Virtualizing Switch Control Plane Engine via Scheduler
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Solution Overview
Problem
Existing switch fabrics do not effectively virtualize control plane engines, limiting the distribution of services within separate data and control planes, as they typically do not instantiate control plane services as virtual machines.
Innovation Solution
A scheduler in the control device of a switch fabric system designates control plane entities as virtual machines based on state information and attribute values, sending signals to compute devices for instantiation, allowing for affinity and anti-affinity attribute-based placement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If control plane services are implemented at different physical devices, then service distribution is limited within physical devices, but if virtualization is applied only within the data plane, then control plane services cannot be distributed flexibly across compute devices
Solution Approach 1:
The control plane engine is segmented into multiple control plane entities that can be independently instantiated as virtual machines on different compute devices. This segmentation enables flexible distribution of control plane services across the network fabric while maintaining manageable individual components.
Solution Approach 2:
The patent introduces virtualization as a new dimension for control plane service distribution. By instantiating control plane entities as virtual machines on compute devices rather than being confined to physical control plane devices, the system gains an additional dimension of flexibility in service placement and management.
2Productivity
If control plane entities are instantiated as virtual machines on compute devices, then service distribution is improved, but then scheduler complexity for managing virtual machine placement increases
Solution Approach 1:
The scheduler is pre-configured with affinity and anti-affinity attributes for different control plane entities. These attributes are established beforehand to guide virtual machine placement decisions, allowing the scheduler to make efficient placement decisions without complex real-time calculations.
Solution Approach 2:
The system implements feedback mechanisms where the scheduler monitors the state of control plane entities and adjusts virtual machine placement accordingly. This feedback loop enables dynamic optimization of service distribution while maintaining manageable scheduler complexity through iterative adjustments rather than complex upfront planning.
Data Source
AI summary
In some embodiments, an apparatus includes a scheduler disposed at a control device of a switch fabric system. The scheduler is configured to receive a control plane request associated with the switch fabric system having a data plane and a control plane separate from the data plane. The scheduler is configured to designate a control plane entity based on the control plane request and state information of each control plane entity from a set of control plane entities associated with the control plane and instantiated as a virtual machine. The scheduler is configured to send a signal to a compute device of the switch fabric system in response to the control plane request such that the control plane entity is instantiated as a virtual machine at the compute device.