Biblio

With the increasing diversity of application needs (datacenters, IoT, content retrieval, industrial automation, etc.), new network architectures are continually being proposed to address specific and particular requirements. From a network management perspective, it is both important and challenging to enable evolution towards such new architectures. Given the ubiquity of the Internet, a clean-slate change of the entire infrastructure to a new architecture is impractical. It is believed that we will see new network architectures coming into existence with support for interoperability between separate architectural islands. We may have servers, and more importantly, content, residing in domains having different architectures. This paper presents COIN, a content-oriented interoperability framework for current and future Internet architectures. We seek to provide seamless connectivity and content accessibility across multiple of these network architectures, including the current Internet. COIN preserves each domain's key architectural features and mechanisms, while allowing flexibility for evolvability and extensibility. We focus on Information-Centric Networks (ICN), the prominent class of Future Internet architectures. COIN avoids expanding domain-specific protocols or namespaces. Instead, it uses an application-layer Object Resolution Service to deliver the right "foreign" names to consumers. COIN uses translation gateways that retain essential interoperability state, leverages encryption for confidentiality, and relies on domain-specific signatures to guarantee provenance and data integrity. Using NDN and MobilityFirst as important candidate solutions of ICN, and IP, we evaluate COIN. Measurements from an implementation of the gateways show that the overhead is manageable and scales well.

We have recently seen an increasing number of attacks that are distributed, and span an entire wide area network (WAN). Today, typically, intrusion detection systems (IDSs) are deployed at enterprise scale and cannot handle attacks that cover a WAN. Moreover, such IDSs are implemented at a single entity that expects to look at all packets to determine an intrusion. Transferring copies of raw packets to centralized engines for analysis in a WAN can significantly impact both network performance and detection accuracy. In this paper, we propose Jaal, a framework for achieving accurate network intrusion detection at scale. The key idea in Jaal is to monitor traffic and construct in-network packet summaries. The summaries are then processed centrally to detect attacks with high accuracy. The main challenges that we address are (a) creating summaries that are concise, but sufficient to draw highly accurate inferences and (b) transforming traditional IDS rules to handle summaries instead of raw packets. We implement Jaal on a large scale SDN testbed. We show that on average Jaal yields a detection accuracy of about 98%, which is the highest reported for ISP scale network intrusion detection. At the same time, the overhead associated with transferring summaries to the central inference engine is only about 35% of what is consumed if raw packets are transferred.

As demand for wireless mobile connectivity continues to explode, cellular network infrastructure capacity requirements continue to grow. While 5G tries to address capacity requirements at the radio layer, the load on the cellular core network infrastructure (called Enhanced Packet Core (EPC)) stresses the network infrastructure. Our work examines the architecture, protocols of current cellular infrastructures and the workload on the EPC. We study the challenges in dimensioning capacity and review the design alternatives to support the significant scale up desired, even for the near future. We breakdown the workload on the network infrastructure into its components-signaling event transactions; database or lookup transactions and packet processing. We quantitatively show the control plane and data plane load on the various components of the EPC and estimate how future 5G cellular network workloads will scale. This analysis helps us to understand the scalability challenges for future 5G EPC network components. Other efforts to scale the 5G cellular network take a system view where the control plane is separated from the data path and is terminated on a centralized SDN controller. The SDN controller configures the data path on a widely distributed switching infrastructure. Our analysis of the workload informs us on the feasibility of various design alternatives and motivates our efforts to develop our clean-slate approach, called CleanG.