Table 2.
Comparison of our survey to current state-of-the-art surveys.
| References | Summary | SLR | EC | FL | CS | HWR | FRD |
|---|---|---|---|---|---|---|---|
| [7] | Survey on architecture and computation offloading in MEC | X | √ | X | √ | X | √ |
| [25] | Survey on convergence of the intelligent edge and edge intelligence | X | √ | X | √ | √ | √ |
| [62] | Communication and networking issues being addressed by DRL | √ | √ | X | X | X | √ |
| [33] | Survey on fog computing and related edge computing paradigms | X | √ | X | X | X | √ |
| [6] | Survey on the integrated management of mobile computing and wireless communication resources in MEC | X | √ | X | √ | X | √ |
| [63] | Edge intelligence architectures and frameworks’ survey | X | √ | X | X | X | √ |
| [64] | Survey on edge intelligence specifically for 6G networks | X | √ | X | √ | X | √ |
| [65] | Management of IoT systems, e.g., network security and management by leveraging ML | X | √ | X | √ | X | X |
| [66] | Survey on computation offloading approaches in mobile edge computing | √ | √ | X | √ | X | √ |
| [67] | Survey on techniques for computation offloading | X | √ | X | X | X | X |
| [68] | Survey on architectures and applications of MEC | X | √ | X | √ | X | √ |
| [69] | Survey on computation offloading modeling for edge computing | X | √ | X | X | X | √ |
| [70] | A MEC survey on computing, caching, and communications | X | √ | X | √ | X | √ |
| [71] | Comparative study of caching phases and caching schemes | X | √ | X | X | X | √ |
| [72] | Survey on MEC for the 5G network architecture | X | √ | X | X | X | X |
| [80] | Survey on the data privacy and security of FL | X | X | √ | X | X | √ |
| [81] | Survey on FL applications in industrial engineering and computer science | X | X | √ | √ | X | √ |
| [61] | Survey on FL research from five perspectives: data partition, privacy techniques, relevant ML models, communication architecture, and heterogeneity solutions | X | X | √ | X | X | √ |
| [82] | Proposed an FL building block taxonomy with six different aspects: data distribution, ML model, privacy mechanism, communication architecture, the scale of the federation, and the motivation for FL | √ | X | √ | √ | X | √ |
| [19] | Tutorial on FL challenges | X | X | √ | X | X | √ |
| [18] | Overview of current research trends and relevant challenges | X | X | √ | X | X | √ |
| [83] | Discussed the opportunities and challenges in FL | X | X | √ | √ | X | X |
| [84] | described the existing FL and proposed an architecture of FL systems | X | X | √ | X | X | √ |
| [17] | Described the different FL settings in more detail, emphasizing their architecture and categorization | X | X | √ | X | X | X |
| [85] | Discussion on the applicability of FL in smart city sensing | X | X | √ | √ | X | √ |
| [86] | Survey on the security threats and vulnerability challenges in FL systems | X | X | √ | X | X | √ |
| [87] | Summarized the most used defense strategies in FL | X | X | √ | X | X | X |
| [88] | Developed protocols and platforms to help industries in need of FL build privacy-preserving solutions | X | X | √ | √ | X | X |
| [89] | Performed a systematic literature review on FL from the software engineering perspective | √ | X | √ | X | X | √ |
| [90] | Highlighted FL’s applications in wireless communications | X | X | √ | X | X | √ |
| [50] | Discussed the basics and problems of FL for edge networks | X | √ | √ | √ | X | √ |
| [91] | Analysis of FL from the 6G communications perspective | X | X | √ | X | X | √ |
| [92] | Survey on FL-powered IoT applications to run on IoT networks | X | √ | √ | X | X | √ |
| [93] | Survey on the FL-enabled IIoT | X | √ | √ | √ | X | √ |
| [94] | Survey on FL implementation in wireless communications | X | X | √ | X | X | √ |
| [95] | Analysis of FL’s potential for enabling a wide range of IoT services | X | √ | √ | √ | X | √ |
| [96] | FDL application for UAV-enabled wireless networks | X | √ | √ | √ | X | √ |
| [97] | Survey on the implementation of FL and challenges | X | √ | √ | X | X | √ |
| [98] | Review of FL for vehicular IoT | X | √ | √ | √ | X | √ |
| [99] | Survey on FL for the future of digital health | X | √ | √ | √ | X | √ |
| [100] | Survey on applications of FL to autonomous robots | X | √ | √ | √ | X | √ |
| [101] | Review of FL technologies within the biomedical space and the challenges | X | √ | √ | √ | X | √ |
| [102] | A tutorial on FL in the domain of communication and networking | X | √ | √ | X | √ | √ |
| [65] | Analysis and design of heterogeneous federated learning | X | X | √ | X | X | √ |
| Our Paper | A systematic review on FL implementation in the EC paradigm | √ | √ | √ | √ | √ | √ |
Note: √ = does include; CS: Case Studies; X = does not include; HWR: Hardware Requirements; SLR: Systematic Literature Review; FRD: Future Research Directions; EC: Edge Computing; FL: Federated Learning.