Exploring large-scale small file storage for search engines

Zhang, Weizhe; Lu, Gangzhao; He, Hui; Zhang, Qizhen; Yu, Chuanliang

doi:10.1007/s11227-015-1394-z

Cited by 11 publications

(3 citation statements)

References 5 publications

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“…Smartphones are now commonly used to record video with HD quality and have Internet access for sharing on the social clouds such as Facebook, Twitter, Tumblr, and Google Plus [1]. Users upload and share HD videos on social clouds but social clouds compress video files for fast loading of the web page, save storage because of a large amount of video data, and provide QoS delivery of video streaming over low-bandwidth networks [2][3][4]. The purpose of video compression is efficiently reducing visual data by avoiding the loss of visual quality due to compression [5].…”

Section: Introductionmentioning

confidence: 99%

Quality of Experience Assessment of Video Quality in Social Clouds

Laghari

Karim

et al. 2017

Wireless Communications and Mobile Computing

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Video sharing on social clouds is popular among the users around the world. High-Definition (HD) videos have big file size so the storing in cloud storage and streaming of videos with high quality from cloud to the client are a big problem for service providers. Social clouds compress the videos to save storage and stream over slow networks to provide quality of service (QoS). Compression of video decreases the quality compared to original video and parameters are changed during the online play as well as after download. Degradation of video quality due to compression decreases the quality of experience (QoE) level of end users. To assess the QoE of video compression, we conducted subjective (QoE) experiments by uploading, sharing, and playing videos from social clouds. Three popular social clouds, Facebook, Tumblr, and Twitter, were selected to upload and play videos online for users. The QoE was recorded by using questionnaire given to users to provide their experience about the video quality they perceive. Results show that Facebook and Twitter compressed HD videos more as compared to other clouds. However, Facebook gives a better quality of compressed videos compared to Twitter. Therefore, users assigned low ratings for Twitter for online video quality compared to Tumblr that provided high-quality online play of videos with less compression.

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Section: Introductionmentioning

confidence: 99%

Quality of Experience Assessment of Video Quality in Social Clouds

Laghari

Karim

et al. 2017

Wireless Communications and Mobile Computing

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“…This method can effectively improve the reading performance of files, but the construction cost and complexity of the system are increased. In order to solve the problem of performance degradation of search engines owing to large-scale small file storage in original pages, Zhang et al [14] improved the file compression algorithm in the EXT3 file system; Meanwhile, they design an original page oriented file organization structure and a read-write query tree to store the large-scale small files which need no modification. Their method can effectively reduce the search response time and disk space waste, but it cannot improve the efficiency of small file access.…”

Section: A Changing the Storage And Management Mechanismmentioning

confidence: 99%

A Small File Merging Strategy for Spatiotemporal Data in Smart Health

2019

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With the rapid development of smart health, the health sensors and wearable devices bring huge amounts of small files of spatiotemporal data, which are distributed in different servers, and affect the I/O performance of the system seriously. There are many methods to solve the problems of a small file, but most of them are applied to specific applications. However, due to the influence of user access behavior and data type, these methods are not effective when applied to sensors data in smart health. In this paper, a novel small file merging strategy for smart health is proposed. By analyzing the features of health sensors data and the preferences of user access, the strategy uses spatiotemporal clustering for the historical user access information. Then, weights are applied to these clusters based on the access density to determine the access-related spatiotemporal range. Finally, the spatiotemporal range is used to merge small files. The experimental results show that the merging strategy is simple but efficient, and it can effectively reduce user access delay for small files of spatiotemporal data in smart health.INDEX TERMS Smart health, small file merging, spatiotemporal data, spatiotemporal clustering.

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“…URL evaluation is responsible for assessment if the URL is not relevant to the subject, to determine when or whether the crawl the URL (pruning); page analyzer is responsible for investigation after a URL to download the page content is relevant to the subject. These two modules directly affect the rate of return, coverage and accuracy of the search focused crawling [6].…”

Section: The Principle Of Topic Search Engines System For Medical Docmentioning

confidence: 99%

Research and Implementation of Topic Search Engines System based on Medical Document Classification

Hu¹

2016

Proceedings of the 2016 International Conference on Sensor Network and Computer Engineering

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This paper studies and analyzes the principle, strategy, structure and working mode of "subject network search engines". A topic search engines system based on medical document classification is designed and implemented in Windows environment using C++. In this paper, the vector space model is used to describe the document, and the document is classified by the simple vector distance method. Through the implementation and testing of the system, it can be concluded that the method used in this paper has a great improvement in the efficiency of the operation and the effect of crawling strategy, which greatly improves the accuracy of the search engines.

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Exploring large-scale small file storage for search engines

Cited by 11 publications

References 5 publications

Quality of Experience Assessment of Video Quality in Social Clouds

Quality of Experience Assessment of Video Quality in Social Clouds

A Small File Merging Strategy for Spatiotemporal Data in Smart Health

Research and Implementation of Topic Search Engines System based on Medical Document Classification

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