GMOM: An Offloading Method of Dependent Tasks Based on Deep Reinforcement Learning

Table 2

Training process of the GMOM model.

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Algorithm GMOM

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(1) Initialize the initial network parameter that the actor network and the critic network share randomly

(2) Initialize the parameter of the old actor network with

(3) For iteration = 1, 2, … do

(4)  for t = 1, 2, …, N do

(5)   for i = 1, 2, …, D do

(6)    the whole episode is collected with the old actor network, and the obtained data is stored in the experience pool D

(7)    calculate the GAE function value for each time step according to formula (14), get and cache it

(8)    calculate the value in each state according to formula (17) and get

(9)   end

(10)   for j = 1, 2, …, H do

(11)   sample batch size sample data to optimize the objective function, update the actor network

(12)   end

(13)   Synchronize the parameters of two actor networks, i.e.,

(14)  end

(15) end

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