# A Dynamic Load Balancing Algorithm For Web Applications

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2 some jobs that are stored in the network load balancer and will be distributed to the servers later. In this algorithm there are two parameters that play important role in distribution of jobs. These parameters are: LBQ (Load Balancing Queue) The LBQ is the parameter that is used to decide how many jobs will be stored in the network load balancer to be distributed in the next stage. The value of LBQ is calculated through the formula: LBQ = (LBQ+NUMBER OF JOBS) %NUMBER OF SERVERS. LBD (Load Distributed) The LBD is the parameter that is used to decide how many jobs will be distributed among the servers at every stage. The value of LBD is calculated through the formula: LBD = (LBQ+NUMBER OF JOBS) /NUMBER OF SERVERS. C. Traffic Served After the calculation of LBD and LBQ the traffic amount that is calculated from LBD is distributed among the servers. Each server will serve the requested traffic according to the number of jobs it can serve per unit of time. After this time the remainder jobs will be sent back to the network load balancer and will be added to the LBQ. By the end of the serve the number of stages is incremented by 1 and the number of serve for each server is incremented by 1. The formula for calculating the utilization is: Utilization of server= number of serves /number of stages. Step7. Utilization of server= number of serves /number of stages. 4. FLOWCHART OF PROPOSED ALGORITHM The flowchart for the dynamic load balancing algorithm has been shown in fig. 2 Fig 1. Block diagram of the proposed algorithm 3. STEPS OF THE ALGORITHM The different steps involved in the algorithm are: Step1: Enter the number of processes, arrival time of each process and the for each process. Step 2: Specify the number of servers and the they can serve per unit time. Initialize LBQ = 0, LBD = 0 and clock = 0. Step3. Repeat steps 4 to 6 till clock is less than Step4. If clock = arrival time (i) LBQ = (LBQ + Number of Jobs) %Number of Servers. (ii) LBD = (LBQ + Number of Jobs) /Number of Servers. (iii) Distribute the LBD values among the servers. After one unit of time the remaining job at the servers is sent back to the LBQ. Else go to step 5. Step5. Check LBQ and distribute the available jobs to the servers. Step6. Serve for each server = Serve for each server + 1. No. of stages = No. of stages + 1. Fig 2. Flow chart for the proposed algorithm 5. EXPERIMENTAL EVALUATION In t his project C#.net 2005 has been used for implementing the proposed algorithm. The algorithm has been checked for a number of inputs and results of five of them are shown here. Different values of the parameters have been taken to see the effect of each parameter on the algorithm Experiment 1 In this experiment the utilization of each server has been investigated by fixing the number of the jobs that each server can serve per unit of time and changing the of each process. We considered the arrival time for each process as given in table 1 with a time difference of 10 units

3 A Dynamic Load Balancing Algorithm For Web Applications Table1: Arrival Time of processes The that can be served by each server per unit time is given in table 2. Table2: Number of jobs served by each server We noted that as the increases the utilization of each server also increases proportionally. Because Server 3 can serve maximum number of the jobs per unit time so server 3 has best utilization. Table 3 shows the results of the experiment as utilization of different servers with changing load. The same result is also shown in the graphical form in Fig. 3. Table3. Utilization of different servers as the number of jobs Varies Fig.3:.The relation between utilization of each server and Experiment 2 In this experiment we investigated the utilization of each server when the processes are arriving at a constant time difference of one unit as shown in table 4 Table4: Arrival Time of processes The that can be served by each server per unit time is given in table 5. Table5: Number of jobs served by each server Fig 4: The relation between utilization of each server and Experiment 3 In this experiment we have considered that all the servers are at par and hence can serve equal per unit of time. We have taken this value to be equal to 2 jobs per unit time and have also taken the arrival times of different processes as 10, 11 and 12 respectively Again we note that the utilization increases with the increase in the. In this experiment, as all the servers can serve same number of jobs per unit time so they all have same utilization. We again note that the utilization increases in proportion to the served. Because Server 3 can serve maximum number of the jobs per unit time so server 3 has best utilization

4 Number of jobs in process 2=209 Number of jobs in process 3=159 We noted that the utilization is again proportionally increasing with the increase in the. Fig 5: The relation between utilization of each server and Experiment 4 In this experiment we investigated the utilization of each server by fixing the for each process and changing the number of the jobs that each serve can serve per unit time. We consider the arrival time for each process and the in each process as follows Arrival time for process 1 =10 Arrival time for process 2=11 Arrival time for process 3=12 Number of jobs in process 1=52 Table 6: Relationship between the that a server can serve per unit time and the utilization. Fig 6: The relation between utilization of each server and no. of jobs each server can serve. Arrival time for process 3=12 Number of jobs in process 1=52 Number of jobs in process 2=209 Number of jobs in process 3=159 We noted that the relation between the each server can serve per unit time and the number of stages is inversely proportional Experiment 5 In this experiment we investigated the number of stages in which the load balancer in able to complete the total distribution and execution of processes when the number of jobs for each process is fixed and the serving capacity of each server changes. The arrival time of the processes were considered as follows Arrival time for process 1 =10 Arrival time for process 2=11 Fig. 7: The relation between each server can serve per unit time and number of stages Continued on Page No. 180

5 A Dynamic Load Balancing Algorithm For Web Applications Continued from Page No. 176 Table 7: Results obtained from experiment number 5. No No of jobs can be serve per unit of time For each server Stages CONCLUSION In this paper we have discussed a new algorithm of load balancing. Preliminary results show that this algorithm has the potential to significantly improve fairness of load balancing between the servers when ever the traffic is coming. The capacity of the server is of major importance in the serving of traffic request. The fairness is very important to increase the performance of the system as well as it gives out all the clients request in shortest time and help the system to be scalable. 7.0 REFERENCES [1]. K. G. Coffman,A. M. Odlyzko: Internet growth: Is there a Moore s Law for data Traffic,AT&T Labs Research, Revised version, June 4, [2]. Eitan Altman, Urtzi Ayesta and Balakrishna Prabhu, Load Balancing in Processor Sharing Systems Proceedings of the 3rd International Conference on Performance Evaluation Methodologies and Tools, October 20-24, 2008, Athens, Greece. [3]. M. Livny and M. Melman, Load balancing in homogeneous broadcast distributed systems, in Proc. Conj Performance, ACM, 1982, pp [4]. load_balance_types. htm

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