Health-Flow: Criticality-Aware Flow Control for SDN-Based Healthcare IoT
Sudip Misra, Ruelia Saha, Nurzaman Ahmed · 2020
In this paper, we propose Health-Flow, a criticality-aware traffic forwarding scheme for mobile devices to maximize the efficiency of a software-defined healthcare network. The proposed scheme uses a machine learning-based approach to find the criticality of flows and the location of the mobile device. Concerning the criticality levels in traffic, the proposed protocol dynamically places or removes flow-rules at the edge access points. Consequently, it helps to take adequate actions for the incoming requests adaptively with improved network reconfiguration overhead, latency, and energy consumption. We mathematically formulate Integer Linear Programming for optimally selecting access points. We mathematically formulate the resource reallocation problem in terms of optimization by minimizing the network overhead subject to the packet flows' criticality requirements. The proposed scheme has the potential to reduce latency by 52%, overhead by 19%, and energy consumption by 12% as compared to the existing schemes.