Application-Driven OAM Framework for Heterogeneous IoT Environments
Author(s) -
Janez Sterle,
Urban Sedlar,
Miha Rugelj,
Andrej Kos,
Mojca Volk
Publication year - 2016
Publication title -
international journal of distributed sensor networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.324
H-Index - 53
eISSN - 1550-1477
pISSN - 1550-1329
DOI - 10.1155/2016/5649291
Subject(s) - computer science , testbed , software deployment , heterogeneous network , distributed computing , variety (cybernetics) , isolation (microbiology) , physical layer , key (lock) , computer network , wireless network , wireless , telecommunications , computer security , artificial intelligence , software engineering , microbiology and biotechnology , biology
We present a novel approach for providing a comprehensive operational picture of heterogeneous networks by collecting system information from physical, data-link, network and application layers using extended methods and mechanisms for OAM, which take into account particularities of persistent access heterogeneity and IoT. A heterogeneous OAM (H-OAM) framework is proposed with a toolset for streamlined failure detection and isolation, and automated performance measurement and monitoring. The framework combines extended standardized OAM toolsets for physical and data-link layers with multiple well-defined and recognized IP network layer toolsets, which introduces possibilities for a tactical view of the monitored system and quick root cause analysis with unified interpretation and cross-correlation of horizontal and vertical levels. A practical deployment of an H-OAM system is presented and its use is demonstrated in a live mobile IoT testbed environment where performance is a function of a wide variety of physical layer parameters that need to be tuned and monitored by the operator. Results of two concrete usage scenarios performed in cooperation with two largest Slovenian mobile operators demonstrate how continuity check and connectivity verification, and performance diagnostics are conducted for Web-based IoT applications and network services of a live operational environment.
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