Publications (44)
A Fragmentation-Aware Adaptive Bilevel Search Framework for Service Mapping in Computing Power Networks
Jingzhao Xie, Zhenglian Li, Gang Sun +2
Computing Power Network (CPN) unifies wide-area computing resources through coordinated network control, while cloud-native abstractions enable flexible resource orchestration and…
Scalable Fine-grained Path Control in Software Defined Networks
Long Luo, Hongfang Yu, Shouxi Luo
The OpenFlow-based SDN is widely studied to better network performance through planning fine-grained paths. However, being designed to configure path hop-by-hop, it faces the scala…
PSACCF: Prioritized Online Slice Admission Control Considering Fairness in 5G/B5G Networks
Miao Dai, Long Luo, Jing Ren +2
5G/B5G is envisioned to support various services with the assistance of network slices, each slice instance asks for adequate resources to provide the pre-negotiated service qualit…
Maximize the Long-term Average Revenue of Network Slice Provider via Admission Control Among Heterogeneous Slices
Miao Dai, Gang Sun, Hongfang Yu +1
Network slicing endows 5G/B5G with differentiated and customized capabilities to cope with the proliferation of diversified services, whereas limited physical network resources may…
Prima.cpp: Fast 30-70B LLM Inference on Heterogeneous and Low-Resource Home Clusters
Zonghang Li, Tao Li, Wenjiao Feng +8
On-device inference offers privacy, offline use, and instant response, but consumer hardware restricts large language models (LLMs) to low throughput and capability. To overcome th…
Real World Assets on-Chain Assistance Low-Altitude Computility Networks: Architecture, Methodology, and Challenges
Haoxiang Luo, Ruichen Zhang, Yinqiu Liu +3
Low-altitude airspace is becoming a new frontier for smart city services and commerce. Networks of drones, electric Vertical Takeoff and Landing (eVTOL) vehicles, and other aircraf…
Cluster-Based Multi-Agent Task Scheduling for Space-Air-Ground Integrated Networks
Zhiying Wang, Gang Sun, Yuhui Wang +2
The Space-Air-Ground Integrated Network (SAGIN) framework is a crucial foundation for future networks, where satellites and aerial nodes assist in computational task offloading. Th…
Compacting Deep Neural Networks for Internet of Things: Methods and Applications
Ke Zhang, Hanbo Ying, Hong-Ning Dai +4
Deep Neural Networks (DNNs) have shown great success in completing complex tasks. However, DNNs inevitably bring high computational cost and storage consumption due to the complexi…
Agentic-SecPBFT: Agentic AI-Driven Proactive Security Framework for Wireless PBFT Consensus in Mobile Ad-Hoc Networks
Haoxiang Luo, Yinqiu Liu, Ruichen Zhang +5
The standard Practical Byzantine Fault Tolerance (PBFT) protocol, designed for stable, wired environments, exhibits critical vulnerabilities when deployed in settings like mobile a…
Blockchain for Energy Market: A Comprehensive Survey
Tianqi Jiang, Haoxiang Luo, Kun Yang +4
The energy market encompasses the behavior of energy supply and trading within a platform system. By utilizing centralized or distributed trading, energy can be effectively managed…
User Association and Channel Allocation in 5G Mobile Asymmetric Multi-band Heterogeneous Networks
Miao Dai, Gang Sun, Hongfang Yu +2
With the proliferation of mobile terminals and the continuous upgrading of services, 4G LTE networks are showing signs of weakness. To enhance the capacity of wireless networks, mi…
Multi-UAV Enabled MEC Networks: Optimizing Delay through Intelligent 3D Trajectory Planning and Resource Allocation
Zhiying Wang, Tianxi Wei, Gang Sun +3
Mobile Edge Computing (MEC) reduces the computational burden on terminal devices by shortening the distance between these devices and computing nodes. Integrating Unmanned Aerial V…
Accelerating Geo-distributed Machine Learning with Network-Aware Adaptive Tree and Auxiliary Route
Zonghang Li, Wenjiao Feng, Weibo Cai +5
Distributed machine learning is becoming increasingly popular for geo-distributed data analytics, facilitating the collaborative analysis of data scattered across data centers in d…
HFedMS: Heterogeneous Federated Learning with Memorable Data Semantics in Industrial Metaverse
Shenglai Zeng, Zonghang Li, Hongfang Yu +4
Federated Learning (FL), as a rapidly evolving privacy-preserving collaborative machine learning paradigm, is a promising approach to enable edge intelligence in the emerging Indus…
Wireless Copilot: An AI-Powered Partner for Navigating Next-Generation Wireless Complexity
Haoxiang Luo, Ruichen Zhang, Yinqiu Liu +3
The sixth-generation (6G) of wireless networks introduces a level of operational complexity that exceeds the limits of traditional automation and manual oversight. This paper intro…
ESIA: An Efficient and Stable Identity Authentication for Internet of Vehicles
Haoxiang Luo, Jin Zhang, Xinling Li +4
Decentralized, tamper-proof blockchain is regarded as a solution to a challenging authentication issue in the Internet of Vehicles (IoVs). However, the consensus time and communica…
Data Heterogeneity-Robust Federated Learning via Group Client Selection in Industrial IoT
Zonghang Li, Yihong He, Hongfang Yu +4
Nowadays, the industrial Internet of Things (IIoT) has played an integral role in Industry 4.0 and produced massive amounts of data for industrial intelligence. These data locate o…
Real-World Asset Integration in Next-Generation Communication Networks: Fundamental, Framework, and Case Study
Tingxuan Su, Haoxiang Luo, Ruichen Zhang +3
Next-generation communication networks are characterized by integrated ultra-high reliability, ultra-low latency, massive connectivity, and ubiquitous coverage. However, this parad…
Performance Analysis and Comparison of Non-ideal Wireless PBFT and RAFT Consensus Networks in 6G Communications
Haoxiang Luo, Xiangyue Yang, Hongfang Yu +3
Due to advantages in security and privacy, blockchain is considered a key enabling technology to support 6G communications. Practical Byzantine Fault Tolerance (PBFT) and RAFT are…
Bus Trajectory-Based Street-Centric Routing for Message Delivery in Urban Vehicular Ad hoc Networks
Gang Sun, Yijing Zhang, Dan Liao +3
This paper focuses on the routing algorithm for the communications between vehicles and places in urban VANET. As one of the basic transportation facilities in an urban setting, bu…
Toward Edge General Intelligence with Multiple-Large Language Model (Multi-LLM): Architecture, Trust, and Orchestration
Haoxiang Luo, Yinqiu Liu, Ruichen Zhang +7
Edge computing enables real-time data processing closer to its source, thus improving the latency and performance of edge-enabled AI applications. However, traditional AI models of…
Performance Analysis of Non-ideal Wireless PBFT Networks with mmWave and Terahertz Signals
Haoxiang Luo, Xiangyue Yang, Hongfang Yu +3
Due to advantages in security and privacy, blockchain is considered a key enabling technology to support 6G communications. Practical Byzantine Fault Tolerance (PBFT) is seen as th…
Incentivizing Users of Data Centers Participate in The Demand Response Programs via Time-Varying Monetary Rewards
Yong Zhan, Du Xu, Hongfang Yu +1
Demand response is widely employed by today's data centers to reduce energy consumption in response to the increasing of electricity cost. To incentivize users of data centers part…
AI Reasoning for Wireless Communications and Networking: A Survey and Perspectives
Haoxiang Luo, Yu Yan, Yanhui Bian +9
Artificial Intelligence (AI) techniques play a pivotal role in optimizing wireless communication networks. However, traditional deep learning approaches often act as closed boxes,…
Information-Theoretic Generalization Analysis for Topology-aware Heterogeneous Federated Edge Learning over Noisy Channels
Zheshun Wu, Zenglin Xu, Hongfang Yu +1
With the rapid growth of edge intelligence, the deployment of federated learning (FL) over wireless networks has garnered increasing attention, which is called Federated Edge Learn…
SD-AETO: Service Deployment Enabled Adaptive Edge Task Offloading in MEC
Liangjun Song, Gang Sun, Hongfang Yu +1
In recent years, edge computing, as an important pillar for future networks, has been developed rapidly. Task offloading is a key part of edge computing that can provide computing…
Symbiotic Blockchain Consensus: Cognitive Backscatter Communications-enabled Wireless Blockchain Consensus
Haoxiang Luo, Qianqian Zhang, Gang Sun +2
The wireless blockchain network (WBN) concept, born from the blockchain deployed in wireless networks, has appealed to many network scenarios. Blockchain consensus mechanisms (CMs)…
Symbiotic PBFT Consensus: Cognitive Backscatter Communications-enabled Wireless PBFT Consensus
Haoxiang Luo, Qianqian Zhang, Hongfang Yu +2
Wireless blockchain networks have played an important role in many network scenarios, among which wireless Practical Byzantine Fault Tolerance (PBFT) consensus is regarded as one o…
A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network
Haoxiang Luo, Gang Sun, Yinqiu Liu +4
Large Language Models (LLMs) have achieved remarkable success across a wide range of applications. However, individual LLMs often produce inconsistent, biased, or hallucinated outp…
A Trustworthy Multi-LLM Network: Challenges,Solutions, and A Use Case
Haoxiang Luo, Gang Sun, Yinqiu Liu +4
Large Language Models (LLMs) demonstrate strong potential across a variety of tasks in communications and networking due to their advanced reasoning capabilities. However, because…
SNPSFuzzer: A Fast Greybox Fuzzer for Stateful Network Protocols using Snapshots
Junqiang Li, Senyi Li, Gang Sun +2
Greybox fuzzing has been widely used in stateless programs and has achieved great success. However, most state-of-the-art greybox fuzzers generally have the problems of slow speed…
DRDST: Low-latency DAG Consensus through Robust Dynamic Sharding and Tree-broadcasting for IoV
Runhua Chen, Haoxiang Luo, Gang Sun +3
The Internet of Vehicles (IoV) is emerging as a pivotal technology for enhancing traffic management and safety. Its rapid development demands solutions for enhanced communication e…
Cross-Silo Heterogeneous Model Federated Multitask Learning
Xingjian Cao, Zonghang Li, Gang Sun +2
Federated learning (FL) is a machine learning technique that enables participants to collaboratively train high-quality models without exchanging their private data. Participants u…
TPI-LLM: Serving 70B-scale LLMs Efficiently on Low-resource Edge Devices
Zonghang Li, Wenjiao Feng, Mohsen Guizani +1
Large model inference is shifting from cloud to edge due to concerns about the privacy of user interaction data. However, edge devices often struggle with limited computing power,…
AgentVNE: LLM-Augmented Graph Reinforcement Learning for Affinity-Aware Multi-Agent Placement in Edge Agentic AI
Runze Zheng, Yuqing Zheng, Zhengyi Cheng +5
The Internet of Agents is propelling edge computing toward agentic AI and edge general intelligence (EGI). However, deploying multi-agent service (MAS) on resource-constrained edge…
Reinforcement Learning based QoS/QoE-aware Service Function Chaining in Software-Driven 5G Slices
Xi Chen, Zonghang Li, Yupeng Zhang +4
With the ever growing diversity of devices and applications that will be connected to 5G networks, flexible and agile service orchestration with acknowledged QoE that satisfies end…
SkyChain Intelligence: A Blockchain-Secured Multi-Agent DRL Framework for Low-Altitude Embodied Artificial Intelligence
Haoxiang Luo, Tianqi Jiang, Ruichen Zhang +5
With the rapid development of the Low-Altitude Economy (LAE) ecosystem, Low-Altitude Embodied Artificial Intelligence (LAEAI) agents have become the core carriers of autonomous aer…
Convergence of Symbiotic Communications and Blockchain for Sustainable and Trustworthy 6G Wireless Networks
Haoxiang Luo, Gang Sun, Cheng Chi +2
Symbiotic communication (SC) is known as a new wireless communication paradigm, similar to the natural ecosystem population, and can enable multiple communication systems to cooper…
Learning In Chaos: Efficient Autoscaling and Self-Healing for Multi-Party Distributed Training
Wenjiao Feng, Rongxing Xiao, Zonghang Li +6
Node and link churn in multi-party, cross-region clusters over wide-area networks (WANs) often disrupts distributed training. However, checkpoint-based recovery and cloud-centric a…
A Survey of Network Protocol Fuzzing: Model, Techniques and Directions
Shihao Jiang, Yu Zhang, Junqiang Li +3
As one of the most successful and effective software testing techniques in recent years, fuzz testing has uncovered numerous bugs and vulnerabilities in modern software, including…
Communication-efficient Decentralized Machine Learning over Heterogeneous Networks
Pan Zhou, Qian Lin, Dumitrel Loghin +3
In the last few years, distributed machine learning has been usually executed over heterogeneous networks such as a local area network within a multi-tenant cluster or a wide area…
PerFED-GAN: Personalized Federated Learning via Generative Adversarial Networks
Xingjian Cao, Gang Sun, Hongfang Yu +1
Federated learning is gaining popularity as a distributed machine learning method that can be used to deploy AI-dependent IoT applications while protecting client data privacy and…
Heterogeneous Federated Learning via Grouped Sequential-to-Parallel Training
Shenglai Zeng, Zonghang Li, Hongfang Yu +4
Federated learning (FL) is a rapidly growing privacy-preserving collaborative machine learning paradigm. In practical FL applications, local data from each data silo reflect local…
ESCM: An Efficient and Secure Communication Mechanism for UAV Networks
Haoxiang Luo, Yifan Wu, Gang Sun +2
UAV (unmanned aerial vehicle) is rapidly gaining traction in various human activities and has become an integral component of the satellite-air-ground-sea (SAGS) integrated network…