  Today's intelligent computing environments, including Internet of Things,
cloud computing and fog computing, allow many organizations around the world to
optimize their resource allocation regarding time and energy consumption. Due
to the sensitive conditions of utilizing resources by users and the real-time
nature of the data, a comprehensive and integrated computing environment has
not yet been able to provide a robust and reliable capability for proper
resource allocation. Although, traditional methods of resource allocation in a
low-capacity hardware resource system are efficient for small-scale resource
providers, for a complex system in the conditions of dynamic computing
resources and fierce competition in obtaining resources, they do not have the
ability to develop and adaptively manage the conditions optimally. To solve
this problem, computing intelligence techniques try to optimize resource
allocation with minimal time delay and energy consumption. Therefore, the
objective of this research is a comprehensive and systematic survey on resource
allocation problems using computational intelligence methods under Game Theory
and Evolutionary-optimization in emerging computing environments, including
cloud, fog and Internet of Things according to the latest scientific-research
achievements.
