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SEAMS 2022
Mon 23 - Tue 24 May 2022
co-located with ICSE 2022
Wed 18 May 2022 10:55 - 11:05 at SEAMS room - Learning Chair(s): Ivana Dusparic, Pooyan Jamshidi

Video

Internet of Things (IoT) is a pivotal technology in application domains that require connectivity and interoperability between large numbers of devices. IoT systems predominantly use a software-defined network (SDN) architecture as their core communication backbone. This architecture offers several advantages, including the flexibility to make IoT networks self-adaptive through software programmability. In general, self-adaptation solutions need to periodically monitor, reason about, and adapt a running system. The adaptation step involves generating an adaptation strategy and applying it to the running system whenever an anomaly arises. In this paper, we argue that, rather than generating individual adaptation strategies, the goal should be to adapt the logic / code of the running system in such a way that the system itself would learn how to steer clear of future anomalies, without triggering self-adaptation too frequently. We instantiate and empirically assess this idea in the context of IoT networks. Specifically, using genetic programming (GP), we propose a self-adaptation solution that continuously learns and updates the control constructs in the data-forwarding logic of SDN-based IoT networks. Our evaluation, performed using open-source synthetic and industrial data, indicates that, compared to a baseline adaptation technique that attempts to generate individual adaptations, our GP-based approach is more effective in resolving network congestion, and further, reduces the frequency of adaptation interventions over time. In addition, we compare our approach against a standard data-forwarding algorithm from the network literature, demonstrating that our approach significantly reduces packet loss.

Wed 18 May

Displayed time zone: Eastern Time (US & Canada) change

10:45 - 12:15
Learning SEAMS 2022 at SEAMS room
Chair(s): Ivana Dusparic Trinity College Dublin, Ireland, Pooyan Jamshidi University of South Carolina
10:45
10m
Paper
Lifelong Self-Adaptation: Self-Adaptation Meets Lifelong Machine LearningBest Student Paper AwardResearch Paper
SEAMS 2022
Omid Gheibi Katholieke Universiteit Leuven, Danny Weyns KU Leuven
Pre-print
10:55
10m
Paper
Learning Self-adaptations for IoT Networks: A Genetic Programming ApproachResearch Paper
SEAMS 2022
Jia Li University of Ottawa, Shiva Nejati University of Ottawa, Mehrdad Sabetzadeh University of Ottawa
Pre-print Media Attached
11:05
10m
Paper
Taming Model Uncertainty in Self-adaptive Systems Using Bayesian Model AveragingResearch Paper
SEAMS 2022
Matteo Camilli Free University of Bozen-Bolzano, Raffaela Mirandola Politecnico di Milano, Patrizia Scandurra University of Bergamo, Italy
Pre-print
11:15
5m
Paper
Emergent Web Server: An Exemplar to Explore Online Learning in Compositional Self-Adaptive SystemsArtifact Paper
SEAMS 2022
Roberto Rodrigues Filho Federal University of Goiás, Elvin Alberts , Ilias Gerostathopoulos Vrije Universiteit Amsterdam, Barry Porter Lancaster University, Fabio Costa
Pre-print
11:20
55m
Panel
Discussion
SEAMS 2022

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Wed 18 May 2022 10:45 - 12:15 at SEAMS room - Learning Chair(s): Ivana Dusparic, Pooyan Jamshidi
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