System Level Functions Managed Through Control Plane – Is This Acceptable?
The rise of software defined networking introduces new ways to control and operate networks. Software programs can now personalize the behavior of the network by reprograming the switching fabrics with specific rules they would like to use. As a result from a silicon perspective, the biggest change in network operation then is the emergence of large volumes of control plane rule changes that have the effect of appearing “random” compared to the predictable flows traditionally controlled by the network. These changes are random because computer programs initiate them, not the network itself and so they are unpredictable in their timing or requirements.
Traditional fabrics have been built using structures optimized for match and forward tasks, and using deep packet inspection and packet classification techniques to learn about where the packets need to be forwarded in the network. These arrays are long in order to achieve line rate for multiple channels. To maximize performance, these arrays require packets to be inserted in the front of the pipeline, with classified packets coming out the end of the pipeline. Over time these traditional architectures have evolved such that specific and often specialized compute and state management is employed.
Introducing the random changes via SDN means the rules changes must occur during a pipeline stage, and as their volumes grow, in turn causes traditional architectures to operate far less efficiently. Eventually both reliability and scalability are compromised. What is emerging is an opportunity for network fabric developers to now leverage embed and general purpose microprocessor architectures as fabrics. These architectures are more optimized for random processing and in general will become adequately efficient as SDN grows. When coupled with companion chip sets that provide traditional IP packet processing tasks, such as TCP offload, these architectures become more efficient traditional network fabrics.
One of the design challenges when using embed or general purpose microprocessors is the continued need to employ data and control planes. SoCs that utilize these technologies and corresponding interconnects to connect multiple cores, have been heavily optimized for data plane operations. However, in networking, control plane is equally important.
SSM is the industry’s first merchant silicon optimized for control plane management using a SoC development methodology.
SSM compliments SoC data plane architectures while filling the void for control plane state management. SSM utilizes a software based policy driven state management approach, which enables SoCs to sufficiently mimic full control and data plane networking. The introduction then of SSM into a SoC enables full utilization of SoC methodologies for network fabric development.
By utilizing software policies that describe the nature of the SDN network personalization required, SSM can orchestrate the operation of the relevant subsystems on the SoC to create the behavior desired. If these subsystems are implemented using deeply embedded processing or re-programmable logic, specific actions that enforce SDN requests can be accommodated in real time while SSM manages the global state operations. As a result, predictability is restored to the network operations.
The SoC based fabric also becomes extremely flexible to adapt to increasingly diverse random requests. Thus, adaptive fabric operation is achievable by using the SSM subsystem to collect data about how the SoC is utilized. A second core processor can then use this data to monitor fabric use and determine optimal behavior patterns. This processor than chooses the SSM policies that reflect the optimizations. A library of SSM policies maintained in memory acts as real time middleware options that enable the fabric to constantly recalibrate and maintain optimal behavior.
The introduction of SDN causes traditional network fabric architectures to loose predictability and efficiency. Embedded and general purpose processors are more optimized for the random actions caused by SDN but lack specific network tasks and do not conventionally support robust control plane operations. SSM provides a complimentary control plane architecture which offers predictability and efficiency adequate for adopting SoC methodology for network fabrics. Additionally, SSM ushers in an adaptive behavior characteristic that enables SoC based fabrics to maintain optimal efficiency as the diversity of SDN random requests grows over time.