Event-driven network programming

McClurg, Jedidiah; Hojjat, Hossein; Foster, Nate; Černý, Pavol

doi:10.1145/2980983.2908097

Cited by 18 publications

(13 citation statements)

References 32 publications

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“…Network operators should be able to specify traffic transformations at a high level and have a runtime distribute the operations over network elements, which may range from network switches to software virtual machines to servers with hardware accelerators for specific operations. Researchers have recently developed high-level languages for specifying transformations of packets based on header fields and their locations [1,11,12], including recent work on stateful operations [3,22]. Some recent work also shows how to synthesize a distributed configuration of network devices (e.g., OpenFlow or P4 switches) to realize these policies while considering network-wide optimization goals [3,27].…”

Section: Specify Sophisticated Network Policiesmentioning

confidence: 99%

Why (and How) Networks Should Run Themselves

Feamster

Rexford

2018

Proceedings of the Applied Networking Research Workshop

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The proliferation of networked devices, systems, and applications that we depend on every day makes managing networks more important than ever. The increasing security, availability, and performance demands of these applications suggest that these increasingly difficult network management problems be solved in real time, across a complex web of interacting protocols and systems. Alas, just as the importance of network management has increased, the network has grown so complex that it is seemingly unmanageable. In this new era, network management requires a fundamentally new approach. Instead of optimizations based on closed-form analysis of individual protocols, network operators need datadriven, machine-learning-based models of end-to-end and application performance based on high-level policy goals and a holistic view of the underlying components. Instead of anomaly detection algorithms that operate on offline analysis of network traces, operators need classification and detection algorithms that can make real-time, closed-loop decisions. Networks should learn to drive themselves. This paper explores this concept, discussing how we might attain this ambitious goal by more closely coupling measurement with real-time control and by relying on learning for inference and prediction about a networked application or system, as opposed to closed-form analysis of individual protocols.

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Section: Specify Sophisticated Network Policiesmentioning

confidence: 99%

Why (and How) Networks Should Run Themselves

Feamster

Rexford

2018

Proceedings of the Applied Networking Research Workshop

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“…Network update schemes also depend on the application, e.g., traffic engineering applications can come with very different requirements than load-balancing [171]. Especially the development of more advanced and complex applications (e.g., [172], [173], [85, §3]) on top of SDN networks may create the need to support new consistency properties, and to potentially preserve these new properties during network updates. This is particularly true for stateful applications, whose state is built or modified by multiple flows.…”

Section: New Update Problems Raised By Stateful Applicationsmentioning

confidence: 99%

Survey of Consistent Software-Defined Network Updates

Foerster

Schmid

Vissicchio

2019

IEEE Commun. Surv. Tutorials

113

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Computer networks have become a critical infrastructure. In fact, networks should not only meet strict requirements in terms of correctness, availability, and performance, but they should also be very flexible and support fast updates, e.g., due to policy changes, increasing traffic, or failures. This paper presents a structured survey of mechanism and protocols to update computer networks in a fast and consistent manner. In particular, we identify and discuss the different desirable consistency properties that should be provided throughout a network update, the algorithmic techniques which are needed to meet these consistency properties, and the implications on the speed and costs at which updates can be performed. We also explain the relationship between consistent network update problems and classic algorithmic optimization ones. While our survey is mainly motivated by the advent of Software-Defined Networks (SDNs) and their primary need for correct and efficient update techniques, the fundamental underlying problems are not new, and we provide a historical perspective of the subject as well.

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“…Following the increasing need for highly dynamic network services and policies, the introduction of programmable data planes enables traffic processing policies to be offloaded directly into the switches. New frameworks to embed user-defined network policies to the stateful switches have been proposed [10], [11]. In this paper, we consider SNAP [10] as a reference framework, even if our proposed approach is general and relevant to any programming abstractions for stateful data planes.…”

Section: State Replication In Stateful Sdnmentioning

confidence: 99%

Optimal State Replication in Stateful Data Planes

Muqaddas

Sviridov

Giaccone

et al. 2020

IEEE J. Select. Areas Commun.

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In SDN stateful data planes, switches can execute algorithms to process traffic based on local states.This approach permits to offload decisions from the controller to the switches, thus reducing the latency when reacting to network events. We consider distributed network applications that process traffic at each switch based on local replicas of network-wide states. Replicating a state across multiple switches poses many challenges, because the number of state replicas and their placement affects both the data traffic distribution and the amount of synchronization traffic among the replicas.In this paper, we formulate the optimal placement problem for replicated states, taking into account the data traffic routing, to ensure that traffic flows are properly managed by network applications, and the synchronization traffic between replicas, to ensure state coherence. Due to the high complexity required to find the optimal solution, we also propose an approximated algorithm to scale to large network instances. We numerically show that this algorithm, despite its simplicity, well approximates the optimal solution. We also show the beneficial effects of state replication with respect to the singlereplica scenario, so far considered in the literature. Finally, we provide an asymptotic analysis to find the optimal number of replicas.

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Event-driven network programming

Cited by 18 publications

References 32 publications

Why (and How) Networks Should Run Themselves

Why (and How) Networks Should Run Themselves

Survey of Consistent Software-Defined Network Updates

Optimal State Replication in Stateful Data Planes

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