Siya Xu

Beijing University of Posts and Telecommunications

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Shaoyong Guo

Beijing University of Posts and Telecommunications

Xuesong Qiu

Beijing University of Posts and Telecommunications

Peng Yu

Beijing University of Posts and Telecommunications

Feng Qi

Beijing University of Posts and Telecommunications

Zhili Wang

Tongji University

Luoming Meng

Beijing University of Posts and Telecommunications

Ao Xiong

State Key Laboratory of Networking and Switching Technology

Kang Sun

Zhejiang University

Lanlan Rui

Beijing University of Posts and Telecommunications

Boxian Liao

Beijing University of Posts and Telecommunications

Cooperative Institutions

Beijing University of Posts and Telecommunications

State Key Laboratory of Networking and Switching Technology

State Grid Corporation of China (China)

Chinese Academy of Sciences

Switch

Shanghai Electric (China)

Peking University

Tianjin University

University of Chinese Academy of Sciences

North China Electric Power University

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Federated Learning Meets Blockchain: State Channel-Based Distributed Data-Sharing Trust Supervision Mechanism

IEEE Internet of Things Journal (2021)

Fan Zhang Shaoyong Guo Xuesong Qiu Siya Xu Feng Qi

With the rapid development of the 5G and 6G technology, it has become an inevitable trend to share the cross-domain scattered data and enhance data value transmission. As a new data-sharing technology with intelligence and privacy computing, federated learning (FL) receives wide attention. It can realize data value delivery and data privacy protection at the same time, however, it lacks supervision in the application process, and the reliability of the calculation process and result transmission cannot be guaranteed. As a distributed ledger technology, blockchain has the trust property but lacks computing power. Therefore, we propose to extend the computing and supervision capabilities of blockchain with state channel, using state channel to create sandboxes and instantiate FL tasks in order to realize the trust supervision mechanism based on sandboxes. In this article, we establish an FL-based distributed data-sharing architecture and on the basis of the architecture we design a state channel-based distributed data-sharing trust supervision mechanism. Through theoretical analysis and experimental verification, the supervision mechanism we designed has an excellent performance in improving system security, resisting malicious attacks, and improving data model quality.

Data Sharing

10.1109/jiot.2021.3130116

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Citations (15)

天の生物学的技術の研究進展【JST・京大機械翻訳】

Jiyinzuxue Yuyingyong Shengwu Xue (2016)

Jing Tianrui Siya Xu Ni Yifei Yongjuan Zhang Guo Bin

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A Delay and Load-balancing based Hierarchical Route Planning Method for Transmission Line IoT Sensing and Monitoring applications

Cheng Ding Siya Xu Xingyu Chen Guiping Zhou Pei-Hao Zheng

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Citations (4)

A Packet Scheduling Method Based on Dynamic Adjustment of Service Priority for Electric Power Wireless Communication Network

Wireless Communications and Mobile Computing (2020)

Bo Hu Xin Liu Jinghong Zhao Siya Xu Zhenjiang Lei

With the development of the energy Internet, power communication services are heterogeneous, and different power communication services have different business priorities. The power communication services with different priorities have different requirements for network bandwidth and real-time performance. For traditional unified service, a scheduling method cannot meet these service requirements at the same time, and electric power communication network cannot guarantee the quality of service. Therefore, how to make full use of the time-varying characteristics of communication resources to meet the business needs of different priorities and achieve the goals of high resource utilization and transmission quality has become one of the urgent problems in the power communication network. For this reason, in order to adapt to the real-time congestion of the network, we have designed a packet scheduling method based on the dynamic adjustment of service priority, which dynamically adjusts the priority of the power service on the node; in addition, an evaluation method for the trust value of wireless forwarding nodes is introduced to improve the security of data transmission; and finally, we valuate the channel quality to establish a reasonable and efficient packet scheduling mechanism for services of different priorities. Simulation results show that this method improves the communication performance of high-priority services and improves the spectrum resource utilization of the entire system.

Packet forwarding

10.1155/2020/8869898

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Citations (4)

High-reliable WDM optical access network expanding by double fiber-tangent-ring topology

Qi Shao Ying Li Yu Shao Siya Xu

Based on double-fiber-tangent rings we propose a high-reliable wavelength-division-multiplexing optical access network. With the proposed architecture, data convergence can be realized and fiber link can be protected well. Because of fiber failure occurring no matter in primary ring and sub-ring, optical line terminal and remote nodes need to be switched automatically to protection mode. The RN designed as tangent point can realize wavelengths adding and dropping between PR and SR, and it also can expand the network conveniently and smoothly with more wavelengths in the network. What is more, the design of DFTR can enhance the survivability and self-healing ability of the network. The analysis and simulation demonstrate the proposed scheme has the strong survivability and it will be a good choice for large-scale access network in the future.

Survivability

Access network

10.1109/apnoms.2017.8094124

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Cloud–Edge Collaborative SFC Mapping for Industrial IoT Using Deep Reinforcement Learning

IEEE Transactions on Industrial Informatics (2021)

Siya Xu Yimin Li Shaoyong Guo Chenghao Lei Di Liu

The industrial Internet of Things (IIoT) and 5G have been served as the key elements to support the reliable and efficient operation of Industry 4.0. By integrating burgeoning network function virtualization (NFV) technology with cloud computing and mobile edge computing, an NFV-enabled cloud–edge collaborative IIoT architecture can efficiently provide flexible service for the massive IIoT traffic in the form of a service function chain (SFC). However, the efficient cloud–edge collaboration, the reasonable comprehensive resource consumption, and different quality of services are still key problems to be solved. Thus, to balance the quality of IIoT services, as well as computational and communicational resource consumption, a multiobjective SFC deployment model is designed to characterize the diverse service requirements and specific network environment for the IIoT. Then, a deep-

$Q$

-learning-based online SFC deployment algorithm is presented, which can efficiently learn the relationship between the SFC deployment scheme and its performance through the iterative training. Simulation results demonstrate that our proposed approach outperforms others in balancing the resource consumption, accepting more SFC requests, as well as providing differentiated services for delay-sensitive IIoT traffic and resource-intensive IIoT traffic.

10.1109/tii.2021.3113875

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Citations (33)

Risk-Aware Task Offloading and Resource Allocation in FiWi HetNets

2022 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB) (2022)

Shi Wang Siya Xu Shaoyong Guo Peng Yu Huiping Meng

Multimedia service, as one of the most important business in Internet of Things (IoT), poses a great challenge to network throughput and reliable service. MEC enhanced fiber-wireless heterogeneous network (FiWi HetNets) is considered to be a cost-effective scheme to improve the network coverage of IoT. However, due to the communication uncertainty caused by the change of channel conditions and the limited resources of the edge server, the offloaded task is at risk of failure caused by packet loss or overload of the edge server. Therefore, this paper proposes a risk-aware computing offload and resource allocation method to ensure the QoS of multimedia services. Firstly, we design a risk perception model based on conditional value at risk (CVaR) to measure the risk of 5G and WiFi wireless transmission modes, and formulate the optimization problem. Then, an A3C based optimization method for wireless access, computation offloading and resource allocation is proposed, to balance the end-to-end service delay. Simulation results verify the reliability and superiority of this method.

CVAR

10.1109/bmsb55706.2022.9828720

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Citations (1)

Deep reinforcement learning assisted edge-terminal collaborative offloading algorithm of blockchain computing tasks for energy Internet

International Journal of Electrical Power & Energy Systems (2021)

Siya Xu Boxian Liao Chao Yang Shaoyong Guo Bo Hu

Mobile Edge Computing

10.1016/j.ijepes.2021.107022

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AIEC-RSC: AI and Edge Collaboration Empowered Reliable Service Computing for High-Speed Mobile Businesses

IEEE Transactions on Services Computing (2023)

Siya Xu Jingye Chi Shi Wang Shaoyong Guo Xuesong Qiu

With the rapid development of high-speed assistant driving and smart inspections, the edge network is required to provide quick and reliable service to avoid large service response delays and frequent re-transmissions caused by interruption. However, the reasonable service component caching, efficient edge collaboration and reliable cross-domain computation offloading are still key problems to be solved. Thus, we consider an AI and mobile edge computing (MEC) integrated service framework, which is highly reliable for high-speed mobile businesses, and we divide the service process into component caching phase and task offloading phase. In the first phase, we novelly define the edge collaborative service domain (ECSD) which allows multiple edge nodes to collaboratively share resources from a global perspective and design a user behavior aware service component pre-caching method to increase resource utilization. In the second phase, based on the formed ECSDs and cached service components, we present an AI-empowered cross-domain computation task offloading mechanism including task partition and backup to enhance the reliable service capability of edge networks. Simulation results verify that the proposed mechanism can jointly optimize the allocation of caching, computation, and communication resources, while improving the service response speed and resource utility of edge networks.

Mobile Edge Computing

Edge device

Cloudlet

Computation offloading

Component (thermodynamics)

10.1109/tsc.2023.3340672

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Hierarchical Edge Cloud Enabling Network Slicing for 5G Optical Fronthaul

Journal of Optical Communications and Networking (2019)

Chuang Song Min Zhang Yueying Zhan Danshi Wang Luyao Guan

Network slicing has been proposed as an innovative concept to partition a physical network into different configurable slices, thereby allowing the network to meet the diverse requirements of expected services in the 5G era. Existing network-slicing schemes focus almost exclusively on the partitioning of the core network or the radio access network. However, to achieve greater flexibility and better resource utilization in service provisioning, the potential of network slicing in the 5G optical mobile fronthaul (MFH) network should be jointly exploited. To address this challenge, we propose a flexible hierarchical edge cloud architecture to enable 5G optical MFH network slicing. Additionally, a corresponding integrated network resource management scheme is proposed to support various quality-of-service (QoS) requirements and diverse resource requests of the network slices. Simulation results indicate that the proposed scheme is able to jointly allocate the bandwidth resources to network slices and realize cloud-computing offloading to meet various QoS requirements, and therefore reduce the fronthaul bandwidth burden.

Core network

Provisioning

Edge device

10.1364/jocn.11.000b60

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Citations (81)