The Development of IoT Compression Technique To Cloud
Kartika Sari(1*), Mardhani Riasetiawan(2)
(1) Master Program of Computer Science, FMIPA UGM, Yogyakarta
(2) Department of Computer Science and Electronics, FMIPA UGM, Yogyakarta
(*) Corresponding Author
Abstract
The main problem of data transmission is how to reduce the length of data packet delivery, so it can reduce the time of sending data. One method that can be used to reduce the data size is by compressing the data size. Data compression is a technique for compressing data to get the data with smaller size than the original size so that it can shorten the data exchange time
This study aims to develop the data compression techniques by modifying and combining the coding and modelling techniques based on the RAKE algorithm. This study testing experiments use 4 different methods in 5 different time-periods to determine the value of the compression, decompression efficiency parameters, and the data transmission time parameters.
The result of this study is the data coding technique that using decimal to binary converter data and the modeling technique by calculating the residue from the sensor value will produce data in small sizes and get a compression efficiency value of 45%. For coding techniques using ASCII and modeling techniques with XOR operations will produce bigger size data and the compression efficiency value of 71%. In testing data decompression, the decompression efficiency value of 100%, there is no data loss.
Keywords
Full Text:
PDFReferences
[1] Z. Lin & Zhang, L., 2016, Data Synchronization Algorithm for loT Gateway and Platform, 2016 2nd IEEE International Conference on Computer and Communications (ICCC), Chengdu, 2016, pp. 114-119
[2] D. Salomon & Motta, G., 2010, Handbook of data compression.
[3] K. Sayood, 2012, Lossless Image Compression, In, Introduction to Data Compression (Fourth Edition).
[4] G. Campobello, Segreto, A., Zanafi, S. & Serrano, S., 2017, RAKE : a Simple and Efficient Lossless Compression Algorithm for the Internet of Things, 7, 2650–2654.
[5] M. Vecchio, Giaffreda, R. & Marcelloni, F., 2014, Adaptive lossless entropy compressors for tiny iot devices, IEEE Transactions on Wireless Communications, 13, 2, 1088–1100.
[6] A. Pinho, J., 2002, An online preprocessing technique for improving the lossless compression of images with sparse histograms, IEEE Signal Processing Letters.
[7] Cloud & Grid Technology Research Group, 2017, G-Connect Project, https://cloud.wg.ugm.ac.id/newgamabox, accessed on September 2nd 2017.
[8] A. Desai, Nagegowda, K.S. & Ninikrishna, T., 2016, A framework for integrating IoT and SDN using proposed OF-enabled management device, Proceedings of IEEE International Conference on Circuit, Power and Computing Technologies, ICCPCT 2016, 1–4.
[9] M. Aazam, Khan, I., Alsaffar, A.A. & Huh, E.N., 2014, Cloud of Things: Integrating Internet of Things and cloud computing and the issues involved, Proceedings of 2014 11th International Bhurban Conference on Applied Sciences and Technology, IBCAST 2014, 414–419.
[10] N. Malhotra & Chaudhary, A., 2014, Implementation of Database Synchronization Technique between Client and Server. International Journal of Engineering Science and Innovative Technology Volume 3, Issue 4, July 2014.
[11] A. Kumar, Nanjangud, C., Narendra & Umesh, B., 2016, Uploading And Replicating Internet Of Things (IoT) Data On Distributed Cloud storage", 2016 IEEE 9th International Conference On Cloud Computing, Vol. 00, No. , Pp. 670-677, 2016, Doi:10.1109/CLOUD.2016.0094
[12] M. Sharma, 2010, Compression Using Huffman Coding, IJCSNS International Journal of Computer Science and Network Security.
[13] F. Hadiatna, Hindersah, H., Yolanda, D. & Triawan, M.A., 2017, Design and implementation of data logger using lossless data compression method for the Internet of Things, Proceedings of the 2016 6th International Conference on System Engineering and Technology, ICSET 2016, 105–108.
DOI: https://doi.org/10.22146/ijccs.47270
Article Metrics
Abstract views : 2730 | views : 2201Refbacks
- There are currently no refbacks.
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
View My Stats1