Self-adaptive load-balancing strategy based on a time series pattern for concurrent user access on Web map service

Li, Rui; Dong, Guangsheng; Jiang, Jane; Wu, Huayi; Yang, Ning; Chen, Wenjing

doi:10.1016/j.cageo.2019.06.015

Cited by 9 publications

(2 citation statements)

References 15 publications

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“…They basically focused on live migration. Self-adaptive load balancing strategy-based works [29], [30] have been proposed by research groups. Using their proposed work, they got quick response based on request arrival for windows media HTTP streaming protocol (WMSP) server thus increases the cost.…”

Section: Related Workmentioning

confidence: 99%

A load balancing strategy for reducing data loss risk on cloud using remodified throttled algorithm

Johora

Ahmed

Shajal

et al. 2022

IJECE

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<p><span>Cloud computing always deals with new problems to fulfill the demand of the challenging organizations around the whole world. Reducing response time without the risk of data loss is a very critical issue for the user requests on cloud computing. Load balancing ensures quick response of virtual machine (VM), proper usage of VMs, throughput, and minimal cost of VMs. This paper introduces a re-modified throttled algorithm (RTMA) that reduces the risk of data hampering and data loss considering the availability of VM which increases system’s performance. Response time of virtual machines have been considered in our work, so that when migration process is running, data will not be overflowed in the VMs. Thus, the data migration process becomes high and reliable. We have completed the overall simulation of our proposed algorithm on the cloud analyst tool and successfully reduced the risk of data loss as well as maintains the response time.</span></p>

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Section: Related Workmentioning

confidence: 99%

A load balancing strategy for reducing data loss risk on cloud using remodified throttled algorithm

Johora

Ahmed

Shajal

et al. 2022

IJECE

View full text Add to dashboard Cite

show abstract

“…Servers can now be started in a cluster, deployed in parallel on multiple servers, or in multinode on a single server, similar to the Nginx mechanism [78]. We use JMeter for the concurrent testing.…”

mentioning

confidence: 99%

BiGeo: A Foundational PaaS Framework for Efficient Storage, Visualization, Management, Analysis, Service, and Migration of Geospatial Big Data—A Case Study of Sichuan Province, China

Liu

Hao

Yang

2019

IJGI

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With the rapid development of big data, numerous industries have turned their focus from information research and construction to big data technologies. Earth science and geographic information systems industries are highly information-intensive, and thus there is an urgent need to study and integrate big data technologies to improve their level of information. However, there is a large gap between existing big data and traditional geographic information technologies. Owing to certain characteristics, it is difficult to quickly and easily apply big data to geographic information technologies. Through the research, development, and application practices achieved in recent years, we have gradually developed a common geospatial big data solution. Based on the formation of a set of geospatial big data frameworks, a complete geospatial big data platform system called BiGeo was developed. Through the management and analysis of massive amounts of spatial data from Sichuan Province, China, the basic framework of this platform can be better utilized to meet our needs. This paper summarizes the design, implementation, and experimental experience of BiGeo, which provides a new type of solution to the research and construction of geospatial big data.

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Browsing behavior modeling and browsing interest extraction in the trajectories on web map service platforms

Dong

et al. 2022

Expert Systems with Applications

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Self-adaptive load-balancing strategy based on a time series pattern for concurrent user access on Web map service

Cited by 9 publications

References 15 publications

A load balancing strategy for reducing data loss risk on cloud using remodified throttled algorithm

A load balancing strategy for reducing data loss risk on cloud using remodified throttled algorithm

BiGeo: A Foundational PaaS Framework for Efficient Storage, Visualization, Management, Analysis, Service, and Migration of Geospatial Big Data—A Case Study of Sichuan Province, China

Browsing behavior modeling and browsing interest extraction in the trajectories on web map service platforms

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