The emergence of Network Functions Virtualization (NFV) is being heralded as an enabler of the recent technologies such as 5G/6G, IoT and heterogeneous networks. Existing NFV monitoring frameworks either do not have the capabilities to express the range of telemetry items needed to perform management or do not scale to large traffic volumes and rates. We present IntOpt, a scalable and expressive telemetry system designed for flexible NFV monitoring using active probing and P4. IntOpt allows us to specify monitoring requirements for individual service chain, which are mapped to telemetry item collection jobs that fetch the required telemetry items from P4 programmable data-plane elements. We propose mixed integer linear program (MILP) as well as a simulated annealing based random greedy (SARG) meta-heuristic approach to minimize the overhead due to active probing and collection of telemetry items. Using P4-FPGA, we benchmark the overhead for telemetry collection. Our numerical evaluation shows that the proposed approach can reduce monitoring overheads by 39% and monitoring delays by 57%. Such optimization may as well enable existing expressive monitoring frameworks to scale for larger real-time networks.

Industrial Internet of Things (I-IoT) applications require a large number of sensor data to be processed under tight delay and jitter constraints. In such applications, flexible event detection and fast reaction to critical events is an important building block. Traditional approaches use either proprietary networks and dedicated hardware or transmit sensor data towards processing elements in the Cloud or at the Network Edge, using distributed stream processing frameworks. For scalability, a large number of servers are needed and processing on commodity CPUs typically involves high and unpredictable latency. In this article, we explore how programmable data planes can be used to detect events flexibly and trigger customized and programmable actions directly from the switch program or the programmable network interface card (SmartNIC). We present FastReact-PS, an event-based publish/subscribe I-IoT processing framework in P4 language, which can be flexibly customized from the control plane. Together with stateful processing, FastReact-PS supports windowed time series analysis as well as complex event detection and processing based on Boolean logic directly in the data plane of newly emerging programmable networking devices. The logic can be adjusted dynamically from the control plane without the need for recompilation. We implement FastReact-PS in P4 and evaluate it on both a SmartNIC and a DPDK-based software switch running in user space. Our evaluation shows that the latency is reduced by one order of magnitude compared to end-host based approaches at significantly lower jitter while being scalable to processing up to 11 million events per second.

Managing and scaling virtual network function (VNF) service chains require the collection and analysis of network statistics and states in real time. Existing network function virtualization (NFV) monitoring frameworks either do not have the capabilities to express the range of telemetry items needed to perform management or do not scale to large traffic volumes and rates. We present IntOpt, a scalable and expressive telemetry system designed for flexible VNF service chain network monitoring using active probing. IntOpt allows to specify monitoring requirements for individual service chain, which are mapped to telemetry item collection jobs that fetch the required telemetry items from P4 (programming protocol-independent packet processors) programmable dataplane elements. In our approach, the SDN controller creates the minimal number of monitoring flows to monitor the deployed service chains as per their telemetry demands in the network. We propose a simulated annealing based random greedy metaheuristic (SARG) to minimize the overhead due to active probing and collection of telemetry items. Using P4-FPGA, we benchmark the overhead for telemetry collection and compare our simulated annealing based approach with a naïve approach while optimally deploying telemetry collection probes. Our numerical evaluation shows that the proposed approach can reduce the monitoring overhead by 39% and the total delays by 57%. Such optimization may as well enable existing expressive monitoring frameworks to scale for larger real-time networks.

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.

Due to the tremendous increase in traffic demand, current mobile access and backhaul networks face a capacity problem. To increase the capacity, one can deploy many small cells, which may be dynamically powered on where traffic demand arises. As a consequence, the backhaul network for dense small cell deployments needs to cope with the massive increase in user demands but rolling out fiber to each small cell is economically not viable. Recently, mmWave based mobile backhaul networks have raised a lot of interest because of the large chunk of available spectrum in the 60 GHz, and 70/80 GHz band. However, due to the specific propagation characteristic of mmWave spectrum, such links may face frequent outage. In addition, a more flexible design of the backhaul network is desired in order to cope with the diversification of service requirements. In this paper, we propose a small cell backhaul network architecture which is based on the concept of Software Defined Networking. In order to cope with the dynamics of mmWave links, we propose that the SDN control plane calculates for each backhaul link a set of backup links. Using OpenFlow Fast Failover groups, a fast local repair of a mmWave backhaul link can be achieved leading to a resilient backhaul mesh architecture. An evaluation of our concept in a network emulator demonstrates the effectiveness of our approach. Particularly how it leads to lower packet loss and consequently higher throughput.

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.

poster Share on CloudMAC: torwards software defined WLANs Authors: Jonathan Vestin Karlstad University, Karlstad, Sweden Karlstad University, Karlstad, SwedenView Profile , Peter Dely Karlstad University, Karlstad, Sweden Karlstad University, Karlstad, SwedenView Profile , Andreas Kassler Karlstad University, Karlstad, Sweden Karlstad University, Karlstad, SwedenView Profile , Nico Bayer Telekom Innovation Laboratories, Berlin, Germany Telekom Innovation Laboratories, Berlin, GermanyView Profile , Hans Einsiedler Telekom Innovation Laboratories, Berlin, Germany Telekom Innovation Laboratories, Berlin, GermanyView Profile , Christoph Peylo Telekom Innovation Laboratories, Berlin, Germany Telekom Innovation Laboratories, Berlin, GermanyView Profile Authors Info & Claims Mobicom '12: Proceedings of the 18th annual international conference on Mobile computing and networkingAugust 2012Pages 393–396https://doi.org/10.1145/2348543.2348592Published:22 August 2012Publication History 9citation903DownloadsMetricsTotal Citations9Total Downloads903Last 12 Months4Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access