Virtualized Cable Data Plane Scaling With SR-IOV Isolation
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Solution Overview
Problem
Virtualization of cable data plane applications in CATV systems is challenging due to real-time constraints and the difficulty in dynamically scaling line cards to meet network demands, particularly in distributed CMTS architectures.
Innovation Solution
Implementing vCore instances on COTS servers using container orchestration systems, with automated lifecycle management and resource allocation to ensure timely data delivery and scalability, utilizing SR-IOV for dedicated network bandwidth and isolating CPU cores from the operating system to maintain real-time performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If virtualization of cable data plane applications is implemented, then resource utilization and scalability are improved, but real-time performance and data delivery timeliness deteriorate
Solution Approach 1:
The system segments virtualized applications into isolated container environments (vCores) with dedicated resource allocations. Each container is granted exclusive access to specific CPU cores, memory, and network resources through hypervisor-enforced partitions, ensuring that virtualization does not compromise real-time performance while maintaining scalability across multiple containers.
Solution Approach 2:
The patent implements local quality by providing differentiated resource guarantees to different containers based on their specific real-time requirements. Critical data plane functions receive dedicated CPU cores and guaranteed network bandwidth through SR-IOV, while less time-sensitive functions can share resources, optimizing both real-time performance and overall resource utilization.
2Stability of the object's composition
If manual scaling of line cards is used, then system stability is maintained, but operational flexibility and response time to demand changes deteriorate
Solution Approach 1:
The system implements self-service through automated orchestration that monitors network demand and dynamically provisions or deprovisions container instances based on actual traffic conditions. The orchestration system automatically allocates computational resources, manages container lifecycles, and scales capacity without manual intervention, maintaining system stability through controlled automation while providing operational flexibility.
Solution Approach 2:
The patent incorporates feedback mechanisms where the orchestration system continuously monitors network traffic patterns, container performance metrics, and resource utilization. Based on this feedback, the system automatically adjusts container scaling decisions, resource allocations, and load distribution to maintain stability while adapting to changing operational demands in real-time.
3Use of energy by moving object
If shared network resources are used in virtualized environments, then resource efficiency is improved, but network performance and data delivery timeliness worsen
Solution Approach 1:
The patent merges multiple virtual network interfaces into a single physical network card using SR-IOV (Single Root I/O Virtualization) technology. This allows multiple virtual functions to share a single physical NIC while maintaining isolated, guaranteed bandwidth allocations for each container, achieving both resource efficiency through consolidation and timely data delivery through dedicated resource partitions.
Solution Approach 2:
The system performs preliminary action by pre-allocating dedicated network bandwidth and buffer resources to containers before data plane traffic arrives. Resource reservations and quality of service (QoS) policies are configured in advance to guarantee minimum performance levels, ensuring that shared network resources do not compromise data delivery timeliness when traffic spikes occur.
Data Source
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AI summary
Systems and methods to support flexible scaling and dynamic resource allocation for virtualized cable data plane applications. The system includes a head end operating together with a node to provide data to customer devices. A container operating on at least one server included in the head end includes a data plane application that provides packets of data for transmission to the node. The data plane application is instantiated with at least one of a virtual networking function and a computing resource function.