Performance Optimization of Cloud Data Centers with a Dynamic Energy-Efficient Resource Management Scheme

Table 3

Improved Salp Swarm Algorithm proposed to obtain the optimal sleep parameters.

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Step 1. Initialize the number of salps, maximum iteration for each salp’s position, initial inertia weight , inertia weight at the maximum iteration, upper search boundary , and lower Search boundary .

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Step 2. Initialize the position for each salp by using a chaotic equation:

     .

   % represents random numbers that obey uniform distribution between .%

     for

   % is a given real parameter.%

   endfor

   for

   endfor

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Step 3. Calculate the fitness for each salp:

   .

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Step 4. Select the best position among all the salps as the source food and calculate the fitness of the source food:

   ,

   .

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Step 5. Set the initial number of iterations as .

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Step 6. Update the coefficient and inertia weight with a nonlinear decreasing function:

   ,

   .

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Step 7. Update the position and calculate the fitness for other salps.

   for

    if

     ,

    else

    end if

   end for

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Step 8. Update the source food and calculate the fitness of the source food:

    ,

    .

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Step 9. Check the number of iterations:

    if

     , go to Step 6

    endif

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Step 10. Output the optimal sleep parameter and the minimum cost .

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