Document Type
Original Article
Subject Areas
Computer Science
Keywords
Ubiquitous computing (UC), Mobile crowdsourcing, Data collector selection, Task unit bid, Contribution density, FAHP, FTOPSIS
Abstract
In Ubiquitous Computing and the Internet of Things, the sensing and control of objects involve numerous devices collecting and transmitting data. However, connecting these devices without fostering collaboration leads to suboptimal system performance. As the number of connected sensing devices in Internet of Things increases, efficient task accomplishment through collaboration becomes imperative. This paper proposes a Data Collector Selection Method for Collaborative Multi-Tasks to address this challenge, considering task preferences and uncertainty in data collectors' contributions. The proposed method incorporates three key aspects: (1) Using Fuzzy Analytical Hierarchy Process to determine optimal weights for task preferences; (2) Ranking data collectors with Fuzzy Technique for Order Preference by Similarity to Ideal Solution based on preferences and determined weights; and (3) Introducing Contribution Density with Ranking as a metric to measure an individual data collector's contribution to a specific task. Extensive experiments validate the efficacy of the proposed strategy, demonstrating superior performance in balancing system profit and data collector rewards, as well as overall satisfaction scores compared to existing approaches.
How to Cite This Article
Hassan, Belal Z.; Gad-Elrab, Ahmed. A. A.; Farag, Mohamed S.; and Abu-Youssef, S. E.
(2024)
"Data Collector Selection Ranking-Based Method for Collaborative Multi-Tasks in Ubiquitous Environments,"
Al-Azhar Bulletin of Science: Vol. 35:
Iss.
2, Article 1.
DOI: https://doi.org/10.58675/2636-3305.1675