.png){kind=icon}
返回
CSSA-based collaborative optimization recommendation of users in mobile crowdsensing
.png){kind=icon}
PRE
AI
DOI：10.1007/s12083-022-01444-y.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
With the large-scale popularization of mobile terminals, crowd sensing technology has gradually replaced the existing static sensors with its efficient and low-cost advantages as an emerging data collection method. How to quickly allocate the sensing task to the optimal execution user under the premise of ensuring the perceived quality and reducing the cost is the focus of the research. In this regard, this paper proposes a Crowd sensing Sparrow Search Algorithm (CSSA) collaborative optimization recommendation method that combines fitness priority, collaboration, and intelligent optimization algorithms, and uses it for task allocation problems. Firstly, the concept of fitness is proposed to calculate the location, power, equipment and reputation of the perceived user, and analyze the matching degree of the user to the task. Secondly, according to the different fitness, the user is divided into explorers and followers, and the two cooperate to complete the perception task. Thirdly, in the process of solving the optimal task allocation scheme, CSSA intelligent optimization algorithm is used to simulate the process of users completing tasks, and the selected user results can be obtained after limited iterations. Through the comparative experiments of the proposed algorithm and other optimization algorithms in the same environment, the results show that it has higher performance in solving the task allocation problem.
Keyword:
Mobile crowdsensing
Sparrow search algorithm
Task allocation
User collaboration
Priority
期刊
IF:
2.6
论文数:
2.2K
被引数:
2.9K
机构
引用论文
Online Quality-Aware Incentive Mechanism for Mobile Crowd Sensing with Extra Bonus具有额外奖金的移动人群感知在线质量感知激励机制
PREAI
分享收藏El Niño - Southern Oscillation and its Effects on Air Pressure, Air Temperature and Precipitation in Europe in the 20th Century厄尔尼诺-南方涛动及其对20世纪欧洲大气压、气温和降水的影响.png)
Geografie
OAAI
GeografieIF0
OAAI分享收藏分享收藏
查看更多内容