly reduces the cost of the storage system. But in the application of cloud storage, there are also many problems to be solved, even to some extent which has hindered the development of cloud storage. Among these issues, the most concerning one is cloud storage security. The following passages discuss the problem and propose a solution to it.

scholarly journals Assure deletion supporting dynamic insertion for outsourced data in cloud computing

2020 ◽  
Vol 16 (9) ◽  
pp. 155014772095829
Author(s):  
Changsong Yang ◽  
Yueling Liu ◽  
Xiaoling Tao
Keyword(s):  
Cloud Computing ◽  
Cloud Storage ◽  
Large Scale ◽  
High Efficiency ◽  
Rapid Development ◽  
Data Set ◽  
Outsourced Data ◽  
Data Owner ◽  
Cloud Storage Service ◽  
Cloud Server

With the rapid development of cloud computing, an increasing number of data owners are willing to employ cloud storage service. In cloud storage, the resource-constraint data owners can outsource their large-scale data to the remote cloud server, by which they can greatly reduce local storage overhead and computation cost. Despite plenty of attractive advantages, cloud storage inevitably suffers from some new security challenges due to the separation of outsourced data ownership and its management, such as secure data insertion and deletion. The cloud server may maliciously reserve some data copies and return a wrong deletion result to cheat the data owner. Moreover, it is very difficult for the data owner to securely insert some new data blocks into the outsourced data set. To solve the above two problems, we adopt the primitive of Merkle sum hash tree to design a novel publicly verifiable cloud data deletion scheme, which can also simultaneously achieve provable data storage and dynamic data insertion. Moreover, an interesting property of our proposed scheme is that it can satisfy private and public verifiability without requiring any trusted third party. Furthermore, we formally prove that our proposed scheme not only can achieve the desired security properties, but also can realize the high efficiency and practicality.

Effect of Rack-Aware Placement in Cloud Storage System

2011 ◽  
Vol 121-126 ◽  
pp. 4446-4450
Author(s):  
Zhen Huang ◽  
Yuan Yuan ◽  
Yu Xing Peng
Keyword(s):  
Cloud Computing ◽  
Markov Model ◽  
Cloud Storage ◽  
Storage Systems ◽  
Rapid Development ◽  
Storage System ◽  
Data Reliability ◽  
Correlated Failures ◽  
Industry Community

We are witnessing the rapid development of Cloud Computing techniques and services. Cloud Storage is widely applied in nowadays research and industry community. One of the most hottest topic in cloud storage is the data reliability. To ensure reliability under the condition of inexpensive hardware, several techniques are discussed and applied. We simplify and analyze the data reliability by a markov model, which includes the discussion of correlated failures and rack-aware placement. Our model aims to tell the effect of rack-aware placement for cloud storage systems.

scholarly journals Cloud-based intelligent self-diagnosis and department recommendation service using Chinese medical BERT

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Junshu Wang ◽  
Guoming Zhang ◽  
Wei Wang ◽  
Ka Zhang ◽  
Yehua Sheng
Keyword(s):  
Cloud Computing ◽  
Large Scale ◽  
Medical Service ◽  
Rapid Development ◽  
Medical Knowledge ◽  
Language Models ◽  
Computing Environment ◽  
Computing Power ◽  
Cloud Computing Environment ◽  
Proposed Model

AbstractWith the rapid development of hospital informatization and Internet medical service in recent years, most hospitals have launched online hospital appointment registration systems to remove patient queues and improve the efficiency of medical services. However, most of the patients lack professional medical knowledge and have no idea of how to choose department when registering. To instruct the patients to seek medical care and register effectively, we proposed CIDRS, an intelligent self-diagnosis and department recommendation framework based on Chinese medical Bidirectional Encoder Representations from Transformers (BERT) in the cloud computing environment. We also established a Chinese BERT model (CHMBERT) trained on a large-scale Chinese medical text corpus. This model was used to optimize self-diagnosis and department recommendation tasks. To solve the limited computing power of terminals, we deployed the proposed framework in a cloud computing environment based on container and micro-service technologies. Real-world medical datasets from hospitals were used in the experiments, and results showed that the proposed model was superior to the traditional deep learning models and other pre-trained language models in terms of performance.

An RFID and sensor technology-based warehouse center: assessment of new model on a superstore in China

2019 ◽  
Vol 39 (1) ◽  
pp. 86-100 ◽  
Author(s):  
Hao Liu ◽  
Zhong Yao ◽  
Li Zeng ◽  
Jing Luan
Keyword(s):  
Radio Frequency Identification ◽  
Operations Management ◽  
Large Scale ◽  
Rapid Development ◽  
Management Mode ◽  
Sensor Technology ◽  
Warehouse Management ◽  
Content Type ◽  
Management Level ◽  
Existing Problems

Purpose Large supermarkets, chain stores and enterprises with large-scale warehousing put forward higher standards and requirements for the automation and informatization of warehouses. As one of the fast-growing commercial supermarkets in China, the traditional warehouse management mode has restricted the rapid development of Yonghui Superstores to a certain extent. The purpose of this paper is to find out how the existing warehouse mode can be changed and to solve the existing problems of warehouse management of Yonghui Superstores. Design/methodology/approach This research puts forward construction of warehouse center, which is based on radio frequency identification (RFID) and sensor technology, then designs the model for receiving, storage, operations management, distribution and outbound to solve the existing problems of warehouse management of Yonghui Superstores. Findings What technologies should be adopted to meet storage requirements? How to monitor the storage environment in real time and improve the operation and management level of the warehouse? This study found that building a warehouse center based on RFID and sensor technology was a good solution. Research limitations/implications The Yonghui Superstores warehouse center model lacks corresponding simulation experiments, and the investment and income are difficult to estimate quantitatively. Practical implications This paper has designed and discussed the warehouse center model based on RFID and sensor technology, which provides a few references for the actual investment and construction of a warehouse center. In addition, the warehouse center model has strong generalized applicability and could be widely used in various enterprises. Social implications The warehouse center could improve the warehouse management level of Yonghui Superstores and change the traditional warehouse management mode. To some extent, it improves the enterprise flexibility of the market, which will be of great significance to improve business efficiency and enhance brand image and competitiveness. Originality/value This study takes Yonghui Superstores as a case to analyze the problems of warehousing management in detail and then designs a warehouse center based on RFID and sensor technology. The study discusses the location and distribution, software and hardware selection, benefits evaluation, significances and return on investment, which makes the warehouse center model versatile, technically feasible and economically applicable.

Task Scheduling of Cloud Computing in Weapon Network System

2014 ◽  
Vol 610 ◽  
pp. 695-698
Author(s):  
Qian Tao ◽  
Bo Pan ◽  
Wen Quan Cui
Keyword(s):  
Cloud Computing ◽  
Task Scheduling ◽  
Evaluation System ◽  
Large Scale ◽  
Rapid Development ◽  
It Industry ◽  
Control Scheme ◽  
Tasks Scheduling ◽  
Constant Bandwidth

In recent years, the rapid development of cloud computing brings significant innovation in the whole IT industry. For the local tasks scheduling on each computational node of the top model of weapon network, an open task scheduling framework was introduced a task accept control scheme based on the tasks based on load balancing, quality of service (QoS) and an improved constant bandwidth server algorithm was presented. The result of simulation shows that the scheduling policies can improve the schedule speed when the number of tasks increases and can meet the demand better for the real time requirementsof the tactical training evaluation system for complexity and Large-scale.

scholarly journals Recreational Value Assessment of Urban Productive Landscape of Baguatian in Hangzhou Based on Contingent Valuation Method (CVM) and Cloud Computing

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Jian-Guo Zhang ◽  
Jian Jiang ◽  
Rui Zhang
Keyword(s):  
Cloud Computing ◽  
Large Scale ◽  
Contingent Valuation Method ◽  
Rapid Development ◽  
Value Assessment ◽  
Recreational Value ◽  
Valuation Method ◽  
Educational Degree ◽  
Occupational Background ◽  
Productive Landscapes

Cloud computing has achieved rapid development in recent years, and the use of cloud platforms to carry various large-scale services has become the general trend of the development of the information industry. This study investigates WTP of Hangzhou residents for the recreational value of Baguatian productive landscapes based on CVM and cloud computing. In this study, we did the related analysis on the social and economic characteristics and WTP of interviewees and made the monetization assessment about the recreational value of its urban productive landscapes. The result shows 62.1% of interviewees have WTP and the average payment intention (WTP) is $40.74 per year. Besides, the total recreational value of Hangzhou Baguatian productive landscapes is 354 million yuan; the relatively accepted payment mode is tax-paying and cash payment; the educational degree, occupational background, and income are the main factors influencing the tourists’ WTP and the correlation between interviewees’ origin, permanent residence, and WTP is not apparent.

scholarly journals MS-PyCloud: An open-source, cloud computing-based pipeline for LC-MS/MS data analysis

2018 ◽  
Author(s):  
Li Chen ◽  
Bai Zhang ◽  
Michael Schnaubelt ◽  
Punit Shah ◽  
Paul Aiyetan ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Data Analysis ◽  
Open Source ◽  
High Performance ◽  
Large Scale ◽  
Rapid Development ◽  
Data File ◽  
Data Sets ◽  
Proteomics Data ◽  
Amazon Web Services

ABSTRACTRapid development and wide adoption of mass spectrometry-based proteomics technologies have empowered scientists to study proteins and their modifications in complex samples on a large scale. This progress has also created unprecedented challenges for individual labs to store, manage and analyze proteomics data, both in the cost for proprietary software and high-performance computing, and the long processing time that discourages on-the-fly changes of data processing settings required in explorative and discovery analysis. We developed an open-source, cloud computing-based pipeline, MS-PyCloud, with graphical user interface (GUI) support, for LC-MS/MS data analysis. The major components of this pipeline include data file integrity validation, MS/MS database search for spectral assignment, false discovery rate estimation, protein inference, determination of protein post-translation modifications, and quantitation of specific (modified) peptides and proteins. To ensure the transparency and reproducibility of data analysis, MS-PyCloud includes open source software tools with comprehensive testing and versioning for spectrum assignments. Leveraging public cloud computing infrastructure via Amazon Web Services (AWS), MS-PyCloud scales seamlessly based on analysis demand to achieve fast and efficient performance. Application of the pipeline to the analysis of large-scale iTRAQ/TMT LC-MS/MS data sets demonstrated the effectiveness and high performance of MS-PyCloud. The software can be downloaded at: https://bitbucket.org/mschnau/ms-pycloud/downloads/

A Review of Security Challenges in Cloud Storage of Big Data

2019 ◽  
pp. 1440-1459
Author(s):  
Sara Usmani ◽  
Faiza Rehman ◽  
Sajid Umair ◽  
Safdar Abbas Khan
Keyword(s):  
Information Technology ◽  
Cloud Computing ◽  
Big Data ◽  
Data Storage ◽  
Cloud Storage ◽  
Personal Data ◽  
Security And Privacy ◽  
Privacy And Security ◽  
Security Issues ◽  
The People

The novel advances in the field of Information Technology presented the people pleasure, luxuries and ease. One of the latest expansions in the Information Technology (IT) industry is Cloud Computing, a technology that uses the internet for storage and access of data. It is also known as on-demand computing. The end user can access personal data and applications anywhere any time with a device having internet. Cloud Computing has gained an enormous attention but it results in the issues of data security and privacy as the data is scattered on different machines in different places across the globe which is a serious threat to the technology. It has many advantages like flexibility, efficiency and scalability but many of the companies are hesitant to invest in it due to privacy concerns. In this chapter, the objective is to review the privacy and security issues in cloud storage of Big Data and to enhance the security in cloud environment so that end users can enjoy a trustworthy and reliable data storage and access.

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