A framework for SDN integrated management based on a CIM model and a vertical management plane

Estrada-Solano, Felipe; Ordóñez, Armando; Granville, Lisandro Zambenedetti; Rendón, Óscar Mauricio Caicedo

doi:10.1016/j.comcom.2016.08.006

Cited by 17 publications

(13 citation statements)

References 9 publications

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“…We use the CIM and the OWL to carry out SIM (see Figure 1 ). We adopted CIM [ 29 ] because it provides high expressiveness for modeling, for management purposes, information systems, applications, and networks [ 30 ]. We used OWL [ 31 ] because it enables reasoning in the model and the sharing of knowledge among software agents [ 32 ].…”

Section: Sim-knowmentioning

confidence: 99%

A Semantic and Knowledge-Based Approach for Handover Management

Vivas

Rendón

Nieves

2021

Sensors

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Handover Management (HM) is pivotal for providing service continuity, enormous reliability and extreme-low latency, and meeting sky-high data rates, in wireless communications. Current HM approaches based on a single criterion may lead to unnecessary and frequent handovers due to a partial network view that is constrained to information about link quality. In turn, HM approaches based on multicriteria may present a failure of handovers and wrong network selection, decreasing the throughput and increasing the packet loss in the network. This paper proposes SIM-Know, an approach for improving HM. SIM-Know improves HM by including a Semantic Information Model (SIM) that enables context-aware and multicriteria handover decisions. SIM-Know also introduces a SIM-based distributed Knowledge Base Profile (KBP) that provides local and global intelligence to make contextual and proactive handover decisions. We evaluated SIM-Know in an emulated wireless network. When the end-user device moves at low and moderate speeds, the results show that our approach outperforms the Signal Strong First (SSF, single criterion approach) and behaves similarly to the Analytic Hierarchy Process combined with the Technique for Order Preferences by Similarity to the Ideal Solution (AHP-TOPSIS, multicriteria approach) regarding the number of handovers and the number of throughput drops. SSF outperforms SIM-Know and AHP-TOPSIS regarding the handover latency metric because SSF runs a straightforward process for making handover decisions. At high speeds, SIM-Know outperforms SSF and AHP-TOPSIS regarding the number of handovers and the number of throughput drops and, further, improves the throughput, delay, jitter, and packet loss in the network. Considering the obtained results, we conclude that SIM-Know is a practical and attractive solution for cognitive HM.

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Section: Sim-knowmentioning

confidence: 99%

A Semantic and Knowledge-Based Approach for Handover Management

Vivas

Rendón

Nieves

2021

Sensors

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“…5 This proposal extended the SDN architecture to comprise four planes (i.e., Management, Application, Control, and Forwarding) and three kinds of interfaces (i.e., Northbound, Southbound, and Management). In a previous work, 2 we modeled such a vertical plane with CIM by proposing particular network instances (e.g., slices, controllers, and apps) to support consistent management and improve the system as a whole. In this paper, we also use such a Vertical Management Plane since it allows and facilitates the implementation and deployment of management functions for all SDN planes.…”

Section: Management Of Sdnmentioning

confidence: 99%

“…Table 2 introduces the related work to our solution by presenting per work: the reference itself, a brief description of the work, SDN plane in which the solution operates, modeling language used for specifying the management tasks, scope (interdomain vs. intradomain), and status (i.e., implementation: functional deployment in a real network, prototype: a development that serves as a proof of concept, and conceptual: nonimplementation/prototype). From the related work analysis, we remark several facts: first, there are a lot of solutions, such as, previous studies, 2,16,17,19,20,22,41,[45][46][47][48] that consider YANG or CIM for network management, but few of them 2,16,17,22 operate in SDN. Second, some works 12,[23][24][25][26]49,50 employ modeling or policy languages or formal notations for specifying their proposals.…”

Section: Related Workmentioning

confidence: 99%

“…1 Software-defined networking (SDN) allows efficient management of networks by offering a centralized logic control, programmable configuration, and interplane communication based on standardized open interfaces. 2 The SDN architecture comprises the Data, Control, Application, Knowledge, and Management Planes. [3][4][5][6][7] The Data Plane is responsible for forwarding data packets.…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, considering the softwarization as an SDN basis, the Management Plane supports FCAPS+P, where the last P corresponds to network programmability management. 2 This paper considers a Vertical Management Mlane since it allows and facilitates the entire SDN's integrated management. 5 The management of SDN faces some challenges, [8][9][10][11][12] such as bootstrapping, performance and scalability, flexibility, decoupling, monitoring and visualization, and continuous changing of network state, as well as the lack of frameworks for integrated network management.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An approach based on Yet Another Next Generation for software‐defined networking management

Montoya-Munoz

Casas-Velasco

Estrada-Solano

et al. 2021

Int J Communication

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The lack of a Management Plane specification in the software-defined networking (SDN) is a fundamental problem for the integrated management of networks that follow this paradigm. Several solutions have addressed this problem, but they do not provide data models intended to support Fault, Configuration, Accounting, Performance, and Security (FCAPS) in SDN from a specialized Management Plane. In this paper, we introduce a technologyagnostic approach that comprises mainly a collection of YANG data models and their relationships. These models characterize SDN management and handle technology heterogeneity. To evaluate our approach, we developed the proof of concept of the YANG data models in an SDN scenario involving the configuration of devices from different vendors supporting diverse technologies. The evaluation results show the efficiency of our approach regarding response time, composition time, consumption time, and network traffic.

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