Abstract
Developing applications on the edge is a difficult
task, as issues arise when multiple nodes have to operate in
unison. Common challenges comprise correctness, performance,
and forensics analysis after a system crash. The challenges are
aggravated when both edge and fog devices get in the picture,
since the limited resources of some of them exacerbate any
possible issue, and create the need for a robust mechanism to
collect log data to make sense of the system’s behavior. The
envisioned monitoring layer should collect log data regarding
performance and errors, protect the data until they are delivered to an external data processing facility, and be easy to
integrate into the deployed system. This paper proposes C-Mon,
a resilience-focused monitoring framework for service-oriented
applications that tests timing constraints against live log data. The
monitoring framework is integrated with OpenAPI Generator,
the mainstream ReST code generator we used to generate client
and server interfaces and monitoring mechanisms. Log data are
cached locally on the disk of the fog/edge devices and transferred
to the monitoring server only when enough CPU cycles and
network bandwidth are available, at the same time enabling
forensics analysis.
task, as issues arise when multiple nodes have to operate in
unison. Common challenges comprise correctness, performance,
and forensics analysis after a system crash. The challenges are
aggravated when both edge and fog devices get in the picture,
since the limited resources of some of them exacerbate any
possible issue, and create the need for a robust mechanism to
collect log data to make sense of the system’s behavior. The
envisioned monitoring layer should collect log data regarding
performance and errors, protect the data until they are delivered to an external data processing facility, and be easy to
integrate into the deployed system. This paper proposes C-Mon,
a resilience-focused monitoring framework for service-oriented
applications that tests timing constraints against live log data. The
monitoring framework is integrated with OpenAPI Generator,
the mainstream ReST code generator we used to generate client
and server interfaces and monitoring mechanisms. Log data are
cached locally on the disk of the fog/edge devices and transferred
to the monitoring server only when enough CPU cycles and
network bandwidth are available, at the same time enabling
forensics analysis.
Originalsprog | Engelsk |
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Titel | 2022 IEEE International Conference on Edge Computing and Communications (EDGE) |
Antal sider | 6 |
Forlag | IEEE |
Publikationsdato | 2022 |
Sider | 153-158 |
ISBN (Trykt) | 978-1-6654-8141-0 |
ISBN (Elektronisk) | 978-1-6654-8140-3 |
DOI | |
Status | Udgivet - 2022 |
Navn | IEEE International Conference on Edge Computing and Communications (EDGE) |
---|---|
ISSN | 2767-9918 |