Soft-Safe: Software Defined Safety-as-a-Service for Intelligent Transportation System

In this work, we propose Soft-Safe, a Software Defined Safety-as-a-Service (Safe-aaS) model for provisioning safety-related decisions to the registered end-users. In Safe-aaS, the end-users register to the infrastructure, provide their initial and destination location, select certain decision parameters, and make payment through a Web portal. As the safety-related decisions are time-critical in nature, therefore timely delivery of these decisions is essential. Considering these facts and road transportation as the application scenario of Safe-aaS, we address the problem of efficient decision delivery to the end-users in two stages. In the first stage, we propose a Software Defined Safe-aaS platform to address the problems of heterogeneity among the SDN switches present in the edge layer. Further, based on the utility of each of the SDN switches present within the vicinity of the end-users, we optimally select a suitable SDN switch among the available ones, for delivering them decisions in the second stage. To obtain the maximum utility for delivering decisions to the end-users, we map the interactions between the SDN controller and SDN switches as a Non-cooperative Single Leader Multiple Follower game. Then, we estimate the optimal delay incurred by an SDN switch applying the Lagrangian function and Karush-Kuhn-Tucker (KKT) conditions. Exhaustive simulation results illustrate that the energy consumed and delay incurred using our proposed scheme, Soft-Safe, is reduced compared to the existing schemes, Traditional Safe-aaS and MoRule.

Automated summary

In this paper, Soft-Safe, a Software Defined Safety-as-a-Service (Safe-aaS) model, is proposed to provide safety-related decisions to registered end-users. The model addresses the problem of efficient decision delivery through a two-stage solution, reducing energy consumption and delay compared to existing schemes.