1,296 research outputs found

    The Potential of Flexible UL/DL Slot Assignment in 5G Systems

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    Stats 101 in P4: Towards In-Switch Anomaly Detection

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    Data plane programmability is greatly improving network monitoring. Most new proposals rely on controllers pulling information (e.g., sketches or packets) from the data plane. This architecture is not a good fit for tasks requiring high reactivity, such as failure recovery, attack mitigation, and so on. Focusing on these tasks, we argue for a different architecture, where the data plane autonomously detects anomalies and pushes alerts to the controller. As a first step, we demonstrate that statistical checks can be implemented in P4 by revisiting definition and online computation of statistical measures. We collect our techniques in a P4 library, and showcase how they enable in-switch anomaly detection

    Fast ReRoute on Programmable Switches

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    Highly dependable communication networks usually rely on some kind of Fast Re-Route (FRR) mechanism which allows to quickly re-route traffic upon failures, entirely in the data plane. This paper studies the design of FRR mechanisms for emerging reconfigurable switches. Our main contribution is an FRR primitive for programmable data planes, PURR, which provides low failover latency and high switch throughput, by avoiding packet recirculation. PURR tolerates multiple concurrent failures and comes with minimal memory requirements, ensuring compact forwarding tables, by unveiling an intriguing connection to classic ``string theory'' (i.e., stringology), and in particular, the shortest common supersequence problem. PURR is well-suited for high-speed match-action forwarding architectures (e.g., PISA) and supports the implementation of a broad variety of FRR mechanisms. Our simulations and prototype implementation (on an FPGA and a Tofino switch) show that PURR improves TCAM memory occupancy by a factor of 1.5x-10.8x compared to a naïve encoding when implementing state-of-the-art FRR mechanisms. PURR also improves the latency and throughput of datacenter traffic up to a factor of 2.8x-5.5x and 1.2x-2x, respectively, compared to approaches based on recirculating packets

    Multi-controller Based Software-Defined Networking: A Survey

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    Software-Defined Networking (SDN) is a novel network paradigm that enables flexible management for networks. As the network size increases, the single centralized controller cannot meet the increasing demand for flow processing. Thus, the promising solution for SDN with large-scale networks is the multi-controller. In this paper, we present a compressive survey for multi-controller research in SDN. First, we introduce the overview of multi-controller, including the origin of multi-controller and its challenges. Then, we classify multi-controller research into four aspects (scalability, consistency, reliability, load balancing) depending on the process of implementing the multi-controller. Finally, we propose some relevant research issues to deal with in the future and conclude the multi-controller research

    Wireless Communications in the Era of Big Data

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    The rapidly growing wave of wireless data service is pushing against the boundary of our communication network's processing power. The pervasive and exponentially increasing data traffic present imminent challenges to all the aspects of the wireless system design, such as spectrum efficiency, computing capabilities and fronthaul/backhaul link capacity. In this article, we discuss the challenges and opportunities in the design of scalable wireless systems to embrace such a "bigdata" era. On one hand, we review the state-of-the-art networking architectures and signal processing techniques adaptable for managing the bigdata traffic in wireless networks. On the other hand, instead of viewing mobile bigdata as a unwanted burden, we introduce methods to capitalize from the vast data traffic, for building a bigdata-aware wireless network with better wireless service quality and new mobile applications. We highlight several promising future research directions for wireless communications in the mobile bigdata era.Comment: This article is accepted and to appear in IEEE Communications Magazin

    Mapping applications onto FPGA-centric clusters

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    High Performance Computing (HPC) is becoming increasingly important throughout science and engineering as ever more complex problems must be solved through computational simulations. In these large computational applications, the latency of communication between processing nodes is often the key factor that limits performance. An emerging alternative computer architecture that addresses the latency problem is the FPGA-centric cluster (FCC); in these systems, the devices (FPGAs) are directly interconnected and thus many layers of hardware and software are avoided. The result can be scalability not currently achievable with other technologies. In FCCs, FPGAs serve multiple functions: accelerator, network interface card (NIC), and router. Moreover, because FPGAs are configurable, there is substantial opportunity to tailor the router hardware to the application; previous work has demonstrated that such application-aware configuration can effect a substantial improvement in hardware efficiency. One constraint of FCCs is that it is convenient for their interconnect to be static, direct, and have a two or three dimensional mesh topology. Thus, applications that are naturally of a different dimensionality (have a different logical topology) from that of the FCC must be remapped to obtain optimal performance. In this thesis we study various aspects of the mapping problem for FCCs. There are two major research thrusts. The first is finding the optimal mapping of logical to physical topology. This problem has received substantial attention by both the theory community, where topology mapping is referred to as graph embedding, and by the High Performance Computing (HPC) community, where it is a question of process placement. We explore the implications of the different mapping strategies on communication behavior in FCCs, especially on resulting load imbalance. The second major research thrust is built around the hypothesis that applications that need to be remapped (due to differing logical and physical topologies) will have different optimal router configurations from those applications that do not. For example, due to remapping, some virtual or physical communication links may have little occupancy; therefore fewer resources should be allocated to them. Critical here is the creation of a new set of parameterized hardware features that can be configured to best handle load imbalances caused by remapping. These two thrusts form a codesign loop: certain mapping algorithms may be differentially optimal due to application-aware router reconfiguration that accounts for this mapping. This thesis has four parts. The first part introduces the background and previous work related to communication in general and, in particular, how it is implemented in FCCs. We build on previous work on application-aware router configuration. The second part introduces topology mapping mechanisms including those derived from graph embeddings and a greedy algorithm commonly used in HPC. In the third part, topology mappings are evaluated for performance and imbalance; we note that different mapping strategies lead to different imbalances both in the overall network and in each node. The final part introduces reconfigure router design that allocates resources based on different imbalance situations caused by different mapping behaviors
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