Automatic data aggregation for recursively modeled NFV services

Summary Network function virtualization (NFV) allows to model network services as graphs interconnecting virtual network functions (VNFs), which may include nested VNFs, modeled as subgraphs of VNFs or end points. To query the performance data of network services modeled as and high‐level graphs is...

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Veröffentlicht in:International journal of network management Jg. 28; H. 2
Hauptverfasser: Cai, Xuejun, John, Wolfgang, Meirosu, Catalin
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Chichester Wiley Subscription Services, Inc 01.03.2018
Schlagworte:
Agglomeration
Business metrics
Concurrency
Data management
Decomposition
Elasticity
Graphs
Infrastructure
Level (quantity)
Logic programming
Performance evaluation
Performance measurement
Programming languages
Queries
Query languages
ISSN:1055-7148, 1099-1190
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Zusammenfassung:Summary Network function virtualization (NFV) allows to model network services as graphs interconnecting virtual network functions (VNFs), which may include nested VNFs, modeled as subgraphs of VNFs or end points. To query the performance data of network services modeled as and high‐level graphs is challenging because of the recursivity of the NFV architecture and the elasticity and dynamicity provided by the NFV infrastructure. We propose to use Datalog, a declarative logic programming language, to build a framework that supports efficient data aggregation for performance metrics of recursively modeled network services. We present our recursive query language for automatic and flexible decomposition and aggregation of NFV performance metrics and describe example use cases for both compute and network metrics. We also describe the design and implementation of a proof‐of‐concept query engine using the language. Our performance evaluation shows that the total query latency is dominated by retrieval times of performance metrics from infrastructure databases, and the time for execution and automatic decomposition of high‐level queries by the query engine itself increases linearly with the size of the service graph up to 1000 nodes. Hence, our evaluations show that the query engine scales well, bounded mainly by the limited execution capabilities of our test environment. Furthermore, it can handle multiple concurrent queries up to the concurrency limits of the backend database in use. The proposed query language and engine are thus effective in recursively retrieving performance metrics of NFV environments supporting large‐scale service graphs and large numbers of query requests. In this paper, we propose to use Datalog, a declarative logic programming language, to build a framework which supports efficient data aggregation for performance metrics of recursively modeled network services. We also describe the design and implementation of a proof‐of‐concept query engine utilizing the language. The experimental evaluation shows that the proposed query language and engine are practicable and effective in recursively retrieving performance metrics of NFV environments supporting large‐scale service graphs and large numbers of query requests.
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ISSN:1055-7148
1099-1190
DOI:10.1002/nem.2009