AIOPS 2021

Second International Workshop on
Artificial Intelligence for IT Operations

Dubai Virtual, November 22, 2021

Organized by Huawei - TU Berlin Innovation Lab, DOS TU Berlin

Call for Papers

Large-scale IT systems, such as data centers, cloud computing environments, edge clouds, IoT, and embedded environments, are the key enablers of digital transformation. Managing such systems puts an enormous burden on the operators in dealing with the abundance of data, oftentimes leading to severe economic implications. To mitigate this issue, IT operators increasingly rely on tools from artificial intelligence for assistance in the operation of IT systems.

Artificial Intelligence for IT Operations (AIOps) is an emerging field arising in the intersection between the research areas of machine learning, big data, streaming analytics, and the management of IT operations. The main goal is the analysis of system information of heterogeneous type (metrics, logs, customer input, and others) to support administrators by optimizing various objectives like prevention of SLA violation, early anomaly detection and auto-remediation, energy-efficient system operation, providing optimal QoE for customers, predictive maintenance and many more. In this field, a constantly growing interest can be observed, and thus, practical tools are developed from both the academy and industry sectors. We envision that, with the advance of AIOps technologies, the IT industry will achieve significant progress and sustained and exponential growth.

This workshop aims to bring together researchers from both academia and industry to present their experiences, results, and work in progress in this field. We want to strengthen the community and unite it to join the efforts for solving the main challenges the field is currently facing. A consensus and adoption of the principles of openness and reproducibility will boost the research in this emerging area significantly.

Topics of Interest

Early anomaly, fault and failure (AFF) detection and analysis
Self-healing, self-correction and auto-remediation
Self-adaptive time-series based models for prognostics and forecasting
AFF identification, localization, and isolation
Root cause analysis
Adaptive fault tolerance policies
Forecasting of hardware and process quality
Performance management
Planning under uncertainty
Predictive and prescriptive maintenance
Maintenance scheduling and on-demand maintenance planning
Alarm correlation
Log analysis
Fault tolerant system control
Resiliency, reliability, and quality assurance
Software dependability
Autonomic process optimization
Energy-efficient cloud operation
Distributed resource management
Autonomous service provisioning
Visual analytics and interactive machine learning
Active and life-long learning
Design of experiment (DoE) and benchmarking
Fault injection and chaos engineering
Use-cases, testbeds, evaluation scenarios

Submission Details

Authors are invited to submit full papers with a maximum length of 12 pages, including references and appendices using Springer LNCS format. All accepted papers will be included in the workshop proceedings published as part of the Lecture Notes in Computer Science (LNCS) series of Springer. The guidelines can be found at: Springer conference proceedings guidelines.
The authors must upload their paper as PDF file via the following link.
If any problem arises when submitting your paper, please contact aiops2021@googlegroups.com.

Paper submission deadline: ~~September 30, 2021~~ ~~October 07, 2021 at 23:59~~ AOE

All deadlines are in Central European Time (CET = UTC+1).

Review Criteria

Each paper will be reviewed by at least three members of the international program committee for ensuring high quality. Paper acceptance will be based on originality, significance, technical soundness, and clarity of presentation. All accepted papers will be included in the workshop proceedings published as part of the Lecture Notes in Computer Science (LNCS) series of Springer.
At least one author of an accepted paper must register and participate in the workshop. Registration is subject to the terms, conditions, and procedures of the main ICSOC conference to be found on the website: https://www.icsoc.org/.