A Load-balancing method for network GISs in a heterogeneous cluster-based system using access density

Abstract

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.