Customer Premises Equipment (CPE) plays a fundamental role in enabling Software-Defined Wide Area Networks (SD-WANs) to support emerging applications such as Metaverse environments. These environments demand agile, secure, and high-performance network infrastructure to ensure seamless connectivity, low latency, and dynamic resource allocation. As the Metaverse continues to evolve, the need for flexible, efficient, and open CPE solutions becomes increasingly important. This paper presents an open-source SD-WAN CPE software designed to enhance network agility, scalability, and performance, specifically addressing the stringent requirements of next-generation Internet applications. The proposed solution supports deployment on both virtual machines and bare-metal systems, enabling seamless integration into diverse infrastructures. To achieve high-speed packet processing, it leverages the Data Plane Development Kit (DPDK), ensuring low-latency and high-throughput communication. Furthermore, it incorporates different overlay tunneling mechanisms, supporting both site-to-site and hub-and-spoke topologies via WireGuard tunneling technology for secure and efficient connectivity. A key feature of this implementation is its rapid failover capability, powered by Bidirectional Forwarding Detection (BFD), alongside real-time performance monitoring, enabling proactive network optimization and fault tolerance. By combining these advanced capabilities with an open-source framework, this SD-WAN CPE software provides a robust and cost-effective solution for next-generation network deployments.

Modern enterprises depend on uninterrupted WideArea Network (WAN) connectivity between geographically dispersed sites and cloud services. Software-Defined Wide Area Networks (SD-WANs) have emerged as a compelling solution, offering greater flexibility and cost-efficiency compared to conventional WAN technologies. Ensuring robust availability-defined as the network's readiness to provide connectivity-is crucial for a successful SD-WAN implementation. This work presents a comprehensive, model-based evaluation framework designed to quantify service-oriented availability between pairs of SDWAN endpoints. Our hierarchical modeling approach effectively addresses the complexity and accurately reflects the dependencies among various SD-WAN components. Furthermore, we investigate the impact of a centralized control plane and its associated non-idealities on availability, providing insights into communication delays, sampling frequency of network characteristics, and algorithm execution times through simulation. In-depth experiments demonstrate the evaluation capabilities of our framework, including sensitivity analysis to identify critical components, the effects of various non-idealities, and how different control plane policies can mitigate them. These results offer valuable guidance for optimizing SD-WAN design before real-world implementation.

Software-Defined Wide Area Networks (SD-WANs) provide flexibility and cost-efficiency but still face significant challenges in guaranteeing high availability and consistent performance, particularly when utilizing diverse internet access networks, especially if best-effort like broadband connectivity. Furthermore, reliance on centralized controllers can introduce bottlenecks and single points of failure. This paper outlines a PhD research roadmap aimed at developing a resilient, performant, and extensible SD-WAN framework. The proposed research starts with robust modeling of service-oriented availability considering control plane impacts and quality of service requirements. This will guide us through an availability-aware SD-WAN modular architecture with the function of simplifying the development and test of new features such as: strategies to enhance edge autonomy by reducing real-time controller dependency; integration of predictive awareness tailored to specific internet access networks as LEO satellite based; and experimenting advanced monitoring for intelligent and reactive edgebased traffic engineering. We present the research context, state-of-the-art limitations, core research questions, the methodology combining modeling, simulation, and prototype development, and the expected contributions towards next-generation SD-WAN architectures suitable for research and demanding enterprise applications.

Software-Defined Wide Area Networks (SD-WANs) have emerged as a transformative solution for modern enterprise networking, enabling dynamic traffic management, cost-efficient connectivity, and improved network performance. However, ensuring real-time visibility into network conditions remains a key challenge, as SD-WAN overlay tunnels operate over diverse and often unpredictable underlay networks. Traditional network monitoring techniques, such as active and passive monitoring, face limitations in balancing accuracy, responsiveness, and overhead. To address this challenge, we propose an In-Band Network Telemetry (INT) framework for SD-WANs, leveraging extended Berkeley Packet Filter (eBPF) technology for efficient and flexible packet processing. Our approach enables real-time telemetry data collection at the Customer Premises Equipment (CPE) level, allowing for precise performance monitoring while minimizing additional network overhead. The framework integrates seamlessly with various VPN-based SD-WAN tunnels, including Generic Routing Encapsulation (GRE), IP Security (IPSec), and IPSec over GRE, ensuring adaptability across different deployment scenarios. By embedding telemetry metadata directly into overlay packets, the proposed solution provides continuous monitoring of critical Quality of Service (QoS) metrics, such as One-Way Delay (OWD), Two-Way Delay (TWD), and packet loss rate. Through extensive experimentation, we demonstrate the effectiveness of our INT-enabled SD-WAN framework in accurately detecting network anomalies and ensuring Service-Level Agreement (SLA) compliance. The results validate our approach as a scalable and lightweight monitoring solution for enhancing network observability in SD-WAN deployments.