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Average AoI Minimization With Directional Charging for Wireless-Powered Network Edge
Quan Chen;Song Guo;Wenchao Xu;Jing Li;Tuo Shi;Hong Gao;Zhipeng Cai
IEEE Transactions on Mobile Computing
Year: 2025 | Early Access Article |
Age of Information (AoI) has been proposed as a new performance metric to capture the freshness of data. At wireless-powered network edge, the source nodes first need to be charged ready for update transmissions, which means the system AoI is not only decided by the scheduling of update transmissions but also by the designing of charging plan. However, the existing works either only focused on the...Show More
Approximation Algorithm and Applications for Connected Submodular Function Maximization Problems
Ziming Wang;Jing Li;He Xue;Wenzheng Xu;Weifa Liang;Zichuan Xu;Jian Peng;Pan Zhou;Xiaohua Jia;Sajal K. Das
In this paper, we study a connected submodular function maximization problem, which arises from many applications including deploying UAV networks to serve users and placing sensors to cover Points of Interest (PoIs). Specifically, given a budget K, the problem is to find a subset S with K nodes from a graph G, so that a given submodular function f(S) on S is maximized and the induced subgraph...Show More
AoI-Aware Service Provisioning in Edge Computing for Digital Twin Network Slicing Requests
Jing Li;Song Guo;Weifa Liang;Jianping Wang;Quan Chen;Zicong Hong;Zichuan Xu;Wenzheng Xu;Bin Xiao
Digital twins are poised to enter our lives with Industry 4.0. The Digital Twin Network (DTN) paradigm is projected to deliver upon the promise of efficient collaboration among digital twins to enable complicated and systematic services across many domains, through depicting an overall picture of a group of physical objects. To achieve timely data processing of digital twins, Mobile Edge Computing...Show More
Approximation Algorithm for Connected Submodular Function Maximization Problems
Wenzheng Xu;He Xue;Jing Li;Weifa Liang;Zichuan Xu;Pan Zhou;Xiaohua Jia;Sajal K. Das
2024 IEEE 44th International Conference on Distributed Computing Systems (ICDCS)
Year: 2024 | Conference Paper |
In this paper, we study a connected submodular function maximization problem, which arises from many applications including deploying UAV networks to serve users and placing sensors to cover Points of Interest (PoIs). Specifically, given a budget $K$, the problem is to find a subset $S$ with $K$ nodes from a graph $G$ so that a given submodular function $f (S)$ on $S$ is maximized while the induce...Show More
AoI-Aware, Digital Twin-Empowered IoT Query Services in Mobile Edge Computing
Jing Li;Song Guo;Weifa Liang;Jie Wu;Quan Chen;Zichuan Xu;Wenzheng Xu;Jianping Wang
The Mobile Edge Computing (MEC) paradigm gives impetus to the vigorous advancement of the Internet of Things (IoT), through provisioning low-latency computing services at network edges. The emerging digital twin technique has been explosively growing in the IoT community, which bridges the gap between physical objects and their digital representations in an MEC network, enabling real-time monitori...Show More
Mobility-Aware Utility Maximization in Digital Twin-Enabled Serverless Edge Computing
Jing Li;Song Guo;Weifa Liang;Jianping Wang;Quan Chen;Wenchao Xu;Kang Wei;Xiaohua Jia
IEEE Transactions on Computers
Cited by: Papers (3)
Driven by data and models, the digital twin technique presents a new concept of optimizing system design, process monitoring, decision-making and more, through performing comprehensive virtual-reality interaction and continuous mapping. By introducing serverless computing to Mobile Edge Computing (MEC) environments, the emerging serverless edge computing paradigm facilitates the communication-effi...Show More
Maximizing Network Throughput in Heterogeneous UAV Networks
Shuyue Li;Jing Li;Chaocan Xiang;Wenzheng Xu;Jian Peng;Ziming Wang;Weifa Liang;Xinwei Yao;Xiaohua Jia;Sajal K Das
In this paper we study the deployment of an Unmanned Aerial Vehicle (UAV) network that consists of multiple UAVs to provide emergent communication service for people who are trapped in a disaster area, where each UAV is equipped with a base station that has limited computing capacity and power supply, and thus can only serve a limited number of people. Unlike most existing studies that focused on ...Show More
Peak AoI Minimization With Directional Charging for Data Collection at Wireless-Powered Network Edge
Quan Chen;Song Guo;Wenchao Xu;Jing Li;Kang Wei;Zhipeng Cai;Hong Gao
Age of Information (AoI) has emerged as a new metric to measure data freshness from the destination's perspective. To optimize the system AoI, most existing works focused on the point of scheduling of update transmissions. While at wireless-powered network edge, the source nodes can only transmit their updates after being charged ready, which means the system AoI is not only determined by the upda...Show More
Towards Real-Time Inference Offloading With Distributed Edge Computing: The Framework and Algorithms
Quan Chen;Song Guo;Kaijia Wang;Wenchao Xu;Jing Li;Zhipeng Cai;Hong Gao;Albert Y. Zomaya
By combining edge computing and parallel computing, distributed edge computing has emerged as a new paradigm to exploit the booming IoT devices at the edge. To accelerate computation at the edge, i.e., the inference tasks for DNN-driven applications, the parallelism of both computation and communication needs to be considered for distributed edge computing, and thus, the problem of Minimum Latency...Show More
Digital Twin-Enabled Service Provisioning in Edge Computing via Continual Learning
Jing Li;Song Guo;Weifa Liang;Jianping Wang;Quan Chen;Yue Zeng;Baoliu Ye;Xiaohua Jia
Propelled by recent advances in Mobile Edge Computing (MEC) and the Internet of Things (IoT), the digital twin technique has been envisioned as a de-facto driving force to bridge the virtual and physical worlds through creating digital portrayals of physical objects. In virtue of the flourishing of edge intelligence and abundant IoT data, data-driven modelling facilitates the implementation and ma...Show More
SafeDRL: Dynamic Microservice Provisioning With Reliability and Latency Guarantees in Edge Environments
Yue Zeng;Zhihao Qu;Song Guo;Baoliu Ye;Jie Zhang;Jing Li;Bin Tang
IEEE Transactions on Computers
Cited by: Papers (2)
As a key technology of 5G, network function virtualization enables each monolithic service to be divided into microservices, facilitating their deployment and management in edge environments. One of the most critical issues in 5G is how to support dynamically arriving mission-critical services with low-latency and high-reliability requirements in distributed edge environments. However, most existi...Show More
AoI-Aware User Service Satisfaction Enhancement in Digital Twin-Empowered Edge Computing
Jing Li;Song Guo;Weifa Liang;Jianping Wang;Quan Chen;Zichuan Xu;Wenzheng Xu
The emerging digital twin technique enhances the network management efficiency and provides comprehensive insights on network performance, through mapping physical objects to their digital twins. The user satisfaction on digital twin-enabled service relies on the freshness of digital twin data, which is measured by the Age of Information (AoI). Due to long service delays, the use of the remote clo...Show More
Peak AoI Minimization at Wireless-Powered Network Edge: From the Perspective of Both Charging and Transmitting
Age of Information, which emerged as a new metric to quantify the freshness of information, has attracted increasing interests recently. To optimize the system AoI, most existing works try to compute an efficient schedule from the point of data transmission. Unfortunately, at wireless-powered network edge, the charging schedule of the source nodes also needs to be decided besides data transmission...Show More
Digital Twin-Assisted, SFC-Enabled Service Provisioning in Mobile Edge Computing
Jing Li;Song Guo;Weifa Liang;Quan Chen;Zichuan Xu;Wenzheng Xu;Albert Y. Zomaya
Mobile Edge Computing (MEC) has been identified as a desirable computing paradigm that provides efficient and effective services for various applications, while meeting stringent service delay requirements. Orthogonal to the MEC computing paradigm, Network Function Virtualization (NFV) technology is another enabling technology that provides the network resource management with great flexibility an...Show More
Wait for Fresh Data? Digital Twin Empowered IoT Services in Edge Computing
Jing Li;Song Guo;Weifa Liang;Jie Wu;Quan Chen;Zichuan Xu;Wenzheng Xu;Jianping Wang
2023 IEEE 20th International Conference on Mobile Ad Hoc and Smart Systems (MASS)
Year: 2023 | Conference Paper |
Cited by: Papers (6)
The Mobile Edge Computing (MEC) paradigm gives impetus to the vigorous advancement of Internet of Things (IoT), through provisioning low-latency computing services at network edges. The emerging digital twin technique has grown in the community of IoT, and bridges the gap between physical objects and their digital representations in MEC, thereby enabling real-time data analysis, simulating the dyn...Show More
Coverage Maximization of Heterogeneous UAV Networks
Shuyue Li;Chaocan Xiang;Wenzheng Xu;Jian Peng;Zichuan Xu;Jing Li;Weifa Liang;Xiaohua Jia
2023 IEEE 43rd International Conference on Distributed Computing Systems (ICDCS)
Year: 2023 | Conference Paper |
Cited by: Papers (2)
In this paper we study the deployment of a UAV (unmanned aerial vehicle) network that consists of multiple UAVs to provide emergent communication services to people trapped in a disaster area, where each UAV is equipped with a base station that has limited computing capacity and power supply, and thus can only serve a limited number of users. Unlike most existing studies focusing on homogenous UAV...Show More
Latency-Optimal Pyramid-based Joint Communication and Computation Scheduling for Distributed Edge Computing
Quan Chen;Kaijia Wang;Song Guo;Tuo Shi;Jing Li;Zhipeng Cai;Albert Zomaya
IEEE INFOCOM 2023 - IEEE Conference on Computer Communications
Year: 2023 | Conference Paper |
Cited by: Papers (5)
By combing edge computing and parallel computing, distributed edge computing has emerged as a new paradigm to accelerate computation at the edge. Considering the parallelism of both computation and communication, the problem of Minimum Latency joint Communication and Computation Scheduling (MLCCS) is studied recently. However, existing works have rigid assumptions that the communication time of ea...Show More
Digital Twin-Enabled Service Satisfaction Enhancement in Edge Computing
IEEE INFOCOM 2023 - IEEE Conference on Computer Communications
Year: 2023 | Conference Paper |
Cited by: Papers (18)
The emerging digital twin technique enhances the network management efficiency and provides comprehensive insights, through mapping physical objects to their digital twins. The user satisfaction on digital twin-enabled query services relies on the freshness of digital twin data, which is measured by the Age of Information (AoI). Because the remote cloud faces challenges in providing data for users...Show More
Optimizing Average AoI with Directional Charging for Wireless-Powered Network Edge
Quan Chen;Song Guo;Wenchao Xu;Jing Li;Tuo Shi;Zhipeng Cai;Hong Gao
2023 IEEE/ACM 31st International Symposium on Quality of Service (IWQoS)
Year: 2023 | Conference Paper |
Cited by: Papers (2)
Age of Information, which emerged as a new performance metric to quantify the data freshness, has drawn increasing interests recently. At wireless-powered network edge, the source nodes can only transmit their updates after being charged ready, which means the system AoI is not only determined by the update transmission strategies, but also the charging strategies. However, the existing works eith...Show More
RuleDRL: Reliability-Aware SFC Provisioning With Bounded Approximations in Dynamic Environments
Yue Zeng;Zhihao Qu;Song Guo;Bin Tang;Baoliu Ye;Jing Li;Jie Zhang
As a key enabling technology for 5G, network function virtualization abstracts services into software-based service function chains (SFCs), facilitating mission-critical services with high-reliability requirements. However, it is challenging to cost-effectively provide reliable SFCs in dynamic environments due to delayed rewards caused by future SFC requests, limited infrastructure resources, and ...Show More
Energy-Aware, Device-to-Device Assisted Federated Learning in Edge Computing
Yuchen Li;Weifa Liang;Jing Li;Xiuzhen Cheng;Dongxiao Yu;Albert Y. Zomaya;Song Guo
The surging of deep learning brings new vigor and vitality to shape the prospect of intelligent Internet of Things (IoT), and the rise of edge intelligence enables provisioning real-time deep neural network (DNN) inference services for mobile users. To perform efficient and effective DNN model training in edge computing environments while preserving training data security and privacy of IoT device...Show More
Budget-Aware User Satisfaction Maximization on Service Provisioning in Mobile Edge Computing
Jing Li;Weifa Liang;Wenzheng Xu;Zichuan Xu;Xiaohua Jia;Albert Y. Zomaya;Song Guo
Mobile Edge Computing (MEC) promises to provide mobile users with delay-sensitive services at the edge of network, and each user service request usually is associated with a Service Function Chain (SFC) requirement that consists of Virtualized Network Functions (VNFs) in order. The satisfaction of a user on his requested service is heavily impacted by the service reliability. In this article, we s...Show More
Service Home Identification of Multiple-Source IoT Applications in Edge Computing
Jing Li;Weifa Liang;Wenzheng Xu;Zichuan Xu;Yuchen Li;Xiaohua Jia
The real-time communication requirement of the Internet of Things (IoT) applications promotes the convergence of IoT and Mobile Edge Computing (MEC). The MEC paradigm greatly shortens the IoT service delay by leveraging cloudlets (edge servers) of MEC in the proximity of IoT devices. Considering limited computing and storage resources in an MEC network, it is challenging to provide efficient IoT-e...Show More
Throughput Maximization of Delay-Aware DNN Inference in Edge Computing by Exploring DNN Model Partitioning and Inference Parallelism
Jing Li;Weifa Liang;Yuchen Li;Zichuan Xu;Xiaohua Jia;Song Guo
Mobile Edge Computing (MEC) has emerged as a promising paradigm catering to overwhelming explosions of mobile applications, by offloading compute-intensive tasks to MEC networks for processing. The surging of deep learning brings new vigor and vitality to shape the prospect of intelligent Internet of Things (IoT), and edge intelligence arises to provision real-time deep neural network (DNN) infere...Show More
SFC-Enabled Reliable Service Provisioning in Mobile Edge Computing via Digital Twins
Jing Li;Song Guo;Weifa Liang;Quan Chen;Zichuan Xu;Wenzheng Xu
2022 IEEE 19th International Conference on Mobile Ad Hoc and Smart Systems (MASS)
Year: 2022 | Conference Paper |
Cited by: Papers (12)
The Mobile Edge Computing (MEC) paradigm emerges as a promising technology to provide services for various mobile applications at edges of core networks while meeting stringent service delay requirements of users. Orthogonal with the MEC, Network Function Virtualization (NFV) provides the network resource management with flexibility and scalability, where Virtual Network Functions (VNFs) are deplo...Show More
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