Abstract
The widespread adoption of smart mobile devices (SMDs) with advanced computing capabilities presents a valuable resource for mobile crowd computing (MCC). Efficient task scheduling in MCC relies on selecting the right SMDs, which poses a complex multi-criteria decision-making challenge due to the diverse hardware specifications of the devices and the presence of non-compensatory parameters. Traditional multi-criteria decision analysis (MCDA) methods, such as the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), typically assume full compensability between criteria. However, this assumption may conflict with strong sustainability principles. To tackle this issue, the authors introduce the Strong Sustainability Paradigm based Technique for Order Preference by Similarity to Ideal Solution (SSP-TOPSIS) method, an extended version of TOPSIS that incorporates linear compensation reduction. This enhancement allows for a more accurate reflection of sustainability requirements in the decision-making process. The SSP-TOPSIS method demonstrates improved analytical capabilities compared to classical TOPSIS and provides a framework that supports sustainability-driven decisions.
Paper Type
Short Paper
DOI
10.62036/ISD.2025.82
Using SSP-TOPSIS in Sustainable Resource Selection for Mobile Crowd Computing
The widespread adoption of smart mobile devices (SMDs) with advanced computing capabilities presents a valuable resource for mobile crowd computing (MCC). Efficient task scheduling in MCC relies on selecting the right SMDs, which poses a complex multi-criteria decision-making challenge due to the diverse hardware specifications of the devices and the presence of non-compensatory parameters. Traditional multi-criteria decision analysis (MCDA) methods, such as the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), typically assume full compensability between criteria. However, this assumption may conflict with strong sustainability principles. To tackle this issue, the authors introduce the Strong Sustainability Paradigm based Technique for Order Preference by Similarity to Ideal Solution (SSP-TOPSIS) method, an extended version of TOPSIS that incorporates linear compensation reduction. This enhancement allows for a more accurate reflection of sustainability requirements in the decision-making process. The SSP-TOPSIS method demonstrates improved analytical capabilities compared to classical TOPSIS and provides a framework that supports sustainability-driven decisions.
Recommended Citation
Wątróbski, J., Bączkiewicz, A. & Karczmarczyk, A. (2025). Using SSP-TOPSIS in Sustainable Resource Selection for Mobile Crowd ComputingIn I. Luković, S. Bjeladinović, B. Delibašić, D. Barać, N. Iivari, E. Insfran, M. Lang, H. Linger, & C. Schneider (Eds.), Empowering the Interdisciplinary Role of ISD in Addressing Contemporary Issues in Digital Transformation: How Data Science and Generative AI Contributes to ISD (ISD2025 Proceedings). Belgrade, Serbia: University of Gdańsk, Department of Business Informatics & University of Belgrade, Faculty of Organizational Sciences. ISBN: 978-83-972632-1-5. https://doi.org/10.62036/ISD.2025.82