Name
Abstract | ||
|---|---|---|
Due to the high demands of mobile video streaming, wireless networks have witnessed great pressure on increasing the transmitting rate. Crowdsourcing sets the trend of ensuring direct communication among the participants, thus expanding the bandwidth of networks, shunting the traffic volume of the core networks and improving the video service quality for mobile users. However, irregularly responding to the requestors poses a threat to the battery life of the mobile devices, and decreasing the service time and incomes of the providers remains challenging. To address this challenge, we propose a multi-objective crowdsourcing method, named MCM, for mobile video streaming. Technically, DBSCAN (Density-based Spatial Clustering for Applications with Noise) and IDP (Improved Dynamic Programming) are utilized to generate the service strategies. Consequently, experimental evaluations are conducted to demonstrate the efficiency of MCM. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/ICWS.2019.00043 | 2019 IEEE International Conference on Web Services (ICWS) |
Keywords | Field | DocType |
crowdsourcing,video,mobile environment,energy,time | Wireless network,Dynamic programming,Service quality,Crowdsourcing,Computer science,Computer network,Mobile device,Bandwidth (signal processing),Cluster analysis,Database,DBSCAN | Conference |
ISBN | Citations | PageRank |
978-1-7281-2718-7 | 0 | 0.34 |
References | Authors | |
9 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xu Xiaolong | 1 | 424 | 64.23 |
| Shucun Fu | 2 | 13 | 2.22 |
| Lianyong Qi | 3 | 560 | 57.12 |
| Zhang Xuyun | 4 | 952 | 69.49 |
| Wanchun Dou | 5 | 878 | 96.01 |