arrow
返回

Optimizing Wirelessly Powered Crowd Sensing: Trading Energy for Data

delete
delete0
PRE
AI
DOI:delete
delete原文链接
delete原文求助
delete分享
delete收藏
摘要

摘要

En 中文
To overcome the limited coverage in traditional wireless sensor networks, mobile crowd sensing (MCS) has emerged as a new sensing paradigm. To achieve longer battery lives of user devices and incentivize human involvement, this paper presents a novel approach that seamlessly integrates MCS with wireless power transfer, named wirelessly powered crowd sensing (WPCS), for supporting crowd sensing with energy consumption and offering rewards as incentives. An optimization problem is formulated to simultaneously maximize the data utility and minimize the energy consumption for service operator, by jointly controlling wireless-power allocation at the access point (AP) as well as sensing-data size, compression ratio, and sensor-transmission duration at the mobile sensor (MS). Given the fixed compression ratios, the optimal power allocation policy is shown to have a threshold-based structure with respect to a defined crowd-sensing priority function for each MS. Given fixed sensing-data utilities, the compression policy achieves the optimal compression ratio. Extensive simulations are also presented to verify the efficiency of the contributed mechanisms.
Keyword:
NETWORKS

期刊

I
IEEE International Conference on Communications Workshops (ICC Workshops)
IF:
0
论文数:
9
被引数:
0

机构

暂无机构信息
引用论文

引用论文

暂无论文信息