Ranked k-NN Crowdsourced Model for Cloud Internet of Things (CIoT)
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How to Cite

Duraipandian, M. 2020. “Ranked K-NN Crowdsourced Model for Cloud Internet of Things (CIoT)”. Journal of ISMAC 2 (3): 173-80. https://doi.org/10.36548/jismac.2020.3.006.

Keywords

— Cloud Computing
— Crowdsourcing
— Internet of Things
Published: 10-07-2020

Abstract

Internet of Things (IoT) has gained more attention in recent years and its influence over future internet is projected to be more as a promising technology. IoT enables sensors to merge with smart devices to monitor, observe and analyse the real time data. These features make the IoT, a suitable technology, for smart applications. On the other hand, cloud offers a better computing paradigm to store and analyse the data. Cloud reduces the complexities in day today life with its novel applications and services, in an efficient manner. However, present IoT and Cloud solutions are focused towards centralized solutions, which limits the user capacity. To enrich the Cloud integrated IoT benefits, a flexible large-scale data collection and analysis is introduced as crowdsourcing, which provides a new dimension in data mining applications. This research work presents a cloud computing crowdsourced data analysis model implemented over IoT, to obtain better computation speed with improved sensitivity, specificity and accuracy.

References

  1. Duraipandian, M, Vinothkanna,R (2019). Cloud Based Internet of Things for Smart Connected Objects. Journal of ISMAC, 1(02), 111-119.
  2. Christoforou,E, Fernández Anta,A., Georgiou, C., Mosteiro, M., and Sánchez, A. 2013. Crowd Computing as a Cooperation Problem: An Evolutionary Approach. Journal of Statistical Physics 151(3), 654-672.
  3. Qingchen Zhang, Laurence Tianruo Yang, Zhikui Chen, Peng Li, Fanyu Bu (2019). An Adaptive Dropout Deep Computation Model for Industrial IoT Big Data Learning with Crowdsourcing to Cloud Computing. IEEE Transactions on Industrial Informatics, 15(4), 2330-2337.
  4. Fei Chen, Cong Zhang, Feng Wang, Jiangchuan Liu, Xiaofeng Wang, Yuan Liu (2015). Cloud-Assisted Live Streaming for Crowdsourced Multimedia Content. IEEE Transactions on Multimedia, 17(9), 1471-1483
  5. Chongwu Dong, Yin Jia, Hua Peng, Xiaoxing Yang, Wushao Wen (2018). A Novel Distribution Service Policy for Crowdsourced Live Streaming in Cloud Platform. IEEE Transactions on Network and Service Management, 15(2), 679-692.
  6. Yuanhuan Zheng, Di Wu, Yihao Ke, Can Yang, Min Chen, Guoqing Zhang (2017). Online Cloud Transcoding and Distribution for Crowdsourced Live Game Video Streaming. IEEE Transactions on Circuits and Systems for Video Technology, 27(8),1777-1789.
  7. Sabita Maharjan, Yan Zhang, Stein Gjessing (2016). Optimal Incentive Design for Cloud-Enabled Multimedia Crowdsourcing. IEEE Transactions on Multimedia, 18(12), 2470-2481.
  8. Dejun Yang, Guoliang Xue, Xi Fang, Jian Tang (2016). Incentive Mechanisms for Crowdsensing: Crowdsourcing With Smartphones. IEEE/ACM Transactions on Networking, 24(3), 1732-1744.
  9. Yanru Zhang, Yunan Gu, Miao Pan, Nguyen H. Tran, Zaher Dawy, Zhu Han (2018). Multi-Dimensional Incentive Mechanism in Mobile Crowdsourcing with Moral Hazard. IEEE Transactions on Mobile Computing, 17(3), 604-616.
  10. Kyuwoong Hwang, Soo-Young Lee (2012). Environmental audio scene and activity recognition through mobile-based crowdsourcing. IEEE Transactions on Consumer Electronics, 58(2), 700-705.
  11. Gaoqiang Zhuo, Qi Jia, Linke Guo, Ming Li, Pan Li (2017). Privacy-Preserving Verifiable Set Operation in Big Data for Cloud-Assisted Mobile Crowdsourcing. IEEE Internet of Things Journal, 4(2), 572-582.
  12. Arijit Karati, SK Hafizul Islam, G. P. Biswas, Md Zakirul Alam Bhuiyan, Pandi Vijayakumar, Marimuthu Karuppiah (2018). Provably Secure Identity-Based Signcryption Scheme for Crowdsourced Industrial Internet of Things Environments. IEEE Internet of Things Journal, 5(4), 2904-2914.
  13. Suma, V. (2019). Security and Privacy Mechanism Using Blockchain. Journal of Ubiquitous Computing and Communication Technologies (UCCT), 1(01), 45-54.
  14. Qingchen Zhang, Laurence T. Yang, Zhikui Chen, Peng Li, M. Jamal Deen (2018). Privacy-Preserving Double-Projection Deep Computation Model With Crowdsourcing on Cloud for Big Data Feature Learning. IEEE Internet of Things Journal, 5(4), 2896-2903.