Efficient Sensor-Cloud Communication using Data Classification and Compression. Department of Computer Science, Engineering, D. I. U., Rahman, M. T., Salan, M. S. A., Shuva, T. F., & Khan, R. T. International Journal of Information Technology and Computer Science, 9(6):9–17, June, 2017.
Efficient Sensor-Cloud Communication using Data Classification and Compression [link]Paper  doi  abstract   bibtex   1 download  
Wireless Sensor Network, a group of specialized sensors with a communication infrastructure for monitoring and controlling conditions at diverse locations, is a recent technology which is getting popularity day by day. Besides, cloud computing is a type of high-performance computing that uses a network of remote servers which simultaneously provides the service to store, manage and process data rather than a local server or personal computer. An architecture called sensor-cloud is also providing good services by combining the capabilities from both ends. In order to provide such services, a large volume of sensor network data needs to be transported to cloud gateway with a high amount of bandwidth and time requirement. In this paper, we have proposed an efficient sensor-cloud communication approach that minimizes the enormous bandwidth and time requirement by using statistical classification based on machine learning as well as compression using deflate algorithm with a minimal loss of information. Experimental results describe the overall efficiency of the proposed method over the traditional and related research.
@article{department_of_computer_science_and_engineering_daffodil_international_university_dhaka_1207_bangladesh_efficient_2017,
	title = {Efficient {Sensor}-{Cloud} {Communication} using {Data} {Classification} and {Compression}},
	volume = {9},
	issn = {20749007, 20749015},
	url = {http://www.mecs-press.org/ijitcs/ijitcs-v9-n6/v9n6-2.html},
	doi = {10.5815/ijitcs.2017.06.02},
	abstract = {Wireless Sensor Network, a group of specialized sensors with a communication infrastructure for monitoring and controlling conditions at diverse locations, is a recent technology which is getting popularity day by day. Besides, cloud computing is a type of high-performance computing that uses a network of remote servers which simultaneously provides the service to store, manage and process data rather than a local server or personal computer. An architecture called sensor-cloud is also providing good services by combining the capabilities from both ends. In order to provide such services, a large volume of sensor network data needs to be transported to cloud gateway with a high amount of bandwidth and time requirement. In this paper, we have proposed an efficient sensor-cloud communication approach that minimizes the enormous bandwidth and time requirement by using statistical classification based on machine learning as well as compression using deflate algorithm with a minimal loss of information. Experimental results describe the overall efficiency of the proposed method over the traditional and related research.},
	language = {en},
	number = {6},
	urldate = {2021-05-17},
	journal = {International Journal of Information Technology and Computer Science},
	author = {{Department of Computer Science and Engineering, Daffodil International University, Dhaka, 1207, Bangladesh} and Rahman, Md. Tanvir and Salan, Md. Sifat Ar and Shuva, Taslima Ferdaus and Khan, Risala Tasin},
	month = jun,
	year = {2017},
	pages = {9--17},
}

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