FlexState: Flexible State Management of Network Functions

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Pozza , M , Rao , A , Lugones , D F & Tarkoma , S 2021 , ' FlexState: Flexible State Management of Network Functions ' , IEEE Access , vol. 9 , pp. 46837 - 46850 . https://doi.org/10.1109/ACCESS.2021.3061814

Title: FlexState: Flexible State Management of Network Functions
Author: Pozza, Matteo; Rao, Ashwin; Lugones, Diego. F.; Tarkoma, Sasu
Other contributor: University of Helsinki, Department of Computer Science
University of Helsinki, Department of Computer Science
University of Helsinki, Department of Computer Science


Date: 2021-03
Language: eng
Number of pages: 14
Belongs to series: IEEE Access
ISSN: 2169-3536
DOI: https://doi.org/10.1109/ACCESS.2021.3061814
URI: http://hdl.handle.net/10138/329092
Abstract: Network function (NF) developers have traditionally prioritized performance when creating new packet processing capabilities. This was usually driven by a market demand for highly available solutions with differentiating features running at line rate, even at the expense of flexibility and tightly-coupled monolithic designs. Today, however, the market advantage is achieved by providing more features in shorter development cycles and quickly deploying them in different operating environments. In fact, network operators are increasingly adopting continuous software delivery practices as well as new architectural styles (e.g., microservices) to decouple functionality and accelerate development. A key challenge in revisiting NF design is state management, which is usually highly optimized for a deployment by carefully selecting the underlying data store. Therefore, migrating to a data store that suits a different use case is time-consuming as it requires code refactoring and adaptation to new application programming interfaces, APIs. As a result, refactoring NF software for different environments can take up to months, reducing the pace at which new features and upgrades can be deployed in production networks. In this paper, we demonstrate experimentally that it is feasible to introduce an abstraction layer to decouple NF state management from the data store adopted while still approaching line-rate performance. We present FlexState, a state management system that exposes data store functionality as configuration options, which reduces code refactoring efforts. Experiments show that FlexState achieves significant flexibility in optimizing the state management, and accelerates deployment on new scenarios while preserving performance and scalability.
Subject: 113 Computer and information sciences
Noise measurement
Scalability
Production
Reliability engineering
Distributed databases
Optimization
Middleware
Data storage systems
middleboxes
network functions
network functions virtualization
NFV
parallel processing
state management
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