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05-07-2019 | Issue 2/2020

Mobile Networks and Applications 2/2020

Task Allocation in Eco-friendly Mobile Crowdsensing: Problems and Algorithms

Journal:
Mobile Networks and Applications > Issue 2/2020
Authors:
Wei Gong, Xiaoyao Huang, Baoxian Zhang, Yawei Zhao
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Abstract

Mobile crowdsensing has emerged as a new sensing paradigm which has many advantages over traditional sensing paradigms. In this paper, we focus on the task allocation problem for eco-friendly mobile crowdsensing which aims to minimize carbon emissions under various constraints such as task deadline and road traffic constraints. We first describe the system model of eco-friendly mobile crowdsensing and formulate the task allocation problem in offline scenario and online scenario, respectively. Then we propose Eco-Friendly Task Allocation algorithm (EFTA) to address the allocation problem in offline scenario. This algorithm consists of two processes including transportation selection and worker-task matching. After this, we propose Online Eco-Friendly Task Allocation algorithm (OEFTA) to tackle the allocation problem in online scenario. The algorithm adopts greedy online task assignment/reassignment upon arrival of a new task or a new worker. Extensive simulation results show our proposed algorithms have much better performance than baseline algorithms.

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