Study QoS Optimization and Energy Saving Techniques in Cloud, Fog, Edge, and IoT

Table 3

Work summary of resource allocation and management in fog computing.

Problems	Solutions	Literatures	Advantages
Task allocation	A new model of scheduling jobs and a redistribution mechanism	[49]	Finishes jobs on time, optimizes the number of tasks, and shortens the delay of tasks
Resource allocation	A framework to administrate resources and a method to predict and administrate resources	[50]	Assists service providers to predict the amount of available resources based on different types of service customers and deals with the phenomenon that objects or devices withdraw from resource utilization at any time
	A bi-matching approach	[51]	Improves the performance of the system and obtains higher cost efficiency
	A framework for joint optimization	[52]	Optimizes resource allocation and improves network performance
	A method to allocate computing and communication resources	[53]	Allocates computing and communication resources, transfers computing jobs to remote cloud and nodes, simplifies edge nodes’ computing, and saves computing energy
	A platform to allocate resources accessible to client devices	[54]	Enables rapid response to computing resources and allocates the resources of devices near the host
	A framework to manage resources	[55]	Considers the fluctuation of the customer abandonment probability and service types
Low latency	A distributed algorithm	[5]	Solves the problem of wide range optimization and allocates resources jointly