Distributed Bio-inspired Configuration of Virtualized Mission-critical Networks

Modern mission-critical embedded systems such as autonomous cars and avionics consist of a multitude of intercon-nected nodes and services with various QoS requirements. Virtu-alization provides further flexibility, configurability, and isolation to such systems by enabling dynamic service placement to off-the-shelf virtualized hardware. Although the service-oriented systems usually rely on a single centralized controller for the service configuration and maintenance as well as establishing their inter-communication, more autonomous and self-driven control schemes are required to cope with their increasing scalability and heterogeneity. Accordingly, bio-inspired algorithms (BIAs) offer distributed self-organization methods by adapting the natural phenomena such as collaborating bee and ant colonies for the requirements of modern networked systems. In this paper, we leverage ant-colony optimization to solve the joint service allocation and routing (JSAR) problem distributedly, where mixed-criticality services should be distributed and communicated under strict QoS requirements on a virtualized, physical network. We also introduce an integer linear program (ILP) to find the optimal solution for JSAR that can be computed by a centralized controller. Our experiments show that our heuristics successfully solve JSAR for even scaling scenarios. Besides, utilizing different redeployment strategies, they can be adapted to obtain near-optimal results in terms of resource efficiency.