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Article
Publication date: 29 October 2020

Mu Shengdong, Wang Fengyu, Xiong Zhengxian, Zhuang Xiao and Zhang Lunfeng

With the advent of the web computing era, the transmission mode of the Internet of Everything has caused an explosion in data volume, which has brought severe challenges to…

Abstract

Purpose

With the advent of the web computing era, the transmission mode of the Internet of Everything has caused an explosion in data volume, which has brought severe challenges to traditional routing protocols. The limitations of the existing routing protocols under the condition of rapid data growth are elaborated, and the routing problem is remodeled as a Markov decision process. this paper aims to solve the problem of high blocking probability due to the increase in data volume by combining deep reinforcement learning. Finally, the correctness of the proposed algorithm in this paper is verified by simulation.

Design/methodology/approach

The limitations of the existing routing protocols under the condition of rapid data growth are elaborated and the routing problem is remodeled as a Markov decision process. Based on this, a deep reinforcement learning method is used to select the next-hop router for each data transmission task, thereby minimizing the length of the data transmission path while avoiding data congestion.

Findings

Simulation results show that the proposed method can significantly reduce the probability of data congestion and increase network throughput.

Originality/value

This paper proposes an intelligent routing algorithm for the network congestion caused by the explosive growth of data volume in the future of the big data era. With the help of deep reinforcement learning, it is possible to dynamically select the transmission jump router according to the current network state, thereby reducing the probability of congestion and improving network throughput.

Details

International Journal of Web Information Systems, vol. 16 no. 5
Type: Research Article
ISSN: 1744-0084

Keywords

Article
Publication date: 2 April 2019

Fengyu Bao, Chuan Chen, Albert P.C. Chan, Igor Martek and Asheem Shrestha

Public–private partnerships (PPPs) have emerged in developing countries, such as China, as a ubiquitous means by which government procures needed infrastructure. In this regard…

Abstract

Purpose

Public–private partnerships (PPPs) have emerged in developing countries, such as China, as a ubiquitous means by which government procures needed infrastructure. In this regard, they have been much studied. However, due to their long concession period, running into decades, few have run their full course into the transfer phase (TP) in which the PPP concession reverts from the private entity back to the public. In China, this is about to change as many PPPs approach their TP. Hence, the purpose of this paper is to comprehensively investigate the TP of PPPs in China.

Design/methodology/approach

A three-part methodology was undertaken to achieve the research purpose. Extensive literature review was first conducted to analyze the status quo of the transfer management regime in China, followed by the identification of critical challenges and the exploration of solutions via studying the TP of the Chengdu No. 6 Water Plant B Project – the first PPP in China’s water sector to reach the TP. Research procedures and outcomes were hierarchically visualized by using Integration DEFinition language 0 (IDEF0) method.

Findings

The current transfer management regime of PPPs in China’s water sector is deficient in many aspects. Based on the insight into the practice, a generic transfer process model with hierarchical structure process and sub-processes serving as a dynamic framework transfer model with self-evolving nature is developed to facilitate the successful transfer of the PPP utility.

Originality/value

To the authors’ best knowledge, this is the first attempt to systematically probe the TP of PPPs. Hopefully, the findings of this paper are to instruct government and PPP practitioners alike on mechanisms for smoothing the TP of further PPP projects ending their concession period.

Details

Engineering, Construction and Architectural Management, vol. 26 no. 7
Type: Research Article
ISSN: 0969-9988

Keywords

Article
Publication date: 30 May 2019

Fengyu Xu and Quansheng Jiang

Field robots can surmount or avoid some obstacles when operating on rough ground. However, cable-climbing robots can only surmount obstacles because their moving path is…

Abstract

Purpose

Field robots can surmount or avoid some obstacles when operating on rough ground. However, cable-climbing robots can only surmount obstacles because their moving path is completely restricted along the cables. This paper aims to analyse the dynamic obstacle-surmounting models for the driving and driven wheels of the climbing mechanism, and design a mechanical structure for a bilateral-wheeled cable-climbing robot to improve the obstacle crossing capability.

Design/methodology/approach

A mechanical structure of the bilateral-wheeled cable-climbing robot is designed in this paper. Then, the kinematic and dynamic obstacle-surmounting of the driven and driving wheels are investigated through static-dynamic analysis and Lagrangian mechanical analysis, respectively. The climbing and obstacle-surmounting experiments are carried out to improve the obstacle crossing capability. The required motion curve, speed and driving moment of the robot during obstacle-surmounting are generated from the experiments results.

Findings

The presented method offers a solution for dynamic obstacle-surmounting analysis of a bilateral-wheeled cable-climbing robot. The simulation, laboratory testing and field experimental results prove that the climbing capability of the robot is near-constant on cables with diameters between 60 and 205 mm.

Originality/value

The dynamic analysis method presented in this paper is found to be applicable to rod structures with large obstacles and improved the stability of the robot at high altitude. Simulations and experiments are also conducted for performance evaluation.

Details

Industrial Robot: the international journal of robotics research and application, vol. 46 no. 3
Type: Research Article
ISSN: 0143-991X

Keywords

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