Mobile Fog Computing by Using SDN/NFV on 5G Edge Nodes

Abstract

Fog computing provides quality of service for cloud infrastructure. As the data computation intensifies, edge computing becomes difficult. Therefore, mobile fog computing is used for reducing traffic and the time for data computation in the network. In previous studies, software-defined networking (SDN) and network functions virtualization (NFV) were used separately in edge computing. Current industrial and academic research is tackling to integrate SDN and NFV in different environments to address the challenges in performance, reliability, and scalability. SDN/NFV is still in development. The traditional Internet of things (IoT) data analysis system is only based on a linear and time-variant system that needs an IoT data system with a high-precision model. This paper proposes a combined architecture of SDN and NFV on an edge node server for IoT devices to reduce the computational complexity in cloud-based fog computing. SDN provides a generalization structure of the forwarding plane, which is separated from the control plane. Meanwhile, NFV concentrates on virtualization by combining the forwarding model with virtual network functions (VNFs) as a single or chain of VNFs, which leads to interoperability and consistency. The orchestrator layer in the proposed software-defined NFV is responsible for handling real-time tasks by using an edge node server through the SDN controller via four actions: task creation, modification, operation, and completion. Our proposed architecture is simulated on the EstiNet simulator, and total time delay, reliability, and satisfaction are used as evaluation parameters. The simulation results are compared with the results of existing architectures, such as software-defined unified virtual monitoring function and ASTP, to analyze the performance of the proposed architecture. The analysis results indicate that our proposed architecture achieves better performance in terms of total time delay (1800 s for 200 IoT devices), reliability (90%), and satisfaction (90%).

Delay Reduction in MTC Using SDN Based Offloading in Fog Computing

“…Fog nodes can provide resources for different requests and avoid resource competition since VRs can generate an isolated environment for each type of request [8,21]. In the heterogeneity MTC requests, integration of the Fog technology using virtualization is scalable and flexible for computation and improving efficiency in networks [22].…”

Fast Verification of Network Configuration Updates

“…Currently, some scholars have done verification work or network optimization for the verification of the control plane and data plane for traditional networks or SDN [20,21]. Among them, Chhabra et al [22] validated the strategy in a federated cloud environment.…”

Mathematical model for forwarding packets in communication network

“…a. Arrival packets at the i th vEdge router as a hyperexponential distribution with the rate λ i b. Packet switching time of the i th vEdge router comes in line with a hypo-exponential distribution with the rate μ i as shown in (17):…”

“…In line with the above mentioned, this paper tries to apply a precise queuing system of packet forwarding performance on SD‐WAN by using a phase‐type distribution to help reduce packet queues and congestion of networks. For achieving this, first, the proposed software defined‐WAN was deployed in four plans as follows: data, control, management and orchestration plans [17]. Then, we built a model of the packet forwarding of each vEdge router and the SD‐WAN controller, upon implementing it into their queuing parameters.…”