Optimization strategy of mobile data transmission based on optimal crowd feedback
© The Author(s). 2016
Received: 18 August 2016
Accepted: 11 November 2016
Published: 9 December 2016
In order to eliminate the factors that restrict the performance of wireless network data transmission, we proposed the optimal control mechanism of wireless network data transmission. The proposed mechanism solves the intelligence problem of the feedback loop, the mobility of relay nodes, and the feedback of the receiving end. On the one hand, to eliminate the external interference factors, we established an optimal feedback loop control system between the sender and the receiver. On the other hand, in the time linear region, the crowd feedback module is added to the optimal feedback closed-loop control system based on the linear weight. On the basis of the above schemes, we proposed an adaptive optimization model of mobile data transmission. The experiments compared the proposed optimal crowd feedback optimal control scheme with the optimization strategy of the data transmission. From the results of system efficiency and system throughput performance, the proposed optimal crowd feedback optimal control scheme has an obvious advantage.
KeywordsControl optimization Mobility management Wireless data transmission Crowd feedback
The diversity of  and data services in wireless transmission environment  makes the quality of wireless transmission data decrease. Wireless transmission system performance is not stable. These problems seriously affect the quality of the user experience . These issues restrict the way  and operating costs of mobile service carriers. In order to solve these problems, the academic and industrial circles have studied the wireless communication protocol [5–8], the wireless data packet [9, 10], the transmission performance control optimization [11, 12], and so on.
Jin M proposed a remote wireless transparent transmission protocol for meeting the requirements of the Internet of Things-based intelligent remote monitoring system for construction vehicles on the real time . The distance-sensitive wireless communication protocol was proposed in an article  to hearing protectors equipped with in-ear microphones. Chaturvedi A et al. studied the secure wireless communication protocol with the Diffie-Hellman key exchange scheme . The link performance of intra-satellite networking was analyzed and discussed  for receiving sensitivity in each model.
The cellular/infostation integrated network was considered by the authors of an article  that supports on-demand data service delivery. The novel approaches was proposed in an article  that are based on data envelopment analysis (DEA) to further optimize energy consumption in wireless multicast networks.
The random wireless sensor networks were considered, where nodes are distributed randomly and form clusters to transmit the packets to relay clusters using cooperative multi-input-multi-output technique . A simple and effective method is demonstrated to overcome the frequency splitting for an optimal efficiency .
The rest of the paper is organized as follows. Section 2 gives the optimal feedback model. Section 3 discussed the optimization strategy of mobile data transmission with crowd feedback. The algorithm analysis results have been in Section 4. Finally, the Section 5 concludes this paper.
2 Optimal feedback model
where x said emission signal intensity. t denotes the data transmission time. H (t) said linear vector data transmission. Function F (t) said linear data transmission control vector. s is the linear transmission data sequence. d (s) denotes the size of the data. y (x) indicates the transmitting power signal. y (t) represents the linear time on the total transmit power.
3 Optimization strategy of mobile data transmission with crowd feedback
According to the different time domain linear weighting w L, the solution is divided into two kinds. According to the formula (2), it can be known that the optimal system efficiency can be obtained when the w L is greater than 0.
4 Algorithm evaluation results
Hard disk space size
Number of concurrent session
Based on the study of the decline reasons of the data transmission performance in the wireless network environment and the influencing factors of the feedback mechanism, we put forward the optimal crowd control of the wireless network data transmission. The innovation of the scheme has also a crowd feedback mechanism, data encapsulation, mobile management, and sensory feedback. Firstly, a closed-loop control system is formed between the transmitter and the receiver, which is affected by the interference of the wireless data transmission. The aim of the system is to eliminate the key factors of these factors. Secondly, according to the time domain linear weight, crowd feedback module is designed to the optimal feedback closed-loop control system. Finally, on the basis of the above researches, we proposed an adaptive optimization model of mobile data transmission. Based on the experimental results, we found that the system efficiency and the system throughput rate of the proposed algorithm are higher and the system throughput is higher and smoother.
The author declares that he/she has no competing interests.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
- Cerpa A, Elson J, Estrin D, et al. Habitat monitoring: application driver for wireless communications technology[J]. Acm Sigcomm Workshop on Data Communications in Latin America & the Caribbean, 2010;31(2):20–41.Google Scholar
- Chamotra S, Sehgal R K, Kamal R, et al. Data diversity of a distributed honey net based malware collection system[C]// Emerging Trends in Networks and Computer Communications (ETNCC), 2011 International Conference on. IEEE, 2011:125–129.Google Scholar
- DM Lestari, D Hardianto, HA Nizar, Analysis of user experience quality on responsive web design from its informative perspective[J]. Int. J. Softw. Eng. Its Appl. 8(5), 53–62 (2014)Google Scholar
- L Deng, Q Zeng, W Zhou et al., The effect of train formation length and service frequency on the determination of train schedules[J]. Proceedings of the Institution of Mechanical Engineers Part F. J. Rail Rapid Transit. 228(4), 378–388 (2013)View ArticleGoogle Scholar
- M Jin, X Zhou, E Luo et al., Industrial-QoS-oriented remote wireless communication protocol for the internet of construction vehicles[J]. IEEE Trans. Ind. Electron. 62(11), 7103–7113 (2015)View ArticleGoogle Scholar
- REB Serhal, TH Falk, J Voix, Integration of a distance sensitive wireless communication protocol to hearing protectors equipped with in-ear microphones.[J]. J. Acoust. Soc. Am. 133(5), 3273 (2013)View ArticleGoogle Scholar
- A Chaturvedi, N Srivastava, V Shukla, A secure wireless communication protocol using Diffie-Hellman key exchange[J]. Int. J. Comput. Appl. 126, 33–36 (2015)Google Scholar
- Q Qi, P Li, XU Guo-Dong, Design and simulation of the wireless communication protocol applied to small satellite[J]. LEMCS-14 38(1), 71–76 (2014)Google Scholar
- T Chen, H Shan, X Wang, Optimal scheduling for wireless on-demand data packet delivery to high-speed trains[J]. IEEE Trans. Veh. Technol. 64(9), 4101–4112 (2015)View ArticleGoogle Scholar
- AA Ajibesin, N Ventura, A Murgu et al., Data envelopment analysis with slacks model for energy efficient multicast over coded packet wireless networks[J]. Iet Sci. Meas. Technol. 8(6), 408–419 (2014)View ArticleGoogle Scholar
- B Li, H Li, W Wang, Q Yin, H Liu, Performance analysis and optimization for energy-efficient cooperative transmission in random wireless sensor network[J]. IEEE Trans. Wirel. Commun. 12(9), 4647–4657 (2013)View ArticleGoogle Scholar
- J Han, YD Kim, NH Myung, Efficient performance optimisation of wireless power transmission using genetic algorithm[J]. Electron. Lett. 50(6), 462–464 (2014)View ArticleGoogle Scholar