Computer Science ›› 2022, Vol. 49 ›› Issue (5): 371-379.doi: 10.11896/jsjkx.210200005
• Interdiscipline & Frontier • Previous Articles
LI Xiao-dong1, YU Zhi-yong1,2, HUANG Fang-wan1,2, ZHU Wei-ping1, TU Chun-yu1, ZHENG Wei-nan1
CLC Number:
[1]GAO R W.Reshaping the relationship between inland rivers and people’s livelihood from the perspective of humanism:A study on the comprehensive accessibility of inland rivers in Fuzhou[J].Fujian Architecture,2020(8):1-9. [2]Fuzhou Urban and Rural Construction Bureau.Measures for the Management of Urban Inland Rivers in Fuzhou[R].Fuzhou,2019. [3]DUTTA J,CHOWDHURY C,ROY S,et al.Towards smartcity:sensing air quality in city based on opportunistic crowd-sensing[C]//Proceedings of the 18th International Conference on Distributed Computing and Networking.2017:1-6. [4]GANTI R K,YE F,LEI H.Mobile crowdsensing:current state and future challenges[J].IEEE Communications Magazine,2011,49(11):32-39. [5]RADU V,KRIARA L,MARINA M K.Pazl:A mobile crowd-sensing based indoor WiFi monitoring system[C]//Proceedings of the 9th International Conference on Network and Service Management (CNSM 2013).IEEE,2013:75-83. [6]CARDONE G,FOSCHINI L,BELLAVISTA P,et al.Fostering participaction in smart cities:a geo-social crowdsensing platform[J].IEEE Communications Magazine,2013,51(6):112-119. [7]GUO W,ZHU W,YU Z,et al.A survey of task allocation:Contrastive perspectives from wireless sensor networks and mobile crowdsensing[J].IEEE Access,2019,7:78406-78420. [8]LIU Y,GUO B,WU W L,et al.Research on the method of selecting multitask participants for mobile group intelligence perception[J].Chinese Journal of Computers,2017,40(8):1872-1887. [9]LI H.Participant Selection and Task Assignment in MobileCrowd Sensing[D].Charlott:University of North Carolina at Charlotte,2018. [10]LUDWIG T,REUTER C,PIPEK V.What you see is what I need:Mobile reporting practices in emergencies[C]//ECSCW 2013:Proceedings of the 13th European Conference on Compu-ter Supported Cooperative Work.London:Springer,2013:181-206. [11]DUTTA J,GAZI F,ROY S,et al.AirSense:Opportunistic crowd-sensing based air quality monitoring system for smart city[C]//Sensors.IEEE,2017. [12]QIN Z,ZHU Y.NoiseSense:A crowd sensing system for urban noise mapping service[C]//2016 IEEE 22nd International Conference on Parallel and Distributed Systems (ICPADS).IEEE,2016:80-87. [13]RAMBURN T,BADOREEA D,CHEERKOOT-JALIM S.Drive-MU:A Real-time Road-Traffic Monitoring Android Application for Mauritius[C]//2019 Conference on Next Generation Computing Applications (NextComp).IEEE,2019:1-8. [14]EL KHAILI M,BAKKOURY J,KHIAT A,et al.Crowdsour-cing by IoT using LabVIEW for Measuring the Air Quality[C]//Proceedings of the 3rd International Conference on Smart City Applications.2018:1-8. [15]LEE H P,GARG S,LIM K M.Crowdsourcing of environmental noise map using calibrated smartphones[J].Applied Acoustics,2020,160:107130. [16]JING Y,GUO B,LIU Y,et al.CrowdTracker:object trackingusing mobile crowd sensing[C]//Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers.2017:85-88. [17]KIM K,ZABIHI H,KIM H,et al.TrailSense:A crowdsensing system for detecting risky mountain trail segments with walking pattern analysis[J].Proceedings of the ACM on Interactive,Mobile,Wearable and Ubiquitous Technologies,2017,1(3):1-31. [18]WU F,YANG S,ZHENG Z,et al.Fine Grained User Profiling for Personalized Task Matching in Mobile Crowdsensing[J].IEEE Transactions on Mobile Computing,2020,1(1):99-112. [19]SONG Z,ZHANG B,LIU C H,et al.QoI-aware energy-efficient participant selection[C]//2014 Eleventh Annual IEEE International Conference on Sensing,Communication,and Networking (SECON).IEEE,2014:248-256. [20]LI H,LI T,WANG Y.Dynamic participant recruitment of mobile crowd sensing for heterogeneous sensing tasks[C]//2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems.IEEE,2015:136-144. [21]ZHANG D,XIONG H,WANG L,et al.CrowdRecruiter:selecting participants for piggyback crowdsensing under probabilistic coverage constraint[C]//Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing.2014:703-714. [22]REDDY S,ESTRIN D,SRIVASTAVA M.Recruitment framework for participatory sensing data collections[C]//Interna-tional Conference on Pervasive Computing.Berlin:Springer,2010:138-155. [23]YU Z,ZHOU J,GUO W,et al.Participant selection for t-sweep k-coverage crowd sensing tasks[J].World Wide Web,2018,21(3):741-758. [24]LV Q,GU J Q,XU S,et al.Structure and characteristics of the automatic monitoring system for rivers in Suzhou city[J].Urban and Rural Construction,2015(4):82-84. [25]CHEN Z Q.Research on Intelligent Video Monitoring System under “River Chief System”[D].North China University of Water Conservancy and Hydropower,2019. [26]TANG X Y.Design and development of an intelligent waterquality monitoring platform for unmanned ships[D].Haikou:Hainan University,2018. [27]KARP R M.Reducibility among combinatorial problems[M]//Complexity of Computer Computations.Boston:Springer,1972:85-103. [28]JUN W,DUAN L I.A New Implicit Enumeration Method for Polynomial 0-1 Programming and Applications[J].Systems Engineering-Theory & Practice,2007 (3):2. [29]LU S H,HU M H.Multi-airport GDP release strategy based on heuristic implicit enumeration algorithm[J].Journal of Wuhan Institute of Technology,2010,32(1):97-99. [30]KENNEDY J,EBERHART R.Particle swarm optimization[C]//Proceedings of ICNN’95-International Conference on Neural Networks.IEEE,1995:1942-1948. [31]EBERHART R,KENNEDY J.A new optimizer using particleswarm theory[C]//Proceedings of the Sixth International Symposium on Micro Machine and Human Science(MHS’95).IEEE,1995:39-43. [32]SHEN L C,HUO X H,NIU Y F.Overview of the Research Status of Discrete Particle Swarm Optimization Algorithms[J].Systems Engineering and Electronics,2008(10):1986-1990. |
[1] | LIU Zhang-hui, ZHENG Hong-qiang, ZHANG Jian-shan, CHEN Zhe-yi. Computation Offloading and Deployment Optimization in Multi-UAV-Enabled Mobile Edge Computing Systems [J]. Computer Science, 2022, 49(6A): 619-627. |
[2] | ZHANG Hong-ying, SHEN Rong-miao, LUO Qian. Study on Optimal Scheduling of Gate Based on Mixed Integer Programming [J]. Computer Science, 2020, 47(8): 278-283. |
[3] | LI Jian-Jun, WANG Xiao-ling, YANG Yu and FU Jia. Emergency Task Assignment Method Based on CQPSO Mobile Crowd Sensing [J]. Computer Science, 2020, 47(6A): 273-277. |
[4] | ZHOU Xin-yue, QIAN Li-ping, HUANG Yu-pin, WU Yuan. Optimization Method of Electric Vehicles Charging Scheduling Based on Ant Colony [J]. Computer Science, 2020, 47(11): 280-285. |
[5] | LIU Dan. Fog Computing and Self-assessment Based Clustering and Cooperative Perception for VANET [J]. Computer Science, 2020, 47(10): 55-62. |
[6] | LI Zhuo, XU Zhe, CHEN Xin, LI Shu-qin. Location-related Online Multi-task Assignment Algorithm for Mobile Crowd Sensing [J]. Computer Science, 2019, 46(6): 102-106. |
[7] | ZHENG Fei-feng, JIANG Juan, MEI Qi-huang. Study on Stowage Optimization in Minimum Container Transportation Cost [J]. Computer Science, 2019, 46(6): 239-245. |
[8] | ZHENG Xiang-ping, YU Zhi-yong, WEN Guang-bin. Community Discovery in Location Network [J]. Computer Science, 2018, 45(6): 46-50. |
[9] | ZHOU Jie, YU Zhi-yong, GUO Wen-zhong, GUO Long-kun and ZHU Wei-ping. Participant Selection Algorithm for t-Sweep k-Coverage Crowd Sensing Tasks [J]. Computer Science, 2018, 45(2): 157-164. |
[10] | ZENG Zi-yi, QIU Han, ZHU Jun-hu, ZHOU Tian-yang. Network Security Experiment Environment Multi-emulation Planning Based on Capability Measurement [J]. Computer Science, 2018, 45(11): 160-163. |
[11] | JIA Xin and ZHANG Shao-ping. Research on Wear Leveling Algorithm of NAND FLASH Memory Based on Greedy Strategy [J]. Computer Science, 2017, 44(Z11): 312-316. |
[12] | LIU Wei, ZHAO Yu and CHEN Rui. Zero-One Integer Programming Based Optimization Model and Two-phase Resource Optimization Algorithm for Wireless Ad hoc Networks [J]. Computer Science, 2017, 44(1): 103-108. |
[13] | HE Xin, LIU Tian-xu, DING Shuang and BAI Lin. Optimization Selection Mechanism for Service Nodes in Hybrid Crowd Sensing [J]. Computer Science, 2017, 44(1): 113-116. |
[14] | YANG Bei, ZHOU Lan-jiang, YU Zheng-tao and LIU Li-jia. Research on Semi-supervised Learning Based Approach for Lao Part of Speech Tagging [J]. Computer Science, 2016, 43(9): 103-106. |
[15] | LI Yu-ling, WANG Xiu-ling and ZHOU Jian-ming. Cooperative Electromagnetic Compatibility Control Complexity Optimization Algorithm Based on Cluster Filter for Mobile Crowd Sensing [J]. Computer Science, 2016, 43(4): 115-117. |
|