41
Figure 3.8 (c) and (d) show the latency results when the servers are heavily 
loaded. When the cluster is heavily loaded, the disk accesses easily become a performance
bottleneck. Since the required time for a disk access is much longer than the local or
remote cache access, the average latency time jumps when the number of disk accesses
increases. Figure 3.8 (c) shows that the average response time of the three models soars at
the point R = 40%. Figure 3.8 (d) shows that these disk accesses become an increasingly
severe performance bottleneck when the Web servers receive more requests. Until R is
30%, the dcs and adaptive models provide stable performance. After this point, the
average latency increases fast. The dcs model shows the worst performance in Figure 3.8
(d) from R = 5% to R = 30% due to steady increase of remote cache read requests. This
result agrees with the previous experiment, which showed that the performance of dcs is
degraded when the load increases. By increasing the replication ratio, we can gain the
performance benefit due to the large number of local cache hits. The proper replication
percentage varies with the system load. However, the disk becomes a severe performance
bottleneck when a system is loaded heavily. Therefore, reducing the number of disk
accesses is more important than increasing the number of local cache hits to provide
better performance in a cluster.












  

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