# Remaining Capacity Based Load Balancing Architecture for Heterogeneous Web Server System

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5 (a) Hit rate system must have as little drop rate as possible. Now we compare the drop rate of these three load balancing algorithms. As shown in Fig. 8, the RR algorithm begins to drop client request at 300 requests per second, but in the LC and RC algorithm, they begin to drop requests at 600 and 700 requests per second, respectively. Because the LC algorithm considers only the connection number, it redirects the request to the Web server according to the current connection. But with RC algorithm, the remaining capacity will be considered, so the request will be redirected to the server with largest remaining capacity. Thus the drop rate is less than that of LC algorithm. (b) Utilization Figure 6. LC hit rate and utilization (a) Hit rate Figure 8. Drop rate of the three algorithms 4.3 Scalability of the Load Balancing System In section 4.1, we can find that the three Web servers can not handle the arrival rate at 1000 requests per second. How many servers do we need if we want to handle 1000 requests per second, and the drop rate will be less than say, 5%? The scalability test results are shown in Figures 9 to 11. Figure 9 shows the result of using RR algorithm. When the total number of servers is three, the drop rate is 40%. The upper line shows that when we add the least capable server, say S 3, the drop rate decrease slowly. When we add S 1 or S 2, the overall drop rate will be 5% at a total seven servers. It means that no matter S 1 or S 2 we add, they will have the same drop rate when the total number of servers are larger then seven. (b) Utilization Figure 7. RC hit rate and utilization 4.2 Drop Rate Comparison When the server reaches its service capacity but the load balancer still redirects the client request to that server, the request will be dropped. An optimal load balancing Figure 9. Scalability with RR algorithm

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