Due to a ransomware attack, the wiki was reverted to a July 2022 version. . We apologize for the lack of a more recent valid backup.
Our goal is to implement ONOS-TAM features, which are enable to analyze and monitor all types of traffic related to ONOS, such as control message traffic and management traffic, as well as data traffic between hosts within ONOS domain. At the end, our proposed ONOS-TAM features will provide deep operational visibility of ONOS in real-time.
Team
| Name | Organization | |
|---|---|---|
| Taesang Choi | ETRI, South Korea | choits@etri.re.kr |
| Chunglae Cho | ETRI, South Korea | clcho@etri.re.kr |
| Sangsik Yoon | ETRI, South Korea | ssyoon90@etri.re.kr |
Quick Links
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Introduction
Network traffic monitoring is a very fundamental function that can be used to operate and manage network stablely and efficiently. Many network management systems(i.e., Traffic Engineering, Network Planning, Billing, Performance Manager, QoS Provisioning, Fault Manager etc.) may need more accurate and real-time network monitoring information. In order to provide effective and deep network monitoing features on ONOS, we will focus on flow monitoring service with an efficient sampling mechanism and selective DPI(Deep Packet Inspection) service in ONOS. We will develop two separate phases in our ONOS-TAM subproject.
- Development Phase 1 : Adaptive(Effective) Flow Sampling Service
- Development Phase 2 : Open Selective-DPI Service
Development Phase 1 : Adaptive(Effective) Flow Sampling Service (~Aug. 31)
- Current Problem Statement
Current FlowRule service collects all flow information from all devices at every time interval(default 10 seconds). Current FlowRule service collects all flow information from all devices at every time interval(default 10 seconds). This mechanism may cause performance degradation issue at each collection time in a large-scale real carrier network due to the number of switches and its associated flows (for example; WAN: ~500 Routers, ~10K ports, ~1-10M flows per port). To overcome performance problem in a simple way, we can maintain collection time interval value with a large number. It then generates another critical issue: lack of accuracy. - First of all , we will develop an effective flow monitoring scheme called, Adaptive(Effective) Flow Sampling Service that can minimize collection computing overhead and provide more accurate flow statistics
- AFS Service Architecture and Development Modules
Development Pahse 2 : Open Selective-DPI Service (~Oct.31)
- Current Problem Statement
Current ONOS flow can be classified and selected by lower-level FlowSelection criteria based on FlowRule entry (eg., ports, ether_type, vlan_id, 5-tuple, etc.). There is no application classification service for ONOS data plane user-data. - We will develop a Selective DPI service that can filter data plane user-data traffic redirected by the controller and classify them with application level granularity by using a open source DPI s/w.
Application of Open S-DPI can be application traffic analysis, service chaining classification, etc. We will take phased approach from a simple application to complex ones.
- Open Selective-DPI Service Architecture and Development Modules
ONON-TAM Development Testbed Environment in ETRI SDN Research Lab (South Korea)
- ONOS Cardinal 1.2.0 Release is installed at Ubuntu 14.04.2
- 6 OVS 1.4.6 version switches and several Openstack hosts
- ETRI ONOS-TAM Testbed Topology GUI
