SCALABILITY IMPROVEMENT OF ACTIVE PROBING FOR FAILURE DETECTION IN LARGE- SCALE SOFTWARE DEFINED NETWORKS USING COMMUNITY DETECTION ALGORITHMS

Document Type

Article

Publication Date

1-1-2023

Abstract

Software-defined networking (SDN) is a networking approach that separates the network's control plane and data plane to provide better network control. The nature of SDN requires an essential focus on its reliability and availability, which includes failure detection aspects. Several techniques have been proposed to enhance SDN failure detection, including passive and active approaches. However, the Route Inspection (RI) algorithm, an example of the active probing method in failure detection, has scalability issues when deployed in large-scale networks as it generates inefficient and lengthy probe paths. To address this, we propose using Community Detection (CD) algorithms to improve the probe path generation of the RI algorithm, resulting in the `Failure Detection using Community Detection and probing (FDCD)' framework. With the aim to reduce travel paths, the proposed framework minimises the network topology using CD algorithms to reduce the topology size into smaller communities. Then, the RI algorithm calculates the probe path in the communities instead of the single large topology, thus improving the efficiency of the failure detection mechanism. This paper adopts three CD algorithms: Louvain, Label Propagation (LP), and GirvanNewman (GN). We evaluate the framework using three well-known network topologies, COST266, PIORO40, and GERMANY50, in Mininet to observe the framework's performance. The results indicate that the proposed approach improves the algorithm's scalability against its baseline approach, improving the average probe round trip time by 66.87% and the average path installation time by 2.67%.

Keywords

Software-Defined Networking, Failure Detection, Active Probing, Community Detection, Scalability

Divisions

fsktm

Publication Title

Malaysian Journal of Computer Science

Volume

36

Issue

4

Publisher

Faculty of Computer Science and Information Technology, University of Malaya

Publisher Location

UNIV MALAYA, FAC COMPUTER SCIENCE & INFORMATION TECH, KUALA LUMPUR, 50603, MALAYSIA

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