&lt;italic&gt;NFVactor&lt;/italic&gt;: A Resilient NFV System Using the Distributed Actor Model

Duan, Jingpu; Yi, Xiaodong; Zhao, Shixiong; Wu, Chuan; Cui, Heming; Le, Franck

doi:10.1109/jsac.2019.2894287

Cited by 12 publications

(6 citation statements)

References 30 publications

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“…This guarantees that data corruption cannot occur, regardless of the thread that actually carries out the operations. NFVActor [51] is a system for managing NFs that leverages the actor model, nevertheless the system has limited support for shared state between NF instances.…”

Section: Concurrencymentioning

confidence: 99%

FlexState: Flexible State Management of Network Functions

et al. 2021

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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.

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Section: Concurrencymentioning

confidence: 99%

FlexState: Flexible State Management of Network Functions

et al. 2021

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“…The actor model programming paradigm has been effectively used in a variety of distributed applications, ranging from small applications to big data processing [7,[36][37][38][39]. The ability of this model to scale resiliently and tolerate faults were among the key reasons for adopting it for building distributed systems.…”

Section: Related Workmentioning

confidence: 99%

A Robust Distributed Clustering of Large Data Sets on a Grid of Commodity Machines

Taamneh

Al-Hami

Bani-Salameh

et al. 2021

Data

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Distributed clustering algorithms have proven to be effective in dramatically reducing execution time. However, distributed environments are characterized by a high rate of failure. Nodes can easily become unreachable. Furthermore, it is not guaranteed that messages are delivered to their destination. As a result, fault tolerance mechanisms are of paramount importance to achieve resiliency and guarantee continuous progress. In this paper, a fault-tolerant distributed k-means algorithm is proposed on a grid of commodity machines. Machines in such an environment are connected in a peer-to-peer fashion and managed by a gossip protocol with the actor model used as the concurrency model. The fact that no synchronization is needed makes it a good fit for parallel processing. Using the passive replication technique for the leader node and the active replication technique for the workers, the system exhibited robustness against failures. The results showed that the distributed k-means algorithm with no fault-tolerant mechanisms achieved up to a 34% improvement over the Hadoop-based k-means algorithm, while the robust one achieved up to a 12% improvement. The experiments also showed that the overhead, using such techniques, was negligible. Moreover, the results indicated that losing up to 10% of the messages had no real impact on the overall performance.

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“…This guarantees that data corruption cannot occur, regardless of the thread which actually carries out the operations. NFVActor [25] is a system for managing NFs that leverages the actor model, nevertheless the system has limited support for shared state between NF instances.…”

Section: Concurrencymentioning

confidence: 99%

FlexState: Enabling Innovation in Network Function State Management

Pozza¹,

Rao²,

Lugones³

et al. 2020

Preprint

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Network function (NF) developers need to provide highly available solutions with diverse packet processing features at line rate. A significant challenge in developing such functions is to build flexible software that can be adapted to different operating environments, vendors, and operator use-cases. Today, refactoring NF software for specific scenarios can take months. Furthermore, network operators are increasingly adopting fast-paced development practices for continuous software delivery to gain market advantage, which imposes even shorter development cycles. A key aspect in NF design is state management, which can be optimized across deployments by carefully selecting the underlying data store. However, migrating to a data store that suits a different use-case is time consuming because it requires code refactoring while revisiting its application programming interfaces, APIs.In this paper we introduce FlexState, a state management system that decouples the NF packet processing logic from the data store that maintains its state. The objective is to reduce code refactoring significantly by incorporating an abstraction layer that exposes various data stores as configuration alternatives. Experiments show that FlexState achieves significant flexibility in optimizing the NF state management across several scenarios with negligible overhead.

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<italic>NFVactor</italic>: A Resilient NFV System Using the Distributed Actor Model

Cited by 12 publications

References 30 publications

FlexState: Flexible State Management of Network Functions

FlexState: Flexible State Management of Network Functions

A Robust Distributed Clustering of Large Data Sets on a Grid of Commodity Machines

FlexState: Enabling Innovation in Network Function State Management

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