An Integration Framework of Cloud Computing with Wireless Sensor Networks
Wireless sensor networks (WSN) is a key technology extensively applied in many fields, such as transportation, health-care and environment monitoring. Despite rapid development, the exponentially increasing data emanating from WSN is not efficiently stored and used. Besides, the data from multiple different types and locations of WSN needs to be well analyzed, fused and supplied to various types of clients, such as PC, workstation and smart phone. The emerging cloud computing technology provides scalable data process and storage power and some types of connectable services, which can helpfully utilize sensor data from WSN. In this paper, we propose an integration framework of cloud computing with WSN, in which sensor data is transmitted from WSN to cloud, and processed and stored in cloud, then mined and analyzed so as to be supplied to various clients. By applying virtualization and cloud storage technology, and Infrastructure as a Service (IaaS) and Software as a Service (SaaS) of cloud service model, the framework can fully process and store mass sensor data from multiple types of WSN. Besides, it efficiently mines and analyzes sensor data, based on which the data applications are well supplied to various types of clients in form of services.
KeywordsWireless Sensor Networks Cloud computing Virtualization Cloud storage As a Service
This research work is supported by National Basic Research Program of China under Grant No. 2011CB302601, and National High-Tech R&D Program of China under Grant No. 2011AA01A202.
- 2.Sharif, A., Potdar, V., Chang, E.: Wireless multimedia sensor networks: A survey. In: 7th IEEE International Conference on Industrial Informatics, pp. 606–613 (2009)Google Scholar
- 4.Liu, R., Wassell, I.J.: Opportunities and challenges of wireless sensor networks using cloud services. In: ACM Workshop on Internet of things and service platforms (2011)Google Scholar
- 5.Buyya, R., Chee, S.Y.: Cloud computing and emerging IT platforms, vision, hype, and reality for delivering computing as the 5th utility. F. G. C. S. 25, 599–611 (2009)Google Scholar
- 6.Mell, P., Grance, T.: The NIST definition of cloud computing. Technical report, National Institute of Standards and Technology (2011)Google Scholar
- 7.Gavrilovska, A., Kumar, S., Raj, K., Gupta,V., Nathuji, R., Niranjan, A., Saraiya, P.: High-performance hypervisor architectures: Virtualization in HPC systems. In: 1st Workshop on System-level Virtualization for High-performance Computing (2007)Google Scholar
- 8.Quinton, C., Rouvoy, R., Duchien, L.: Leveraging feature models to configure virtual appliances. In: Proceedings of the 2nd International Workshop on Cloud Computing Platforms (2012)Google Scholar
- 9.Basal, A.M., Steenkamp, A.L.: A saas-based approach in an E-learning system. Iran J. Inf Sci. Manage. 1, 27–40 (Special issue) (2010)Google Scholar
- 10.Marc, F., Heiko, N., Georg, C.: Cloud computing for the masses. In: Proceedings of the ACM Conference on Emerging Networking Experiments and Technologies, pp. 31–36 (2009) Google Scholar
- 12.Xu, P., Zheng, W., Wu, Y., Huang, X., Xu, C.: Enabling cloud storage to support traditional application. In: Proceedings of 5th Annual China Grid Conference, pp. 167–172 (2010)Google Scholar
- 13.You, P., Peng, Y., Liu, W., Xue, S.: Security issues and solutions in cloud computing. In: Proceedings of IEEE ICDCS Workshops, pp. 573–577 (2012)Google Scholar