research-article

ADAM: Adaptive Monitoring of Runtime Anomalies in Small Uncrewed Aerial Systems

Authors:

Md Nafee Al Islam,

Jane Cleland-Huang,

Michael VierhauserAuthors Info & Claims

SEAMS '24: Proceedings of the 19th International Symposium on Software Engineering for Adaptive and Self-Managing Systems

Pages 44 - 55

https://doi.org/10.1145/3643915.3644092

Published: 07 June 2024 Publication History

Abstract

Small Uncrewed Aerial Systems (sUAS), commonly referred to as drones, have become ubiquitous in many domains. Examples range from drones taking part in search-and-rescue operations to drones being used for delivering medical supplies or packages. As sUAS commonly exhibit safety-critical behavior, ensuring their safe operation has become a top priority. Thus, continuous and rigorous monitoring of sUAS at runtime is essential. However, sUAS generate vast amounts of data, for example, multi-variate time series which need to be analyzed to detect potential emerging issues. This poses a significant challenge, due to resource constraints imposed on the onboard computation capabilities of sUAS. To alleviate this problem, we introduce ADAM, a novel adaptive monitoring anomaly detection framework for sUAS. ADAM selectively monitors a subset of data streams, which serve as indicators of anomalous behavior. In the event of a raised alert, ADAM adjusts its monitoring strategy, enabling additional detectors and taking further mitigation actions. We evaluated the effectiveness of ADAM through simulations in Gazebo, analysis of real flight logs taken from sUAS forums, and tests with real drones. Results confirm that ADAM can enhance safety and efficiency of sUAS operations, by dynamically managing anomaly detection, reducing CPU and memory usage by up to 65%.

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Cited By

Purandare SCohen M(2024)Exploration of Failures in an sUAS Controller Software Product LineProceedings of the 28th ACM International Systems and Software Product Line Conference10.1145/3646548.3672597(125-135)Online publication date: 2-Sep-2024
https://dl.acm.org/doi/10.1145/3646548.3672597

Index Terms

ADAM: Adaptive Monitoring of Runtime Anomalies in Small Uncrewed Aerial Systems
1. Computer systems organization
  1. Embedded and cyber-physical systems
    1. Sensors and actuators
  2. Real-time systems
    1. Real-time operating systems
2. Software and its engineering
  1. Software notations and tools
    1. Development frameworks and environments

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cover image ACM Conferences

SEAMS '24: Proceedings of the 19th International Symposium on Software Engineering for Adaptive and Self-Managing Systems

April 2024

233 pages

ISBN:9798400705854

DOI:10.1145/3643915

Chair:
Luciano Baresi
Politecnico di Milano, Italy
,
Program Chair:
Xiaoxing Ma
Nanjing University, China
,
Program Co-chair:
Liliana Pasquale
University College Dublin & Lero, Ireland

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Published: 07 June 2024

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SEAMS '24: 19th International Symposium on Software Engineering for Adaptive and Self-Managing Systems

April 15 - 16, 2024

AA, Lisbon, Portugal

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Overall Acceptance Rate 17 of 31 submissions, 55%

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Cited By

Purandare SCohen M(2024)Exploration of Failures in an sUAS Controller Software Product LineProceedings of the 28th ACM International Systems and Software Product Line Conference10.1145/3646548.3672597(125-135)Online publication date: 2-Sep-2024
https://dl.acm.org/doi/10.1145/3646548.3672597

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