Quality-Aware Sensing Coverage in Budget-Constrained Mobile Crowdsensing Networks

Mobile crowdsensing has shown elegant capacity in data collection and has given rise to numerous applications. In the sense of coverage quality, marginal works have considered the efficient (less cost) and effective (considerable coverage) design for mobile crowdsensing networks. We investigate the...

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Vydáno v:IEEE transactions on vehicular technology Ročník 65; číslo 9; s. 7698 - 7707
Hlavní autoři: Zhang, Maotian, Yang, Panlong, Tian, Chang, Tang, Shaojie, Gao, Xiaofeng, Wang, Baowei, Xiao, Fu
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.09.2016
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Approximation algorithm
Approximation algorithms
Approximation methods
coverage
Mobile communication
Mobile computing
mobile crowdsensing networks
Optimization
quality-aware sensing
Sensors
Trajectory
ISSN:0018-9545, 1939-9359
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Shrnutí:Mobile crowdsensing has shown elegant capacity in data collection and has given rise to numerous applications. In the sense of coverage quality, marginal works have considered the efficient (less cost) and effective (considerable coverage) design for mobile crowdsensing networks. We investigate the optimal quality-aware coverage in mobile crowdsensing networks. The difference between ours and the conventional coverage problem is that we only select a subset of mobile users so that the coverage quality is maximized with constrained budget. To address this new problem, which is proved to be NP-hard, we first prove that the set function of coverage quality is nondecreasing submodular. By leveraging the favorable property in submodular optimization, we then propose an (1 - (1/e)) approximation algorithm with O(n k+2 ) time complexity, where k is an integer that is greater than or equal to 3. Finally, we conduct extensive simulations for the proposed scheme, and the results demonstrate that ours outperforms the random selection scheme and one of the state of the art in terms of total coverage quality by, at most, 2.4× and 1.5× and by, on average, 1.4× and 1.3×, respectively. Additionally, ours achieves a near-optimal solution, compared with the brute-force search results.
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ISSN:0018-9545
1939-9359
DOI:10.1109/TVT.2015.2490679