SEAMS 2020
Mon 29 June - Fri 3 July 2020
co-located with ICSE 2020

The rapidly changing workload of service-based systems can easily cause under-/over-utilization on the component services, which can consequently affect the overall Quality of Service (QoS), such as latency. Self-adaptive services composition rectifies this problem, but poses several challenges: (i) the effectiveness of adaptation can deteriorate due to over-optimistic assumptions on the latency and utilization constraints, at both local and global levels; and (ii) the benefits brought by each composition plan is often short term and is not often designed for long-term benefits – a natural prerequisite for sustaining the system. To tackle these issues, we propose a two levels constraint reasoning framework for sustainable self-adaptive services composition, called DATESSO. In particular, DATESSO consists of a re ned formulation that differentiates the “strictness” for latency/utilization constraints in two levels. To strive for long-term benefits, DATESSO leverages the concept of technical debt and time-series prediction to model the utility contribution of the component services in the composition. The approach embeds a debt-aware two level constraint reasoning algorithm in DATESSO to improve the efficiency, effectiveness and sustainability of self-adaptive service composition. We evaluate DATESSO on a service-based system with real-world WS-DREAM dataset and comparing it with other state-of-the-art approaches. The results demonstrate the superiority of DATESSO over the others on the utilization, latency and running time whilst likely to be more sustainable.

Tue 30 Jun

Displayed time zone: (UTC) Coordinated Universal Time change

06:00 - 07:30
Session 2: Testing, Analysis, Reasoning, and MonitoringSEAMS 2020 at SEAMS
Chair(s): Sona Ghahremani Hasso Plattner Institute, University of Potsdam
06:00
5m
Talk
Leveraging Test Logs for Building a Self-Adaptive Path PlannerNIER
SEAMS 2020
Kun Liu Peking University, China, Xiaoyi Zhang National Institute of Informatics, Japan, Paolo Arcaini National Institute of Informatics , Fuyuki Ishikawa National Institute of Informatics, Wenpin Jiao Peking University, China
Pre-print Media Attached
06:05
5m
Talk
Supporting Viewpoints to Review the Lack of Requirements in Space Systems with Machine LearningExperience
SEAMS 2020
Kenji Mori Japan Aerospace Exploration Agency, Japan, Naoko Okubo Japan Aerospace Exploration Agency, Japan, Yasushi Ueda Japan Aerospace Exploration Agency, Japan, Masafumi Katahira Japan Aerospace Exploration Agency, Toshiyuki Amagasa University of Tsukuba, Japan
Media Attached
06:10
5m
Talk
DATESSO: Self-Adapting Service Composition with Debt-Aware Two Levels Constraint ReasoningTechnicalBest Student Paper
SEAMS 2020
Satish Kumar University of Birmingham, United Kingdom, Tao Chen Loughborough University, Rami Bahsoon University of Birmingham, Rajkumar Buyya University of Melbourne, Australia
DOI Pre-print Media Attached
06:15
5m
Talk
Towards Bridging the Gap between Control and Self-Adaptive System PropertiesNIER
SEAMS 2020
Javier Camara University of York, Alessandro Vittorio Papadopoulos Mälardalen University, Thomas Vogel Humboldt-Universität zu Berlin, Danny Weyns KU Leuven, David Garlan Carnegie Mellon University, Shihong Huang Florida Atlantic University, Kenji Tei Waseda University / National Institute of Informatics, Japan
DOI Pre-print Media Attached
06:20
5m
Talk
Explanation for Human-on-the-loop: a probabilistic model checking approachNIER
SEAMS 2020
NIANYU LI Peking University, China, Sridhar Adepu Singapore University of Technology and Design, Singapore, Eunsuk Kang Carnegie Mellon University, David Garlan Carnegie Mellon University
Pre-print Media Attached
06:25
65m
Other
Q&A and Discussion (Session 2)
SEAMS 2020