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Approximation Algorithm for the NP-Complete problem of balancing job loads on machines. Does not guarantee an optimal solution, but instead, a solution is within a factor of 1.5 of the optimal solution

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Load Balancing Problem Approximation Algorithm

Approximation Algorithm for the NP-Complete problem of balancing job loads on machines. (Could be applied to processes management on a CPU). Does not guarantee an optimal solution, but instead, a solution is within a factor of 1.5 of the optimal solution.

Problem Statement

  • M identical machines
  • N jobs
  • Each jobs has processing time Tj
  • J(i) is the subset of jobs assigned to machine i
  • The load of machine i is Li = sum of the processing times for the jobs on that machine

Makespan = the maximum of the loads on the machines (the machine with the largest load)
Goal: Minimize the Makespan

Solution

Assign each job to a machine to minimize makespan
There are mn different assignments of n jobs to m machines, which is exponential

The greedy solution runs in polynomial time and gives a solution no more than 1.5 times the optimal makespan
Proof involves complicated sigma notation and can be found in the references

Sort jobs by largest processing time 1st & keep assigning jobs to the machine with the smallest load

Runtime

  • O(n log n) for sorting jobs by processing time
  • O(n log m) for Greedy Balance & assigning jobs to machines
  • O(n log n) + O(n log m)
  • ⇒ O(n log n)

Input Jobs

Jobs1 Inputs

Jobs1 Machine Assignments


Jobs2 Inputs

Jobs2 Machine Assignments


Jobs3 Inputs

Jobs3 Machine Assignments

Usage

Machine ID's are meaningless since machines are identical, they're created for readability.
But the algorithm still creates the job assignments on the machines according to the greedy strategy

  • int machineCount parameter is how many machines there are
  • int[][] jobs is a 2D array containing the jobs
    • jobs[i] is an array represents a job
    • jobs[i][0] is the Job Id or name
    • jobs[i][1] is the Processing time

Code Details

  • Unlike the pseudocode, the jobs assigned to a machine are inside the Machine object in the Priority Queue
  • 1st Creates M machines with unique Id's
  • Then loop over the jobs and assigns the job with the longest processing time to the machine with the smallest current load
    • Java's Priority Queue doesn't really have an IncreaseKey() method so the same effect is achieved by removing the machine from the Queue, updating the Machine's currentLoad and then adding the Machine back to the Queue
  • Machine class represents a machine
    • Some Important Parts of a Machine
    • id is the ID or name of the machine
    • currentLoad is the sum of the processing times of the jobs currently assigned to the machine
    • jobs is a 2D ArrayList containing the jobs currently assigned to the machine
    • Machine class overrides compareTo() from the Comparable interface so that the `PriotityQueue is always has the smallest load machine at the top

References

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Approximation Algorithm for the NP-Complete problem of balancing job loads on machines. Does not guarantee an optimal solution, but instead, a solution is within a factor of 1.5 of the optimal solution

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