Memory Management Productivity in Big data Multimedia using Fireworks Algorithm
Resumen
The using of Big Data applications increased exponentially in the last few years. There are some knowledge extracted from huge volumes of data has been concerned by several enterprise. The working in Big Data faced chal- lenges and should do hard. As a result, various types of distributions and tech- nologies have been developed. This paper present a method for memory map- ping of image depend on some aggregation function and optimization these function using Fireworks algorithm to reduce the size of memory required in searching process. Image features extraction used in aggregation function and used later for optimization. Three types of feature extraction used image descriptors techniques. The proposed method provides abstract domain that replaced total data domain and the performance increase the system through- put and reduce cost.Citas
Field Cady, “In-Memory Big Data Management and Processing: A Survey”, IEEE TRANSACTIONS ON KNOWLEDGE AND DATA EN- GINEERING, VOL. 27, NO. 7, JULY 2015.
Yao Wang, LinBo Zhu, Jiwen Wang and Jianfeng Qiu, “The rise of “Big Data” on cloud computing: Review and open research issues”, Published February 3rd 2017 by Wiley.
Ibrahim Abaker Targio Hashem, Ibrar Yaqoob, Nor Badrul Anuar, Salimah Mokhtar, Abdullah Gani, and Samee Ullah Khan,” Big Data and Cloud Computing: Trends and Challenges”, this publication at: https:// www.researchgate.net/publication/264624667, 2014.
Samir A. El-Seoud, Hosam F. El-Sofany, Mohamed Abdelfattah and Reham Mohamed,” Big Data and Cloud Computing: Trends and Chal- lenges”, International Journal of Interactive Mobile Technologies (IJIM) · April 2017.
Dr.A.P.Mittal, Dr.Vanita Jain, and Tanuj Ahuja,“Google File System and Hadoop Distributed File System- An Analogy”, Internation- al Journal of Innovations & Advancement in Computer Science IJIACS ISSN 2347 – 8616 Volume 4, Special Issue March 2015.
Adriana Alexandru, Cristina Adriana Alexandru, Dora Coardos, and Eleonora Tudora,” Healthcare, Big Data and Cloud Computing”, WSEAS TRANSACTIONS on COMPUTER RESEARCH, 2017.
Nader Gemayel, “Analyzing Google File System and Hadoop Distributed File System”, Research Journal of Information Technology, 2016.
Atul Bansal, Ravinder Agarwal and R. K. Sharma “Statistical fea- ture extraction based iris recognition system”, Indian Academy of Scienc- es, Vol. 41, No. 5, May 2016.
Gaurav Kumar, and Pradeep Kumar Bhatia, “A Detailed Review of Feature Extraction in Image Processing Systems”, Fourth Internation- al Conference on Advanced Computing & Communication Technologies, 2014.
P. Mohanaiah, P. Sathyanarayana, and L. GuruKumar,” Image Texture Feature Extraction Using GLCM Approach”, International Journal of Scientific and Research Publications, Volume 3, Issue 5, May 2013. [11] Hongming Zhang and Debin Zhao, ”Spatial Histogram Features for Face Detection in Color Images”, Springer-Verlag Berlin Heidelberg 2004
Jae Young Choi, Konstantinos N. Plataniotis, and Yong Man Ro1, “Using Colour Local Binary Pattern Features for Face Recognition”, IEEE 17th International Conference on Image Processing September 26-29, Hong Kong, 2010.
Ke Ding, Shaoqiu Zheng, and Ying Tan, “A GPU-based Parallel Fireworks Algorithm for Optimization”, GECCO’13, July 6-10, 2013. [14] Shaoqiu Zheng, Andreas Janecek, Junzhi Li, and Ying Tan, “Dy- namic Search in Fireworks Algorithm” the National Natural Science Foun- dation of China under grants number 61375119, 61170057 and 60875080, 2014.
Xi-Guang Li, Shou-Fei Han, and Chang-Qing Gong, ”Analysis and Improvement of Fireworks Algorithm”, Academic Editors: Sergio Ra- jsbaum and George Karakostas, 2017
