Optimizing Distributed Network Monitoring for NFV Service Chains

Hohemberger, Rumenigue; Lorenzon, Arthur F.; Rossi, Fábio Diniz; Luizelli, Marcelo Caggiani

doi:10.1109/lcomm.2019.2922184

Cited by 11 publications

(2 citation statements)

References 9 publications

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“…Furthermore, the described model is assessed considering a real-world use case scenario, and the overall output of the experiments is satisfactory. Furthermore, an interesting related contribution is reported by Hohemberger et al [52], which defines the concept of coordinated network monitoring as an essential functional approach for the optimisation of network monitoring in virtualised environments.…”

Section: Network Monitoringmentioning

confidence: 99%

Real-Time Monitoring and Management of Hardware and Software Resources in Heterogeneous Computer Networks through an Integrated System Architecture

Aldea,

Bocu,

Solca

2023

Symmetry

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The theoretical and practical progress that has occurred in the field of computer networks during the past fifteen years has enhanced the economical efficiency and social relevance of related real-world use cases. Nevertheless, this ubiquitous usage has also introduced numerous security risks. Therefore, monitoring hardware and software resources represents one of the main instruments used in order to prevent potential attacks and to ensure the security and reliability of a network. Various solutions have been reported in the related scientific literature. In essence, most of the existing approaches are not suitable to implement a real-time hardware monitoring and management solution, particularly in heterogeneous networks. Therefore, the main contribution of this paper is represented by an architectural and implementational model, which is effective in order to build an interconnected system that can help system and network administrators to secure a network. This requirement is met by considering symmetrical design and implementation features related to various operating systems. Thus, the existing symmetrical relationships among identified parameters allow for the data to be wrapped into the same custom network packages, which are transported over the communication medium or are stored using the same data structures or tables. The system has been thoroughly assessed considering several real-world use case scenarios, and the results demonstrate that the proposed model can be applied to software-defined networks, which can be protected by relevant intrusion detection systems (IDS).

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Section: Network Monitoringmentioning

confidence: 99%

Real-Time Monitoring and Management of Hardware and Software Resources in Heterogeneous Computer Networks through an Integrated System Architecture

Aldea,

Bocu,

Solca

2023

Symmetry

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“…In [21], the authors propose a probabilistic INT mechanism to bound the amount of information added to each packet to limit overhead. In [22], the authors study the optimization problem for distributed virtual network monitoring which determines the optimal placement of monitoring nodes and the coordinated forwarding of network monitoring traffic. In [23], the authors present IntOpt, a telemetry system that maps SFC monitoring jobs into a minimum number of monitoring flows for multiple VNF SFC monitoring.…”

Section: Related Workmentioning

confidence: 99%

A Learning-Based Service Function Chain Early Fault Diagnosis Mechanism Based on In-Band Network Telemetry

FU¹,

LIU

et al. 2022

IEICE Trans. Inf. & Syst.

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Network virtualization has become a promising paradigm for supporting diverse vertical services in Software Defined Networks (SDNs). Each vertical service is carried by a virtual network (VN), which normally has a chaining structure. In this way, a Service Function Chain (SFC) is composed by an ordered set of virtual network functions (VNFs) to provide tailored network services. Such new programmable flexibilities for future networks also bring new network management challenges: how to collect and analyze network measurement data, and further predict and diagnose the performance of SFCs? This is a fundamental problem for the management of SFCs, because the VNFs could be migrated in case of SFC performance degradation to avoid Service Level Agreement (SLA) violation. Despite the importance of the problem, SFC performance analysis has not attracted much research attention in the literature. In this current paper, enabled by a novel detailed network debugging technology, In-band Network Telemetry (INT), we propose a learning based framework for early SFC fault prediction and diagnosis. Based on the SFC traffic flow measurement data provided by INT, the framework firstly extracts SFC performance features. Then, Long Short-Term Memory (LSTM) networks are utilized to predict the upcoming values for these features in the next time slot. Finally, Support Vector Machine (SVM) is utilized as network fault classifier to predict possible SFC faults. We also discuss the practical utilization relevance of the proposed framework, and conduct a set of network emulations to validate the performance of the proposed framework.

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