LOAD BALANCING IN A CENTRALIZED DISTRIBUTED SYSTEM

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LOAD BALANCING IN A CENTRALIZED DISTRIBUTED
SYSTEM

• BY
• ANILA JAGANNATHAM
• ELENA HARRIS

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OUTLINE

• PROBLEM STATEMENT
• ARCHITECTURE
• LOAD BALANCING METHODS
• EXPERIMENTAL RESULTS
• CONCLUSION

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PROBLEM STATEMENT

• To study different load balancing methods in
  order to improve CPU utilization and overall
  execution time of requests in a centralized
  distributed system with an environment that
  requires extensive calculations.

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ARCHITECTURE

• MASTER SLAVE ARCHITECHTURE
• CENTRALIZED CLIENT ACTS AS THE MASTER MACHINE
• SERVERS ACT AS SLAVES
• SOCKETS ARE USED FOR COMMUNICATION

SERVER
SERVER
SERVER
CLIENT
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LOAD BALANCING APPROACHES

• RANDOM LOAD BALANCING
• Requests are routed to servers at random.
  Used for homogeneous systems.
• ROUND ROBIN LOAD BALANCING
• Simple and no overhead
• Load may not be evenly balanced in the
  system
• CPU UTILIZATION BASED LOAD BALANCING
• Client queries CPU utilization of each of
  the servers and chooses the least loaded server
  to assign incoming user request.

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CPU UTILIZATION METRIC

• Client requests statistics from /proc/stat file
  maintained by each server to estimate current CPU
  utilization.
• Statistics from /proc/stat
• Total time spent by the CPU on all processes
• Total number of processes
  running.
• Average time per process, ?T / ?P is used as
  metric
• ?T Difference in CPU time at two time
  points
• ?P Difference in number of processes at
  two time points
• The larger ?T / ?P, the less loaded a CPU is.

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USER APPLICATIONS

• Four applications are chosen to simulate user
  requests.
• Run time of these applications is
• 8 min , 3 min, 30 sec and 3 sec
  respectively.
• Client has dual functionality
• - Generates user requests
• - Performs load balancing.

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EXPERIMENTAL RESULTS

?T/?P
TIME PERIODS
RANDOM LOAD BALANCING
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?T/?P
TIME PERIODS
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?T/?P
TIME POINTS
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EXPERIMENT -II

• In this experiment, 1000 tasks were distributed.
• From the graph, average time/process using the
  proposed method changes less drastically.

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CONCLUSION

• LOAD BALANCING USING CURRENT CPU AVERAGE
  TIME/PROCESS RESULTS IN BETTER OVERALL CPU
  UTILIZATION AS COMPARED TO RANDOM OR ROUND ROBIN
  METHODS.