A combination replication strategy for data-intensive services in distributed geographic information system

Shaoming Pan, Zhengquan Xu, Qingxiang Meng and Yanwen Chong

International Journal of Distributed Sensor Networks, 2017, vol. 13, issue 5, 1550147717707112

Abstract: Distributed geographic information system is a typical service-intensive application which has to store massive data in lots of storages and server for a large number of users. Due to the slow network input/output, replicas can be used to improve system performance. Since all data have the relationships of long-term stability as well as short-term bursty, a comprehensive method which considers not only static replicas and its placement strategy but also dynamic replicas and its selection strategy can achieve more significant improvements and are proposed in this article. First, a general dynamic correlation representation model of all data is designed and implemented. And then replica selection strategies for static copies and dynamic copies are proposed based on their relationships. Also, a comprehensive data placement strategy for all data and all replicas is defined to realize load balance. Finally, the performance of the proposed method has been proved through a series of comparative experiments, and the simulation results demonstrate that the proposed algorithm can meet the requirements of distributed geographic information system in all aspects, including different dataset, different access modes, and different data scales and can achieve an average local storage hit ratio of about 11.55%–45.22% higher than the other methods.

Keywords: Data replication; replica selection; data placement; data mining; distributed geographic information system (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:13:y:2017:i:5:p:1550147717707112

DOI: 10.1177/1550147717707112

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