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Control plane in dynamic software networks

Abstract : During the last years, network infrastructure has moved from dedicated-hardware solutions implementing fixed functions to more flexible software based ones. On one hand, SDN (Software Defined Network) can flexibly control forwarding operations, while on the other, NFV (Network Function Virtualization) creates elastic functions that can scale with the user demands. So far, these solutions have been used to simplify network management and operations, but they let envision a network that can automatically react to network events. In this thesis, we explore to what extent these new software networks can be used to react and adapt finely to the network dynamics.Our first contribution focuses on service chaining: the ability to steer flows through a set of waypoints hosting functions before they reach their destinations. We show that a distributed control plane that relies on existing routing protocols and is constituted by autonomous nodes can dynamically steer traffic through chains of services. Our solution finely adapts its decision to the network traffic and automatically balances the induced load on the functions present in the network. Moreover, our proposal, contrary to existing solutions, can be incrementally deployed in today's network.In our second contribution, we compare two types of chaining decisions: a centralized one with an end-to-end view of the chain and a distributed approach that solely routes flow from a function to another. We show that the two decisions are close in realistic topologies. Thus, hop-by-hop chaining could be used without affecting chaining performance. Finally, we explore how software networks can react to network dynamics in datacenters. So far, load balancers use static policies to spread incoming traffic on servers, which leads to imbalance and overprovisioning. We propose to close the loop and dynamically adapt the policy to the server load variation. Our MPC (Model Predictive Control) approach proved to be efficient to reduce load imbalance at a slow pace, thus improving the number of requests a cluster can process.
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Submitted on : Sunday, January 2, 2022 - 1:35:05 AM
Last modification on : Thursday, January 6, 2022 - 6:10:14 PM
Long-term archiving on: : Sunday, April 3, 2022 - 7:38:30 PM


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  • HAL Id : tel-03506284, version 1



Adrien Wion. Control plane in dynamic software networks. Networking and Internet Architecture [cs.NI]. Institut Polytechnique de Paris, 2021. English. ⟨NNT : 2021IPPAT007⟩. ⟨tel-03506284⟩



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