Progress and Challenges of Distributed Caching Techniques in Cloud Computing

Qin, Xiu-Lei; Zhang, Wenbo; Wei, Jun; Wang, Wei; Zhong, Hua; Huang, Tao

doi:10.3724/sp.j.1001.2013.04276

Cited by 8 publications

(4 citation statements)

References 19 publications

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“…Cloud computing provides a description of an Web service value, use and delivery model based on [1]. In cloud computing, NIST [4] defines three service models, which are SaaS, PaaS and IaaS.…”

Section: Cloud Computing and Cloud Storagementioning

confidence: 99%

“…Cloud computing is a computing model based on Web implementation of hardware and software of dynamic scalable resource sharing, and is the combination of [1] data and service sharing.In addition, it is also the deep development of [2]distributed computing, parallel computing and grid computing. With the rapid development of the Internet, various Web data is growing at an alarming rate.They are not only a huge volume of data, but also Various types.More importantly, we require low cost and long term storage,which already has brought severe challenges for quick access to Web and the traditional data storage,as well as access mode.…”

Section: Introductionmentioning

confidence: 99%

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Distributed Caching Technology Research Based on Cloud Computing Model

Liu¹

2014

AMR

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With the rapid development of Internet technology, a variety of Web data also grows at an alarming rate, which has brought great challenges for the traditional data access and storage . Distributed caching technology based on cloud computing nodes provides a storage service with high performance through a large cloud caching service.Distributed cache system in each cache server coordinates and works together effectively to realize the sharing of resources, which is an important means of cloud-based storage platform to improve application performance of the cloud.

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Section: Cloud Computing and Cloud Storagementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Distributed Caching Technology Research Based on Cloud Computing Model

Liu¹

2014

AMR

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“…Under data intensive and access intensive scenarios in a smart city, the traditional single node cache cannot meet the requirements in storage capacity and processing speed. Studies have shown that the distributed cache method can minimize network delay and enhance data access speed [ 3 , 4 ]. The replica strategy can further improve the performance of distributed cache and reduce access delay for systems with the same infrastructure, node performance, network bandwidth, and associated features.…”

Section: Introductionmentioning

confidence: 99%

Replication Strategy for Spatiotemporal Data Based on Distributed Caching System

Yang¹,

Yang²,

Xu³

et al. 2018

Sensors

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The replica strategy in distributed cache can effectively reduce user access delay and improve system performance. However, developing a replica strategy suitable for varied application scenarios is still quite challenging, owing to differences in user access behavior and preferences. In this paper, a replication strategy for spatiotemporal data (RSSD) based on a distributed caching system is proposed. By taking advantage of the spatiotemporal locality and correlation of user access, RSSD mines high popularity and associated files from historical user access information, and then generates replicas and selects appropriate cache node for placement. Experimental results show that the RSSD algorithm is simple and efficient, and succeeds in significantly reducing user access delay.

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“…Cache is one of the most important means of improving big data processing speed [2]. Data are stored in cache, which largely improve I/O efficiency and then data processing performance.…”

Section: Introductionmentioning

confidence: 99%

Cache Management of Big Data in Equipment Condition Assessment

Ma¹,

Chen²,

Lin³

et al. 2016

MATEC Web of Conferences

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Abstract. Big data platform for equipment condition assessment is built for comprehensive analysis. The platform has various application demands. According to its response time, its application can be divided into offline, interactive and real-time types. For real-time application, its data processing efficiency is important. In general, data cache is one of the most efficient ways to improve query time. However, big data caching is different from the traditional data caching. In the paper we propose a distributed cache management framework of big data for equipment condition assessment. It consists of three parts: cache structure, cache replacement algorithm and cache placement algorithm. Cache structure is the basis of the latter two algorithms. Based on the framework and algorithms, we make full use of the characteristics of just accessing some valuable data during a period of time, and put relevant data on the neighborhood nodes, which largely reduce network transmission cost. We also validate the performance of our proposed approaches through extensive experiments. It demonstrates that the proposed cache replacement algorithm and cache management framework has higher hit rate or lower query time than LRU algorithm and round-robin algorithm.

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Progress and Challenges of Distributed Caching Techniques in Cloud Computing

Cited by 8 publications

References 19 publications

Distributed Caching Technology Research Based on Cloud Computing Model

Distributed Caching Technology Research Based on Cloud Computing Model

Replication Strategy for Spatiotemporal Data Based on Distributed Caching System

Cache Management of Big Data in Equipment Condition Assessment

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