Abstract
With the development of Internet of Things technology, embedded real-time operating system has been more and more widely used. The embedded real-time operating system has higher requirements on the real-time, fragmentation rate and reliability of dynamic memory allocation. Therefore, dynamic memory allocation has become an important research content of embedded real-time operating system. Aiming at the shortage of μC/OS-II memory management mechanism, an improved memory management algorithm is proposed. By predicting transient objects, allocating them on one side of the heap memory, and then allocating the remaining objects on the other side of the heap memory, the algorithm uses enhanced multilevel separation mechanisms and look-up tables and hierarchical bitmaps to make efficient use of memory occupy. The comparison experiment of μC/OS-II platform shows that the improved dynamic memory allocation algorithm can better improve the speed and utilization of memory allocation. The dynamic memory algorithm has better real-time performance and can effectively improve the memory management of embedded real-time operating system performance.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Diwase, D., Shah, S., Diwase, T., et al.: Survey report on memory allocation strategies for real time operating system in context with embedded devices. Int. J. Eng. Res. Appl. (IJERA) 2, 1151–1156 (2012)
Shen, F.-Y., Zhang, Y., Lin, Y.: Design and implementation of dynamic memory management algorithm in embedded real-time system. Comput. Sci. Modern. 7, 103–107 (2015)
Jabeen, Q., Khan, F., Hayat, M.N., et al.: A survey: embedded systems supporting by different operating systems. arXiv preprint arXiv:1610.07899(2016)
Yan, J., Xuewen, Z., Sun, P.: Low memory process management algorithm based on statistical analysis and prediction. Comput. Eng. Des. 35(1), 107–111 (2014)
Mancuso, R., Dudko, R., Betti, E., et al.: Real-time cache management framework for multi-core architectures. In: 2013 IEEE 19th Real-Time and Embedded Technology and Applications Symposium (RTAS), pp. 45–54. IEEE (2013)
Patil, N.V., Irabashetti, P.S.: Dynamic memory allocation: role in memory management (2014)
Cheng, X., Gong, Y., Anming, X.: Embedded memory prediction and allocation algorithm based on markov chain. Comput. Eng. Des. 34(8), 2727–2731 (2013)
Xiao, L., Kejiang, L.: Analysis and comparison of dynamic memory management mechanism of μC/OS and FREERTOS. Softw. Eng. 19(5), 21–22 (2016)
Wang, C., Wong, W.F.: Observational wear leveling: an efficient algorithm for flash memory management. In: 2012 49th ACM/EDAC/IEEE Design Automation Conference (DAC), pp. 235–242. IEEE (2012)
Wang, X., Qiu, X., Mu., F., et al.: Research on a new dynamic memory management mechanism of embedded system. Microelectron. Comput. 34(8), 66-6 (2017)
Acknowledgment
As the research of the thesis is sponsored by National Natural Science Foundation of China (No: 61662017, No: 61262075), Key R & D projects of Guangxi Science and Technology Program (AB17195042), Guangxi Natural Science Foundation (No: 2017GXNSFAA198223), Major scientific research project of Guangxi higher education (No: 201201ZD012), Scientific and Technological Research Program for Guangxi Educational Commission grants (#2013YB113), Guilin Science and Technology Project Fund (No: 2016010408) and Guangxi Graduate Innovation Project (No: SS201607), we would like to extend our sincere gratitude to them.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Cheng, X., Guan, Y., Zhang, Y. (2018). Design and Implementation of Dynamic Memory Allocation Algorithm in Embedded Real-Time System. In: Zhou, Q., Gan, Y., Jing, W., Song, X., Wang, Y., Lu, Z. (eds) Data Science. ICPCSEE 2018. Communications in Computer and Information Science, vol 901. Springer, Singapore. https://doi.org/10.1007/978-981-13-2203-7_43
Download citation
DOI: https://doi.org/10.1007/978-981-13-2203-7_43
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-2202-0
Online ISBN: 978-981-13-2203-7
eBook Packages: Computer ScienceComputer Science (R0)