Software Defined Wide Area Networks: Current Challenges and Future Perspectives

Abstract

Software Defined Wide Area Network (SD-WAN) is rapidly becoming an attractive solution for enterprise networks as it offers several benefits such as cost efficiency, increased bandwidth, and improved application performance. However, SDWAN also brings new challenges that must be addressed for effective deployment (i.e. openness, interoperability, network automation, monitoring, QoS guarantees, scalability and security). In this paper, we highlight the criticalities of this technology and analyze the solutions proposed by the state of the art. We then present a scalable framework based on distributed Reinforcement Learning agents for guaranteeing availability and QoS to business applications. We believe that our work provides valuable insights into the opportunities and challenges of SD-WAN technology and offers new perspectives for future research in this area.