Network monitoring is of paramount importance for effective network management: it allows to constantly observe a network's behavior to ensure it is working as intended, and can trigger both automated and manual remediation procedures in case of failures and anomalies. Software-Defined Networking (SDN) decouples the control plane of network infrastructure from its data plane to perform centralized control on the multiple switches in a network. In this context, the responsibility of switches is only to forward packets according to the instructions provided by a controller. The lack of programmability in the data plane of SDNs prompted the advent of data-plane programmable switches, which allow developers to customize the data-plane pipeline (e.g. match-action tables) by using a domain specific language named P4, and implement novel programs and protocols operating at wire speed directly in the switches. This unlocks the possibility to offload some monitoring tasks to the programmable data plane, and to perform fine-grained monitoring at very high packet processing speeds. Given the central importance of this topic, the principal goal of this thesis is to enable a wide range of monitoring tasks in data-plane programmable switches, with a focus on the ones equipped with programmable Application-Specific Integrated Circuits (ASICs). To achieve this goal, this thesis makes three main contributions: (i.) We enhance P4-supported data plane programmability for network monitoring; (ii.) We design and develop several network monitoring tasks in programmable data planes; (iii.) We combine multiple tasks in a single commodity switch to collect various metrics for different monitoring purposes. Our evaluations show that our solutions can be exploited by network administrators, operators and security engineers to better track and understand the current network status, and thus prevent infrastructure and service failures.
Ding, D., Savi, M., Pederzolli, F., Siracusa, D. (2022). Design and Development of Network Monitoring Strategies in P4-enabled Programmable Switches. In Proceedings of the IEEE/IFIP Network Operations and Management Symposium 2022. Network and Service Management in the Era of Cloudification, Softwarization and Artificial Intelligence (pp.1-6). IEEE [10.1109/NOMS54207.2022.9789848].
Design and Development of Network Monitoring Strategies in P4-enabled Programmable Switches
Savi, M;
2022
Abstract
Network monitoring is of paramount importance for effective network management: it allows to constantly observe a network's behavior to ensure it is working as intended, and can trigger both automated and manual remediation procedures in case of failures and anomalies. Software-Defined Networking (SDN) decouples the control plane of network infrastructure from its data plane to perform centralized control on the multiple switches in a network. In this context, the responsibility of switches is only to forward packets according to the instructions provided by a controller. The lack of programmability in the data plane of SDNs prompted the advent of data-plane programmable switches, which allow developers to customize the data-plane pipeline (e.g. match-action tables) by using a domain specific language named P4, and implement novel programs and protocols operating at wire speed directly in the switches. This unlocks the possibility to offload some monitoring tasks to the programmable data plane, and to perform fine-grained monitoring at very high packet processing speeds. Given the central importance of this topic, the principal goal of this thesis is to enable a wide range of monitoring tasks in data-plane programmable switches, with a focus on the ones equipped with programmable Application-Specific Integrated Circuits (ASICs). To achieve this goal, this thesis makes three main contributions: (i.) We enhance P4-supported data plane programmability for network monitoring; (ii.) We design and develop several network monitoring tasks in programmable data planes; (iii.) We combine multiple tasks in a single commodity switch to collect various metrics for different monitoring purposes. Our evaluations show that our solutions can be exploited by network administrators, operators and security engineers to better track and understand the current network status, and thus prevent infrastructure and service failures.File | Dimensione | Formato | |
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