Multi-Task oriented data diffusion and transmission paradigm in crowdsensing based on city public traffic
| Autor: | Jian An, Xiaolin Gui, Zhenlong Peng, Tianjie Wu, Ruowei Gui |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Diffusion (acoustics)
Computer Networks and Communications Computer science Real-time computing 020206 networking & telecommunications 02 engineering and technology Task (computing) Crowdsensing Transmission (telecommunications) Transfer (computing) 0202 electrical engineering electronic engineering information engineering Redundancy (engineering) 020201 artificial intelligence & image processing Budget constraint |
| Zdroj: | Computer Networks. 156:41-51 |
| ISSN: | 1389-1286 |
| DOI: | 10.1016/j.comnet.2019.03.020 |
| Popis: | As mobile smart devices become increasingly popular and are equipped with increasingly powerful sensors, they have been pervasively applied in crowdsensing as effective tools to solve large-scale sensing tasks in urban areas. Task requesters can allocate sensing tasks to mobile nodes through a crowdsensing platform, eliminating the cost of deploying and maintaining large numbers of fixed sensors. However, several kinds of crowdsensing tasks (e.g., audio and video transmission) that generate large-scale sensed data may bring high network traffic costs to participants using a 3G/4G network, which may affect their satisfaction. In this paper, we build a data diffusion and transmission paradigm in crowdsensing based on City Public Traffic System (PTS), and thoroughly discuss a paradigm for Multi-Task diffusion and transmission within budget constraints. This paradigm makes full use of the advantages of a bus in PTS to realize the rapid transmission of large-scale sensed data: predictable trajectory, wide coverage area, fast moving speed and long contact duration among passengers. Further, we also propose a new data transmission algorithm called BUI-BA that chooses mobile nodes to transfer data by maximizing the transmission utility increment. The experimental results demonstrate that BUI-BA has better overall performance than widely used Greedy and effSense, achieving a tradeoff between overall transmission utility and transmission redundancy. |
| Databáze: | OpenAIRE |
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