Research Article
Intelligent Computation Offloading for IoT Applications in Scalable Edge Computing Using Artificial Bee Colony Optimization
Algorithm 2
ABC to offload computation to the edge/cloud.
| (1) | Step1: Initialization | | (2) | q ← # of employed bees, of onlooker bees | | (3) | dimension of problem | | (4) | Max. of iterations allowed | | (5) | Create an initial population using Equation (20) | | (6) | Evaluate the fitness of the population | | (7) | repeat | | (8) | Step 2: Employed bees’ phase | | (9) | | | (10) | whiledo | | (11) | Compute new solution using Equation (21) | | (12) | Compute the fitness value of new solution using Equation (23) | | (13) | if in a neighborhood then | | (14) | = , and | | (15) | else | | (16) | Increase by 1 | | (17) | end if | | (18) | | | (19) | end while | | (20) | Step 3: Onlooker bees’ phase | | (21) | | | (22) | whiledo | | (23) | Generate a random number such that | | (24) | Calculate the probability using Equation (22) | | (25) | ifthen | | (26) | Compute new solution using Equation (21) | | (27) | Compute the fitness value of new solution using Equation (23) | | (28) | if in a neighborhood then | | (29) | = , and | | (30) | else | | (31) | Increase by 1 | | (32) | end if | | (33) | end if | | (34) | | | (35) | | | (36) | ifthen | | (37) | | | (38) | end if | | (39) | end while | | (40) | Step 4: Scout bees’ phase | | (41) | ifthen | | (42) | Initialize randomly chosen solution using Equation (20) | | (43) | end if | | (44) | Step 5: Memorize the best solution achieved so far | | (45) | until maximum cycle number reached | | (46) | Output the best solution identified |
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