Research Article

An Intelligent Adaptive Algorithm for Servers Balancing and Tasks Scheduling over Mobile Fog Computing Networks

Table 1

Main notations and corresponding explanations of the system model.

NotationExplanation

The number of fog servers
The number of cloud servers
The period duration of equal length time slots in a quasi-static system
The index of time period
The number of periods
The initial task data size in bit at the beginning of period
The task computation workload of CPU in cycle per bit
The task arrival rate in bit per second
The mean rate of task arrival rate in bit per second
The scheduled decision
The available computation capacity of end device in cycle per second
The operating computation frequency of end device in cycle per second
The computing operating power on the user device
The task computing rate on the user device
The ever-changing channel gain
The channel noise
The transmitting operating power on the user device
The transmitting rate of scheduled task
The task computing rate on the fog server
The processed data size in local computing mode during period
The processed data size in scheduled computing mode during period
The remaining data size at the end of period
The operating power on user device during period
The appended workload on server by scheduled task
The weighted sum cost of optimization problem
The weighting factors for adjusting the trade-off among the three factors