[AISWorld] AIOPS 2020 (Call for Papers)

[Bogatinovski, Jasmin]

Dear researcher,

we are very excited to announce the organization of the International Workshop for AIOPS (AIOPS2020). Following the ever greatest interest in that area, we are strongly devoted to the appearance of high-quality research papers aiming to depict the landscape for our community. Our goal is to bring the community together, identify the most relevant problems and open a possibility for further collaborations. To further confirm our strong interest, we choose to collocate the workshop with the A-ranked ICSOC (International Conference on Service-Oriented Computing) 2020, Dubai, UAE, 14-17.12.2020.

Therefore, we announce our call for research papers, looking for novel and innovative methods in the area of artificial intelligence in the field system operation.

More information can be found at https://aiopsworkshop.github.io/

Submissions are now open at https://easychair.org/conferences/?conf=aiops2020

The official Call for Papers can be found at: https://easychair.org/cfp/AIOPS2020

Abstract registration deadline: August 8, 2020
Submission deadline: August 16, 2020

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*CFP*

Large-scale systems of all types, such as data centres, cloud computing environments, edge clouds, IoT and embedded environments, are becoming more and more complex. Managing such systems only with human resources puts an enormous burden on the operators and scales poorly from an economic perspective. To mitigate this issue IT operators increasingly rely on tools from artificial intelligence for assistance.

Artificial Intelligence for IT Operations (AIOps) is an emerging field arising in the intersection between the research areas of machine learning, big data and streaming analytics, and the management of IT operations. The main aim is to analyze system information of different kinds (metrics, logs, customer input, etc) 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.

As a result, AIOps progress towards a future standard for IT operation management. However, the combination of previously separate research fields brings many challenges. Novel modeling techniques are needed that help to understand the dynamics of different systems, laying out the basis for assessing time horizons and uncertainty for imminent SLA violations, the early detection of emerging problems, autonomous remediation, decision making, and support, and various optimization objectives. Furthermore, a good understanding and interpretability of these aiding models are especially important for building trust between the employed tools and the domain experts. This will result in faster adoption of AIOps and further increase the interest in this research field.

The main aim of this workshop is 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 towards the goal of joining 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.


List of topics:

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
Decision support
Planning under uncertainty
Predictive and prescriptive maintenance
Maintenance scheduling and on-demand maintenance planning
Fault-tolerant system control
Reliability and quality assurance
Autonomic process optimization
Energy-efficient cloud operation
Autonomous service provisioning
Explainable AI for Systems
Visual analytics and interactive machine learning
Active and life-long learning
Information and communication models for AIOps systems
Platforms: Time-series DBs, Streaming, Data Lakes
AI platforms for AIOps
Design of experiment (DoE) for different use-cases, testbeds, evaluation scenarios


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.


Organizers,

Odej Kao, Technical University Berlin

Jorge Cardoso, Huawei Research