A Review of Techniques and Methods for IoT Applications in Collaborative Cloud-Fog Environment

Table 1

Work summary of task offloading among fog and cloud.

Reference	Solution	Advantages
[23]	A generic IoT-fog-cloud architecture	Reduces energy consumption and request completion time
[14, 24]	A joint offloading method based on the existing fog-cloud framework	Takes various factors affecting the offloading as parameters to generate mixed-integer programming
[25]	An energy-saving offloading method	Uses random optimization technique to solve energy-saving offloading problem
[26]	A computation offloading method using blockchain	Offloads overloaded tasks to the suitable adjacent node with the optimal offloading strategy determined by simple additive weighting and multicriterion decision
[27]	An efficient online algorithm considering the unnecessary consumption of idle servers	Combines the computation offloading and sleep decisions of node servers to maximize server quality and reduces energy consumption
[28]	An optimal decision strategy with some reinforcement learning methods	Makes the fog node decide the processing location itself and realizes low-latency offloading and high-quality processing
[29]	An energy-efficient computing offload scheme	Proposes an accelerated gradient algorithm to find optimal offloading point with a high speed
[30]	An optimal collaboration scheme with low latency and energy consumption	Decomposes the load allocation problem into three subproblems by using approximation method
[31]	An extensible fog computing paradigm	Develops a distribution strategy based on genetic algorithm to enable the roadside nodes to offload computing tasks with the minimum cost