I. INTRODUCTION  
A. IoT drives Cloud Computing to Edge Computing-Artificial Intelligence  
B. Motivation for this Survey  
C. Existing Surveys and Reviews  
D. Contributions of this survey  
E. Survey Organization  

II. CONCEPTUAL BACKGROUND  
B. Different Edge Computing Architectures  
C. IoT concept, Structure, Protocols and Requirements  
D. AI Algorithms, Framework in an IoT-EC-CC Environment  
E. Evolutionary Algorithms  
F. Summary  

III. PARTITIONING IN IOT-EC-CC-AI  
A. Data Partitioning  
B. Computation Task Partitioning  
C. DNN Model Partitioning  

V. FUTURE RESEARCH DIRECTIONS  
A. Subtask Property for Computation Task Partitioning  
C. Lightweight Virtualization for Heterogeneous IoT Structures  
D. Standardized APIs  
E. Deep Reinforcement Learning(DRL) Algorithm in Designing Task Partitioning Policy  

VI. CONCLUSION