Paper Info
Title
Crowdsensing Task Assignment Based on Particle Swarm Optimization in Cognitive Radio Networks.
Abstract
Cognitive radio technology allows unlicensed users to utilize licensed wireless spectrum if the wireless spectrum is unused by licensed users. Therefore, spectrum sensing should be carried out before unlicensed users access the wireless spectrum. Since mobile terminals such as smartphones are more and more intelligent, they can sense the wireless spectrum. The method that spectrum sensing task is assigned to mobile intelligent terminals is called crowdsourcing. For a large-scale region, we propose the crowdsourcing paradigm to assign mobile users the spectrum sensing task. The sensing task assignment is influenced by some factors including remaining energy, locations, and costs of mobile terminals. Considering these constraints, we design a precise sensing effect function with a local constraint and aim to maximize this sensing effect to address crowdsensing task assignment. The problem of crowdsensing task assignment is difficult to solve since we prove that it is NP-hard. We design an optimal algorithm based on particle swarm optimization to solve this problem. Simulation results show our algorithm achieves higher performance than the other algorithms.
Year
DOI
Venue
2017
10.1155/2017/4687974
WIRELESS COMMUNICATIONS & MOBILE COMPUTING
Field
DocType
Volume
Particle swarm optimization,Wireless,Computer science,Crowdsensing,Crowdsourcing,Computer network,Cognitive radio,Distributed computing
Journal
2017
ISSN
Citations 
PageRank 
1530-8669
2
0.38
References 
Authors
11
2
Name
Order
Citations
PageRank
Linbo Zhai152.13
Hua Wang27614.82