The Methods of Data Prefetching Based on User Model in Cloud Computing

Ge, Yunwen; Wu, Shaochun; Bowen, Yuan; Jiazheng, Li

doi:10.1109/ithings/cpscom.2011.82

Cited by 4 publications

(2 citation statements)

References 7 publications

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“…The analysis results are made visible to clients whilst a continued query for results generation is still running. Existing work on stream and near-time processing attempt to leverage strategies to predict user or service behaviour [89]. In this way, an analytics service can pre-fetch data to anticipate a user's behaviour, hence selecting the appropriate applications and methods before the user's request arrives.…”

Section: Data Processing and Resource Managementmentioning

confidence: 99%

Big Data computing and clouds: Trends and future directions

Assunção

Calheiros

Bianchi

et al. 2015

Journal of Parallel and Distributed Computing

671

317

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This paper discusses approaches and environments for carrying out analytics on Clouds for Big Data applications. It revolves around four important areas of analytics and Big Data, namely (i) data management and supporting architectures; (ii) model development and scoring; (iii) visualisation and user interaction; and (iv) business models. Through a detailed survey, we identify possible gaps in technology and provide recommendations for the research community on future directions on Cloud-supported Big Data computing and analytics solutions.

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Section: Data Processing and Resource Managementmentioning

confidence: 99%

Big Data computing and clouds: Trends and future directions

Assunção

Calheiros

Bianchi

et al. 2015

Journal of Parallel and Distributed Computing

671

317

View full text Add to dashboard Cite

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“…In [21], G. Yunwen proposes pre-fetching intelligence analysis and computing technologies technique. It records user usage pattern, history of service data and view records to improve the response time in terms of speed and quality.…”

Section: Software Controlled (Pro-active)mentioning

confidence: 99%

Performance analysis of time and cost efficient data pre-fetching in mobile cloud computing

Khorramnejad¹

2022

Preprint

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Recently, many methods and algorithms have been proposed in pre-fetching area. However, pre-fetching integrated with workload scheduling approaches have not been investigated as much. Initially, this thesis reviews the principles of the existing pre-fetching strategies considering latency and cost factor as primary objectives. Later, it focuses on an integrated workload scheduling and pre-fetching model to enhance the performance of response time and minimize the cost. Furthermore, response time and cost problems are formulated and to overcome the total response time and cost problems a heuristic approach is proposed. Integrated model is tested for wide range of variables and, the effects of various parameters such as processing speed and pre-fetcher’s utilization are analysed and compared. Finally, based on the results integrated pre-fetching and workload scheduling model outperforms either of them, individually. Thus, this thesis can contribute to the the new solutions in this area.

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