Efficient Resource Slicing Scheme for Optimizing Federated Learning Communications in Software-Defined IoT NetworksEfficient Resource Slicing Scheme for Optimizing Federated Learning Communications in Software-Defined IoT Networks
- Other Titles
- Efficient Resource Slicing Scheme for Optimizing Federated Learning Communications in Software-Defined IoT Networks
- Authors
- Prohim Tam; Sa Math; 김석훈
- Issue Date
- Oct-2021
- Publisher
- 한국인터넷정보학회
- Keywords
- Deep Learning; Federated Learning; Internet of Things; Network Functions Virtualization; Software-Defined Networking
- Citation
- 인터넷정보학회논문지, v.22, no.5, pp 27 - 33
- Pages
- 7
- Journal Title
- 인터넷정보학회논문지
- Volume
- 22
- Number
- 5
- Start Page
- 27
- End Page
- 33
- URI
- https://scholarworks.bwise.kr/sch/handle/2021.sw.sch/20034
- ISSN
- 1598-0170
- Abstract
- With the broad adoption of the Internet of Things (IoT) in a variety of scenarios and application services, management and orchestration entities require upgrading the traditional architecture and develop intelligent models with ultra-reliable methods. In a heterogeneous network environment, mission-critical IoT applications are significant to consider. With erroneous priorities and high failure rates, catastrophic losses in terms of human lives, great business assets, and privacy leakage will occur in emergent scenarios. In this paper, an efficient resource slicing scheme for optimizing federated learning in software-defined IoT (SDIoT) is proposed. The decentralized support vector regression (SVR) based controllers predict the IoT slices via packet inspection data during peak hour central congestion to achieve a time-sensitive condition. In off-peak hour intervals, a centralized deep neural networks (DNN) model is used within computation-intensive aspects on fine-grained slicing and remodified decentralized controller outputs. With known slice and prioritization, federated learning communications iteratively process through the adjusted resources by virtual network functions forwarding graph (VNFFG) descriptor set up in software-defined networking (SDN) and network functions virtualization (NFV) enabled architecture. To demonstrate the theoretical approach, Mininet emulator was conducted to evaluate between reference and proposed schemes by capturing the key Quality of Service (QoS) performance metrics.
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