A Load-balancing method for network GISs in a heterogeneous cluster-based system using access density
A Load-balancing method for network GISs in a heterogeneous cluster-based system using access density
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基于访问密度的异构集群系统中网络GIS的负载平衡方法
DOI:
10.1016/j.future.2012.08.005
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发表时间:
2013-02
期刊:
影响因子:
--
通讯作者:
Wu, Huayi
中科院分区:
文献类型:
--
作者:
Li, Rui;Zhang, Yinfeng;Xu, Zhengquan;Wu, Huayi
The uneven distribution of data access and imbalances in the processing capability of heterogeneous servers are two important factors that affect load balancing for network geographic information systems. This article presents a load-balancing method that considers both localized access control and balanced load allocation. First, the method considers access patterns for terrain data (tiles) that follow the Zipf law as well as the different processing performance of servers in a heterogeneous cluster-based environment. Adapting to intense user access by distributing heterogeneous cluster-based caching, the proposed method balances the access load for hotspot data to yield a higher hit rate. Then, queue theory is applied to solve the minimum processing cost for data requests in view of the overall heterogeneous cluster-based server performance, balancing the load for each server according to its processing capability and as a result, obtaining the optimal response time. Finally, using the cache distribution strategy mentioned above, data requests are distributed according to their content to prevent over-concentration of loads caused by hotspot data access. This approach takes into account large-scale traffic and highly aggregated user access preferences, adapting to the intensity of data access requests and hence handles more access traffic per unit time. Experimental results reveal that the proposed method obtains a good response performance and higher system throughput and, consequently, improves the utilization efficiency of large-scale network geographic information systems.
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DOI:
10.1109/mic.2002.1036041
发表时间:
2002-09
期刊:
IEEE Internet Comput.
影响因子:
--
作者:
D. Menascé
通讯作者:
D. Menascé
DOI:
10.1016/j.future.2009.08.002
发表时间:
2010
期刊:
Future Gener. Comput. Syst.
影响因子:
--
作者:
G. Folino;Agostino Forestiero;Giuseppe Papuzzo;G. Spezzano
通讯作者:
G. Folino;Agostino Forestiero;Giuseppe Papuzzo;G. Spezzano
DOI:
--
发表时间:
2010
期刊:
Geomatics and Information Science of Wuhan University
影响因子:
--
作者:
Li Rui
通讯作者:
Li Rui
DOI:
10.1109/69.706061
发表时间:
1998-07
期刊:
IEEE Trans. Knowl. Data Eng.
影响因子:
--
作者:
S. Shekhar;S. Ravada;Vipin Kumar;Douglas Chubb;Greg Turner
通讯作者:
S. Shekhar;S. Ravada;Vipin Kumar;Douglas Chubb;Greg Turner
DOI:
--
发表时间:
2001
期刊:
--
影响因子:
--
作者:
M. Jo;Yun-Won Jo;Jeong-Soo Oh;Si-Young Lee
通讯作者:
M. Jo;Yun-Won Jo;Jeong-Soo Oh;Si-Young Lee