Software Defined Networking envisions smart centralized controllers governing the forwarding behavior of dumb low-cost switches. But are "dumb" switches an actual strategic choice, or (at least to some extent) are they a consequence of the lack of viable alternatives to OpenFlow as programmatic data plane forwarding interface? Indeed, some level of (programmable) control logic in the switches might be beneficial to offload logically centralized controllers (de facto complex distributed systems) from decisions just based on local states (versus network-wide knowledge), which could be handled at wire speed inside the device itself. Also, it would reduce the amount of flow processing tasks currently delegated to specialized middleboxes. The underlying challenge is: can we devise a stateful data plane programming abstraction (versus the stateless OpenFlow match/action table) which still entails high performance and remains consistent with the vendors' preference for closed platforms? We posit that a promising answer revolves around the usage of extended finite state machines, as an extension (super-set) of the OpenFlow match/action abstraction. We concretely turn our proposed abstraction into an actual table-based API, and, perhaps surprisingly, we show how it can be supported by (mostly) reusing core primitives already implemented in OpenFlow devices.

OpenState: programming platform-independent stateful openflow applications inside the switch

CAPONE, ANTONIO;CASCONE, CARMELO
2014-01-01

Abstract

Software Defined Networking envisions smart centralized controllers governing the forwarding behavior of dumb low-cost switches. But are "dumb" switches an actual strategic choice, or (at least to some extent) are they a consequence of the lack of viable alternatives to OpenFlow as programmatic data plane forwarding interface? Indeed, some level of (programmable) control logic in the switches might be beneficial to offload logically centralized controllers (de facto complex distributed systems) from decisions just based on local states (versus network-wide knowledge), which could be handled at wire speed inside the device itself. Also, it would reduce the amount of flow processing tasks currently delegated to specialized middleboxes. The underlying challenge is: can we devise a stateful data plane programming abstraction (versus the stateless OpenFlow match/action table) which still entails high performance and remains consistent with the vendors' preference for closed platforms? We posit that a promising answer revolves around the usage of extended finite state machines, as an extension (super-set) of the OpenFlow match/action abstraction. We concretely turn our proposed abstraction into an actual table-based API, and, perhaps surprisingly, we show how it can be supported by (mostly) reusing core primitives already implemented in OpenFlow devices.
2014
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/846131
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