The AnServApp Workshop

09:30 - 10:30

Session 1: AnServApp: Network Management & Observability

Chair: Pál Varga (Budapest University of Technology and Economics, Hungary)

1. SCP-Tracer: Procedure-Aware 5G Core Tracing
Abdelkader Mekrache (Simula Metropolitan Center for Digital Engineering, Norway); Tarik Cicic (Simula Metropolitan Centre for Digital Engineering, Norway) 

2. Design Considerations, Application, and Challenges for Flexible Fixed-Size Telemetry Collection and Aggregation in IOAM
Ramon Bister (Eastern Switzerland University of Applied Sciences & INS Institute for Network and Security, Switzerland); Alexander Clemm (USA); Severin Dellsperger (Eastern Switzerland University of Applied Sciences, Switzerland)

3. Fuzzy Intent Satisfaction for Flexible Conflict Resolution
Attila Frankó, Daniel Ficzere, Gergely Hollósi, Pál Varga and Jozsef Biro (Budapest University of Technology and Economics, Hungary) 

11:00 - 12:30

Session 2: AnServApp: Security & Intelligent Networking

Chair: Abdelkader Mekrache (Simula Metropolitan Center for Digital Engineering, Norway)

1. Cybersecurity for Underwater Wireless Networks and Autonomous Maritime Systems: Challenges and Opportunities
Jeffrey A Adjei, Samer Lahoud, M. I. Heywood and Nur Zincir-Heywood (Dalhousie University, Canada) 

2. Graph-Based Ethereum Transaction Tracking with FollowCyp: A Reproducible Forensic Case Study
Adam Mate and Pál Varga (Budapest University of Technology and Economics, Hungary)

3. Adversarial Robustness of Autoencoder-Based Anomaly Detection in Cloud-Native Microservices: A Systematic White-Box and Black-Box Evaluation
Pedro Tomás (OneSource, Portugal & University of Coimbra, Portugal); Marco Neto, Tomás Dias, Bruno Ferreira and Jorge Proença (OneSource, Portugal); Tiago Cruz (University of Coimbra, Portugal); Luis Cordeiro (OneSource, Portugal) 

4. DUET: Dual-stage Ultra-light Estimator for Cellular Throughput

Darijo Raca (University of Sarajevo, Bosnia and Herzegovina); Ahmed H. Zahran and Gregory Provan (University College Cork, Ireland) 

--- --- --- --- --- ---
Call for Papers

Scope:

The International Workshop on Analytics for Service and Application Management (AnServApp) provides a forum for researchers and practitioners working on the use of data analytics, machine learning, artificial intelligence, and cognitive techniques for service and application management. The workshop welcomes contributions that address how operational data can be transformed into actionable insights, automated decisions, and trustworthy management processes.

Relevant approaches include predictive analytics, data mining, machine learning, deep learning, graph-based analytics, causal inference, anomaly detection, log and trace analysis, foundation models, large language models, and AI-assisted operations. The workshop is particularly interested in methods that support observability, performance management, fault detection and diagnosis, root-cause analysis, service assurance, intent-based management, resource optimization, security analytics, and closed-loop automation. AnServApp also encourages work that examines the reliability, explainability, robustness, and operational trustworthiness of analytics-driven management solutions.

The main goal of AnServApp is to present mature research results, emerging ideas, and work-in-progress contributions in the area of analytics and AI for service and application management. In addition to regular papers, short papers describing late-breaking advances, practical experiences, position papers, and reports from ongoing research are also welcome.

Topics of Interest:

Topics of interest include but are not limited to:

• Analytics, machine learning, and AI for service and application management

• MLOps, LLMOps, observability, and automated operations

• Anomaly detection, incident prediction, and root-cause analysis

• Log, metric, event, and trace analytics

• Resource management & orchestration

• Multi-Agent Reinforcement Learning (RL)

• Distributed RL over communication networks

• Performance, reliability, and service assurance

• Resource management and optimization in cloud, edge, and hybrid environments

• Analytics for microservices, distributed applications, and cloud-native systems

• Intent-based, policy-based, and closed-loop service management

• Explainable, trustworthy, and robust AI for operational decision support

• Security analytics for service and application infrastructures

• Privacy-aware and federated analytics for operational data

• Foundation models and large language models for service management tasks

• Human-in-the-loop analytics and cognitive approaches to operations

• Practical experiences, datasets, benchmarks, and reproducibility studies in service and application analytics

• Verticals:

-          Lower carbon foot print applications / services / systems

-          Industry5.0 applications / services / systems

-          Smart cities and smart transportation services / systems

-          Social media apps / services / systems

-          Smart education services / systems

-          Edge, fog, cloud services / systems

-          Sustainability and resilience of applications / services / systems

-          Digital Twins for networks and services

Paper Submission:

Authors are invited to submit original unpublished papers not under review elsewhere. Papers should be submitted in IEEE 2-column format. Maximum paper length, including title, abstract, all figures, tables, and references, is 6 pages.

Papers have to be submitted electronically in PDF format through the EDAS conference management system, accessible via EDAS: https://anservapp2026.edas.info

For accepted papers, at least one author is expected to register and present the paper in person at the workshop. Accepted papers will be published in the conference proceedings and submitted to IEEE Xplore.

Important dates:

Paper Submission Deadline: August 31, 2026 (extended)

Notification of Acceptance: September 14, 2026

Submission of Camera-ready Version: September 18, 2026

Conference Date: 26 October 2026

Workshop Co-chairs:

·         Pal Varga <pvarga@tmit,bme.hu>, Budapest University of Technology and Economics, Hungary

·         Tokunbo Makanju <makanju@cs.dal.ca>, Dalhousie University, Canada