Analysis of the asymmetric shortest queue problem
Queueing Systems: Theory and Applications
SIGMETRICS '99 Proceedings of the 1999 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Tradeoffs in Designing Web Clusters
IEEE Internet Computing
Declustering and Load-Balancing Methods for Parallelizing Geographic Information Systems
IEEE Transactions on Knowledge and Data Engineering
Performance evaluation of scheduling schemes for NOW with heterogeneous computing power
Future Generation Computer Systems - Special issue: Modeling and simulation in supercomputing and telecommunications
Future Generation Computer Systems - Special issue: Modeling and simulation in supercomputing and telecommunications
Hotmap: Looking at Geographic Attention
IEEE Transactions on Visualization and Computer Graphics
A grid portal for solving geoscience problems using distributed knowledge discovery services
Future Generation Computer Systems
Quantitative analysis of zipf’s law on web cache
ISPA'05 Proceedings of the Third international conference on Parallel and Distributed Processing and Applications
Incremental anomaly detection approach for characterizing unusual profiles
Sensor-KDD'08 Proceedings of the Second international conference on Knowledge Discovery from Sensor Data
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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.