联合区域热度和社交属性感知的移动群智感知参与者选择机制

doi:10.11959/j.issn.1000-0801.2020050

Abstract

Abstract:

Aiming at the problem of tasks that are low reliability acquired by platform and difficult to accomplish on time in user sparse area.A participant selection mechanism that combines regional heat and social attribute aware was proposed.Firstly,considering the influence of different regional heat on task completion,the regional heat was evaluated according to the number of active users,the average residence time of users and the completion of historical task.Secondly,in order to analyze the impact of user social attributes on task completion,the user willingness,reputation and activity were calculated by combining the status information of users and the historical task record of users.Finally,by taking the above factors into account,two different mechanisms of participant selection for social attribute perception were designed for high and low heat areas to maximize quality and number oftask completionrespectively.The results show that the proposed mechanism can significantly improve the overall data quality,and can also perform sensing tasks in sparse areas on time.Meanwhile,compared with SUR and GGA-I,the failure rate is reduced by 66.7% and 50.6% respectively.

Key words: mobile crowd sensing, participant selection, regional heat, social attribute

CLC Number:

TP393

Luoyong XIANG,Wen CHEN,Luyang ZHANG. Regional heat and social attribute aware participant selection mechanis in mobile crowd sensing[J]. Telecommunications Science, 2020, 36(2): 24-34.

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References 15

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参数	参数值
区域面积/km²	1~2
区域热度	0~1
任务的截止时间/min	5~45
单个任务需要的参与者数量/个	1~5
每个参与者接受的任务数/个	0~8
服务平台任务数量/个	1~100
任务覆盖半径/m	200~1 600
参与者的信誉度	0~1
参与者的活跃度	0~1
参与者的移动速度/（km·h^-1）	10~50
感知任务的种类/个	5

Regional heat and social attribute aware participant selection mechanis in mobile crowd sensing

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