The wide area network (WAN) primarily manages remote and long-haul interconnectivity between network sites, such as headquarters and branches, branch to branch, and data center to data center scenarios. Currently, the WAN mainly passively carries various service traffic. A traditional WAN was typically rigid and managed from the perspective of network nodes instead of applications. Lacking scalability and visibility into applications, a traditional WAN backbone network could hardly adapt to accelerated application deployments and increasingly complex workloads driven by new technologies such as cloud computing and mobile Internet. Traditional distributed networks focus more on the performance and operations of individual network nodes, lacking a global perspective on traffic scheduling and optimization based on deep insights into services.
The H3C Application-Driven Wide Area Network (AD-WAN) solution uses a standard SDN architecture that is unified, tiered, open, and intelligent. It integrates intelligent analysis module, intelligent control module, and intelligent management module to provide unified network management, control, and analytics and end-to-end service orchestration across the campus, data center, and WAN domains. The solution also provides a unified portal for administrators to provision, assure, operate, and manage the network from a single pane of management. The solution can take real-time snapshots of the network, build offline models, and do AI-assisted big data analytics to provide actionable insights, intelligent simulation, and intelligent troubleshooting. With the support for SRv6, the solution facilitates one-hop migration to cloud and network programming capabilities essential for the cloud service era. The AD-WAN backbone solution helps enterprises build modern, intelligent WAN backbone networks to drive their digital transformation.
The solution is underpinned by Unified Platform, H3C’s digital network engine. Unified Platform uses a containerized architecture to provide software as services across the campus, data center, and WAN domains. In the northbound direction, the platform provides standard RESTful APIs for flexible integration with the operations support systems (OSSs) and business support systems (BSSs) for accelerated business innovations. In the southbound direction, the platform supports a variety of protocols and techniques to communicate with the infrastructure layer for network management, control, telemetry data collection, and analytics. The supported southbound protocols and techniques include SNMP, NETCONF, BGP link-state (BGP-LS), BGP Segment Routing over IPv6 (SRv6) Policy, and Path Computation Element Communication Protocol (PCEP).
Management module—The solution provides automated end-to-end service orchestration of VPN, QoS, and SR tunneling, in addition to traditional management capabilities such as management of versioning, configuration, alarms, performance, and topology.
Control module—The solution provides WAN optimization capabilities. With a holistic view of the network, administrators can configure and deploy policies to select and optimize paths for applications based on metrics such as bandwidth, latency, jitter, packet loss ratio, time range, link affinity, link preference, and excluded links. The solution supports granular application traffic classification and automated traffic engineering. With the solution, you can classify application traffic based on the IP five-tuple, DSCP, and VPN for native IP public services and VPN services. The controller can then dynamically steer the application streams to SR tunnels to provide assured services to prioritized applications and maximize bandwidth use efficiency. The solution constantly monitors the network for changes. The network devices can do failover in milliseconds and optimize traffic paths in seconds to provide assured reliable network services.
Analysis module—The solution supports multiple model-driven telemetry techniques for quick state change detection and maintenance in seconds. The collected telemetry data is visualized to present critical metrics for maintenance and provide actionable insights. The analytics platform uses AI technologies such as machine learning and deep learning to assist in network operations and maintenance. It analyzes and correlates massive data collected from the entire network about network devices, traffic, quality, correlated events, and alarms to proactively identify and predict network and application issues. The solution also provides automated troubleshooting to help customers quickly remove network and application issues before or after they occur. All these capabilities help improve efficiency and decrease operations and maintenance costs.
The following contents are complex, and it is recommended to browse on PC.
Enter c.h3c.com.cn on the PC browser and operate according to the page to synchronize to the PC and continue browsing.
Continue by mobile