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Application of lean six sigma methodology in software continuous integration

Key Engineering Materials 2016年第1期693卷 1893-1898页

作者： Xu, Xueqi Huang, Chao Lu, Hao School of Management Hangzhou Dianzi University Hangzhou310018 China Nokia Solutions and Networks System Technology Co. Ltd Hangzhou310053 China

Lean Six Sigma (LSS) is an effective methodology that aims to maximize shareholder value by improving quality, efficiency, customer satisfaction and costs. Continuous integration is the software engineering practice of rapid and automated development and testing. A case study presented in this paper demonstrates how LSS tools help software R&D teams to improve product quality and reduce development cost. The define, measure, analyze, improve and control (DMAIC) methodology is applied to develop an action plan to achieve continuous integration at an anonymous software R&D organization's LSS Green Belt project. The LSS implementation has had a significant impact on the financial performance of the organization. It is showed that the package continuous integration (PCI) success ratio (3 months average) increased from 27% to 74%, meanwhile an operational saving of approximately 56.87K Euro was reported from this project. Finally, some key success factors that are critical to the implementation of an effective Green Belt program are examined, and managerial implications are provided. © 2016 Trans Tech Publications, Switzerland.

关键词： Customer satisfaction

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A BEARER SPLITTING METHOD, USER EQUIPMENT AND BASE STATION

A BEARER SPLITTING METHOD, USER EQUIPMENT AND BASE STATION

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作者： LIU, Yang DU, Lei

标准号: WO2019071528(A1)

The present invention provides a bearer splitting method performed by user equipment and base station, and the corresponding user equipment and base station. A bearer splitting method performed by user equipment, comprising: carrying out measurement for one or more second base stations during the user equipment connecting to a first base station prior to network configuration;sending measurement results of at least part of the second base stations of the one or more second base stations to the first base station, such that the first base station selecting a target base station from the one or more second base stations according to the measurement results, wherein the target base station is used to control split bearer from the target and first base station to the user equipment.

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METHOD AND APPARATUS FOR LOAD BALANCING

METHOD AND APPARATUS FOR LOAD BALANCING

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作者： LIU, Yang DU, Lei

标准号: WO2019061246(A1)

A method and apparatus for load balancing. The method executed by a master base station for load balancing comprising: determining a load balancing group, wherein the load balancing group includes a plurality of secondary base stations;and sending a grouping information about the load balancing group to each secondary base station of the load balancing group. The method executed by a secondary base station of a load balancing group for load balancing comprising: receiving a grouping information about the load balancing group from a master base station;exchanging the load information with other secondary base stations of the load balancing group;selecting a target secondary base station from the other secondary base stations according to the load information of other secondary base stations;and forwarding at least a portion of load of the secondary base station to the target secondary base station.

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A CONNECTION SETUP METHOD, USER EQUIPMENT, COMMON CENTRAL CONTROL NODE AND COMMUNICATION system

A CONNECTION SETUP METHOD, USER EQUIPMENT, COMMON CENTRAL CO...

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作者： DU, Lei LIU, Yang VIERING, Ingo ZANIER, Paolo

标准号: WO2018119664(A1)

The present invention provides a connection setup method, the corresponding user equipment, common central control node and communication system. A connection setup method performed by a user device, comprising: acquiring information transmitted by a plurality of cells;determining a plurality of candidate cells according to the information transmitted by the plurality of cells, sending a common connection setup request for the plurality of candidate cells to a common central control node, the common central control node corresponding to each of the plurality of candidate cells;receiving a common connection setup message for a plurality of connecting cells transmitted by the common central control node, the plurality of connecting cells being determined from the plurality of candidate cells by the common central control node, so that the user equipment establishes multiple radio connections through each of the plurality of connecting cells.

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Backhaul-aware optimal access selection for traffic offloading in small-cell networks

Backhaul-aware optimal access selection for traffic offloadi...

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2017 IEEE International Conference on Communications Workshops, ICC Workshops 2017

作者： Chai, Haohan Qian, Liping Wu, Yuan Zhou, Haibo Lu, Weidang Jianchao, Zheng Yu, Changsheng College of Information Engineering Zhejiang University of Technology Hangzhou China Department of Electrical and Computer Engineering University of Waterloo WaterlooON Canada Institute of Communications Engineering PLA University of Science and Technology Nanjing China Nokia Solutions and Networks System Technology Co. Ltd Hangzhou China

ISBN: (纸本)9781509015252

The limited backhaul capacity has been considered as an important issue that influences the performance of traffic offloading in small-cell networks. We thus investigate how mobile users (MUs) efficiently offload traffic to different small cells with the new paradigm of dual-connectivity, subject to different backhaul capacities of small cells. Specifically, we formulate an optimization problem that jointly optimizes the MUs' access-selections, traffic scheduling, and transmit-power allocations, with the objective of minimizing all MUs' mobile data cost. To tackle with the difficulty due to the mixed binary nonconvex optimization problem, we decompose the joint optimization problem into a subproblem that optimizes the MUs' traffic scheduling and power allocations and a top problem that optimizes the MUs' access-selections. Based on our previous study [1], we can efficiently solve the subproblem by exploiting its hidden monotonicity. With the solution of the subproblem, we further propose two effective algorithms (namely, a simulated annealing based algorithm and a fast access-selection algorithm) to solve the top problem. The key idea of the fast access-selection algorithm is to exploit the information of limited backhaul capacities and properly remove the infeasible selection to reduce the search space. Numerical results validate the effectiveness of our proposed algorithms and the performance advantage of the proposed joint resource allocations for traffic offloading. © 2017 IEEE.

关键词： Simulated annealing

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Multi-Dilated Hierarchical Filter Based 3D U-Net for Multi-Modal Brain Tumor Segmentation

Multi-Dilated Hierarchical Filter Based 3D U-Net for Multi-M...

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Chinese Automation Congress (CAC)

作者： Shaocong Mo Xiaotian Jin Xin Jin College of Computer Science and Technology Zhejiang University Hangzhou China Nokia Solutions and Networks System Technology (Beijing) Co. Ltd. School of Management Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781665426480

Brain tumor segmentation is an essential task in the field of medical image analysis. Brain lesions (e.g. gliomas) have various shapes, sizes, and locations between different patients, making it challenging localizing and doing other tasks. For a single tumor, the essential contextual information may inhabit much larger regions than itself. Multi-scale feature representation can improve model generalization. However, existing U-Net models perform with layer-wise features. In this paper, a 3D multi-dilated hierarchical filter module is proposed based on hierarchical multi-scale strategy and multi-fiber strategy. The main points of our proposed module are multi hierarchical filter connection and multi-branch dilated convolutions. Besides, the proposed module is applied with a 3D U-Net. The results of experiments on the validation subset of BraTS2018 dataset show the efficacy of the proposed module.

关键词： Solid modeling Image segmentation Three-dimensional displays Uncertainty Shape Brain modeling Feature extraction

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Backhaul-Aware Optimal Access Selection for Traffic Offloading in Small-Cell networks

Backhaul-Aware Optimal Access Selection for Traffic Offloadi...

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IEEE International Conference on Communications Workshops

作者： Haohan Chai Liping Qian Yuan Wu Haibo Zhou Weidang Lu Jianchao Zheng Changsheng Yu College of Information Engineering Zhejiang University of Technology Department of Electrical and Computer Engineering University of Waterloo Institute of Communications Engineering PLA University of Science and Technology Nokia Solutions and Networks System Technology Co. Ltd

ISBN: (纸本)9781509015269

关键词： UNLOADING Muscae Mus Traffic return stroke power splitting optimal access Resource utilization selection algorithm algorithms

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Incremental Tensor Decomposition and BiGRU based Network Traffic Prediction for IIoT

Incremental Tensor Decomposition and BiGRU based Network Tra...

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IEEE International Conference on Communications in China (ICCC)

作者： Sifu Yan Na Li Hangguan Shan Shibo He Zhiguo Shi Qi Zhang Xianhua He College of Information Science and Electronic Engineering Zhejiang University Hangzhou China College of Control Science and Engineering Zhejiang University Hangzhou China Nokia Solutions and Networks System Technology (Beijing) Co. Ltd Hangzhou China

The Industrial Internet of Things (IIoT) has become one of the major platforms for deploying 5G networks and artificial intelligence technologies. For the large amount of network traffic generated by various heterogeneous services in factories, accurate traffic predictions can lead to lower costs and higher production efficiency. But, in industrial network scenarios, it is challenging to make an accurate traffic prediction, requiring efficient methods to exploit the spatial and temporal dependency features of the traffic and overcome the computation complexity brought about by large-scale traffic. To this end, in this paper we propose a traffic prediction algorithm named ITD-BiGRU, utilizing incremental tensor decomposition (ITD) and a bidirectional gate recurrent unit (BiGRU). Specifically, ITD extracts the spatial features of traffic with reduced computation complexity as compared with traditional tensor decomposition approaches. As ITD is designed to force two factor matrices within the total three keep unchanged in each ITD period, BiGRU predicts traffic change with only the input of the changed factor matrix, further reducing computation complexity. The effectiveness of the proposed algorithm is verified by conducting experiments on a real data set and it is shown that the proposed algorithm outperforms baseline algorithms.

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