IEEE 802.11 WLANs are a very important technology to provide high speed wireless Internet access. Especially at airports, university campuses or in city centers, WLAN coverage is becoming ubiquitous leading to a deployment of hundreds or thousands of Access Points (AP). Managing and configuring such large WLAN deployments is a challenge. Current WLAN management protocols such as CAPWAP are hard to extend with new functionality. In this paper, we present CloudMAC, a novel architecture for enterprise or carrier grade WLAN systems. By partially offloading the MAC layer processing to virtual machines provided by cloud services and by integrating our architecture with OpenFlow, a software defined networking approach, we achieve a new level of flexibility and reconfigurability. In Cloud-MAC APs just forward MAC frames between virtual APs and IEEE 802.11 stations. The processing of MAC layer frames as well as the creation of management frames is handled at the virtual APs while the binding between the virtual APs and the physical APs is managed using OpenFlow. The testbed evaluation shows that CloudMAC achieves similar performance as normal WLANs, but allows novel services to be implemented easily in high level programming languages. The paper presents a case study which shows that dynamically switching off APs to save energy can be performed seamlessly with CloudMAC, while a traditional WLAN architecture causes large interruptions for users.Index Terms-Software Defined Networking, MAC Layer, Cloud GC'12 Workshop: The 8th Broadband Wireless Access Workshop 978-1-4673-4941-3/12/$31.00 ©2012 IEEE

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The Configuration and Management of large WLAN deployments is a challenge and available tools to ease such deployments and introduce new services are either commercial or very inflexible. In this paper, we present a different approach to such challenges called QoS enabled CloudMAC, which is to the best of our knowledge the first step towards QoS enabled WiFi MAC layer processing as an example of Network Function Virtualization. By moving the MAC layer processing to the cloud and integrating our architecture with QoS aware OpenFlow deployment, a software defined networking approach, we achieve a new level of flexibility, control and reconfigurability. CloudMAC Access Points (AP) just forward MAC layer frames towards a set of VMs (Virtual Access Points-VAP) that are responsible for processing MAC layer data and management frames (such as beacons, probe requests, etc). We have extended the SDN that connects the VAPs with the physical APs to support different packet prioritisation strategies such as HTB, SFQ, or FQ CoDel. Our SDN controller is based on OpenDaylight which creates layer 2 forwarding rules that effectively prioritise CloudMAC traffic over legacy traffic. Our evaluation in a real testbed shows that packet prioritization strategies, especially FQ CoDel, lead to good throughput and low latency for CloudMAC traffic while at the same time maintaining low latency for background traffic.

Providing network reliability as well as low and predictable latency is important especially for Industrial Automation and Control Networks. However, diagnosing link status from the control plane has high latency and overhead. In addition, the communication with the industrial controller may impose additional network latency. We present FastReact -a system enabling In-Network monitoring, control and caching for Industrial Automation and Control Networks. FastReact outsources simple monitoring and control actions to evolving programmable data planes using the P4 language. As instructed by the Industrial Controller through a Northbound API, the SDN controller composes control actions using Boolean Logic which are then installed in the data plane. The data plane parses and caches sensor values and performs simple calculations on them which are connected to fast control actions that are executed locally. For resiliency, FastReact monitors liveness and response of sensors/actuators and performs a fast local link repair in the data plane if a link failure is detected. Our testbed measurement show that FastReact can reduce the sensor/actuator delay while being resilient against several failure events.

In-Band Network Telemetry (INT) is a novel framework for collecting telemetry items and switch internal state information from the data plane at line rate. With the support of programmable data planes and programming language P4, switches parse telemetry instruction headers and determine which telemetry items to attach using custom metadata. At the network edge, telemetry information is removed and the original packets are forwarded while telemetry reports are sent to a distributed stream processor for further processing by a network monitoring platform. In order to avoid excessive load on the stream processor, telemetry items should not be sent for each individual packet but rather when certain events are triggered. In this paper, we develop a programmable INT event detection mechanism in P4 that allows customization of which events to report to the monitoring system, on a per-flow basis, from the control plane. At the stream processor, we implement a fast INT report collector using the kernel bypass technique AF XDP, which parses telemetry reports and streams them to a distributed Kafka cluster, which can apply machine learning, visualization and further monitoring tasks. In our evaluation, we use realworld traces from different data center workloads and show that our approach is highly scalable and significantly reduces the network overhead and stream processor load due to effective event pre-filtering inside the switch data plane. While the INT report collector can process around 3 Mpps telemetry reports per core, using event pre-filtering increases the capacity by 10-15x.