Geyong Min

University of Exeter | UoE · College of Engineering, Mathematics and Physical Sciences

Vehicular Edge Computing (VEC) is a computing paradigm that brings Mobile Edge Computing (MEC) to the road and vehicular scenarios by providing low-latency and high-efficiency computation services. One key technology of VEC is task offloading, which allows vehicles to send their computation tasks to surrounding Roadside Units (RSUs) for execution,...

Federated learning (FL) is a swiftly evolving field within machine learning for collaboratively training models at the network edge in a privacy-preserving fashion, without training data leaving the devices where it was generated. The privacy-preserving nature of FL shows great promise for applications with sensitive data such as healthcare, financ...

Nature-inspired computing (NIC) has been widely studied for many optimization scenarios. However, miscellaneous solution space of real-world problem causes it is challenging to guarantee the global optimum. Besides, cumbersome structure and complex parameters setting-up make the existed algorithms hard for most users who are not specializing in NIC...

As an indispensable part of modern critical infrastructures, cameras deployed at strategic places and prime junctions in an intelligent transportation system (ITS), can help operators in observing traffic flow, identifying any emergency situation, or making decisions regarding road congestion without arriving on the scene. However, these cameras ar...

Efficient and timely dispatch of maintenance personnel for fault detection and failure recovery play a key role towards safe operation of power grid and has become a challenging issue. To address this challenge, this paper proposes a new optimal strategy, namely adaptive NSGAII (NSGAII/A), for dispatching maintenance personnel in the event of secur...

Increasing workload conditions lead to a significant surge in power consumption and computing node failures in data centers. The existing workload distribution strategies focused on either thermal awareness or failure mitigation, overlooking the impact of node failures on the energy efficiency of cloud data centers. To address this issue, a new hol...

Resource provisioning for the ever-increasing applications to host the necessary network functions necessitates the efficient and accurate prediction of required resources. However, the current efforts fail to leverage the inherent features hidden in network traffic, such as temporal stability, service correlation and periodicity, to predict the re...

Instantiated containers of an application are distributed across multiple Physical Machines (PMs) to achieve high parallel performance. Container placement plays a vital role in network traffic and the performance of containerized data centers. Existing container placement techniques are inadequate due to the ignorance of container traffic patterns...

In this paper, we propose a learning-based cooperative edge caching approach to improve the caching performance. We formulate the cooperative edge caching problem as a NP-hard knapsack problem with the goal of minimizing the average content delivery latency. To solve the problem, we firstly establish a TCNCP model to predict the popularity of futur...

The ever-expanding scale of cloud datacenters necessitates automated resource provisioning to best meet the requirements of low latency and high energy-efficiency. However, due to the dynamic system states and various user demands, efficient resource allocation in cloud faces huge challenges. Most of the existing solutions for cloud resource alloca...

Edge computing is an emerging promising computing paradigm that brings computation and storage resources to the network edge, hence significantly reducing the service latency and network traffic. In edge computing, many applications are composed of dependent tasks where the outputs of some are the inputs of others. How to offload these tasks to the...

Spatial keyword query has attracted wide-spread academic and industrial concerns due to the popularity of LBSs and IOTs. To efficiently support the online query processing, the data owners need to outsource their data to cloud platforms. However, the outsourcing services may raise privacy leaking issues. Moreover, access control, another important...

Most existing routing schemes in Software-Defined Vehicular Networks (SDVNs) consider the networks as a sequence of static graphs. However, the vehicular network is a de facto temporal graph, and routing in the static graph could be inefficient. The main reason could be the temporal information that would play a vital role in the vehicular network....

As customers take virtual machines (VMs) as their demands, high-efficient placement of VMs is required to reduce the energy consumption in data centers. Existing Virtual Machine placement (VMP) strategies can minimize energy consumption of data centers by optimizing resource allocation in terms of multiple physical resources (e.g., memory, bandwidt...

Blockchain has recently been regarded as an important enabler for building secure energy trading in microgrid systems due to its inherent features of distributively providing immutable data record, storage and sharing across networks in a Peer-to-Peer (P2P) manner. However, designing highly-efficient and scalable blockchain-enabled energy trading m...

Greedy routing schemes are considered the most efficient routing solutions in vehicular communications. However , most existing greedy routing schemes only consider simple routing metrics for complicated communication scenarios. This shortcoming can inevitably degrade the exhibited overall performance. In such a scheme, a vehicle only selects a rel...

Federated learning (FL) is a privacy-preserving machine learning paradigm that enables collaborative training among geographically distributed and heterogeneous users without gathering their data. Extending FL beyond the conventional supervised learning paradigm, federated Reinforcement Learning (RL) was proposed to handle sequential decision-makin...

Identifying key structures from social networks that aims to discover hidden patterns and extract valuable information is an essential task in the network analysis realm. These different structure detection tasks can be integrated naturally owing to the topological nature of key structures. However, identifying key network structures in most studie...

Implementing federated learning (FL) algorithms in wireless networks has garnered a wide range of attention. However, few works have considered the impact of user mobility on the learning performance. To fill this research gap, firstly, we develop a theoretical model to characterize the hierarchical federated learning (HFL) algorithm in wireless ne...

Federated Learning (FL) is a recent development in the field of machine learning that collaboratively trains models without the training data leaving client devices, in order to preserve data-privacy. In realistic settings, the total training set is distributed over clients in a highly non-Independent and Identically Distributed (non-IID) fashion,...

Identifying the optimal groups of users that are closely connected and satisfy some ranking criteria from an attributed social network attracts significant attention from both academia and industry. Skyline query processing, a multicriteria decision-making optimized technique, is recently embedded into cohesive subgraphs mining in graphs/social net...

One of the main challenges in computer science and image processing is 2D human pose estimation. Specifically, occlusion and in particular occlusion of human joints caused by camera angle are of paramount importance. In this paper, a new highly accurate network was proposed that can estimate 2D human poses in video images using deep learning. We em...

Deep Neural Networks (DNNs) have become an essential and important supporting technology for smart Internet-of-Things (IoT) systems. Due to the high computational costs of large-scale DNNs, it might be infeasible to directly deploy them in energy-constrained IoT devices. Through offloading computation-intensive tasks to the cloud or edges, the comp...

The statistical values of the latencies between two sets of hosts over a given period, which is referred as to statistical latency, can benefit many applications in the next-generation networks, such as Network in a Box (NIB) based resource provisioning. However, existing methods can hardly achieve low measurement cost and high prediction accuracy...

Federated Learning (FL) is an emerging approach for collaboratively training Deep Neural Networks (DNNs) on mobile devices, without private user data leaving the devices. Previous works have shown that non-Independent and Identically Distributed (non-IID) user data harms the convergence speed of the FL algorithms. Furthermore, most existing work on...

The cloud computing paradigm provides numerous tempting advantages, enabling users to store and share their data conveniently. However, users are naturally resistant to directly outsourcing their data to the cloud since the data often contain sensitive information. Although numerous fine-grained access control schemes for cloud-data sharing have be...

Three-way concept analysis (3WCA), a combination of three-way decision and formal concept analysis, is widely used in the field of knowledge discovery. Generally, constructing three-way concept lattices requires the original formal context and its complement context simultaneously. Additionally, the existing three-way concept lattice construction a...

Flying Ad hoc Network (FANET) has drawn significant consideration due to its rapid advancements and extensive use in civil applications. However, the characteristics of FANET including high mobility, limited resources, and distributed nature, have posed a new challenge to develop a secure and efficient routing scheme for FANET. To overcome these ch...

Network function virtualization (NFV) is critical to the scalability and flexibility of various network services in the form of service function chains (SFCs), which refer to a set of Virtual Network Functions (VNFs) chained in a specific order. However, the NFV performance is hard to fulfill the ever-increasing requirements of network services mai...

Data centers are critical to the commercial and social activities of modern society but are also major electricity consumers. To minimize their environmental impact, it is imperative to make data centers more energy efficient while maintaining a high quality of service (QoS). Bearing this consideration in mind, we develop an analytical model using...

Wireless power transfer technologies such as simultaneous wireless information and power transfer (SWIPT) have shown significant potentials to revolutionise the design of future wireless communication systems. When the only energy source is the wireless signals that are mainly intended for information communications, the sustainability and outage p...

Knowledge graph describes entities by numerous RDF data (subject-predicate-object triples), which has been widely applied in various fields, such as artificial intelligence, Semantic Web, entity summarization. With time elapses, the continuously increasing RDF descriptions of entity lead to information overload and further cause people confused. Wi...

Notice that it is difficult and expensive to implement global network measurements to obtain network distance, a feasible idea is to predict unknown distances by introducing network coordinates with limited network measurements. The existing solutions always represent the unknown network distances in a rather unique number. However, research and ap...

The quantitative performance analysis plays a critical role in assessing the capability of Vehicular Edge Computing (VEC) systems to meet the requirements of vehicular applications. However, developing accurate analytical models for VEC systems is extremely challenging due to the unique features of intelligent vehicular applications. Specifically,...

Mobile social networks (MSNs) provide real-time information services to individuals in social communities through mobile devices. However, due to their high openness and autonomy, MSNs have been suffering from rampant rumors, fraudulent activities, and other types of misuses. To mitigate such threats, it is urgent to control the spread of fraud inf...

Three-way concept analysis (3WCA) has been an emerging and important methodology for knowledge discovery and data analysis. Particularly, 3WCA can efficiently characterize the information of “jointly possessed” and “jointly not possessed” compared to the classical formal concept only can describe common attributes owned by objects. This property, t...

With the rapid development of the fifth-generation (5G) wireless communications, the number of users is increasing dramatically and Ultra-Dense Networks (UDN) are becoming more important for supporting numerous users and emerging mission-critical applications. In order to conquer the communication restrictions caused by natural disasters, an emerge...

Over the past few years, Fog Radio Access Networks (F-RANs) have become a promising paradigm to support the tremendously increasing demands of multimedia services, by pushing computation and storage functionalities towards the edge of networks, closer to users. In F-RANs, distributed edge caching among Fog Access Points (F-APs) can effectively redu...

The Internet of Things (IoT) and Industrial 4.0 bring enormous potential benefits by enabling highly customised services and applications, which create huge volume and variety of data. However, preserving the privacy in IoT and Industrial 4.0 against re-identification attacks is very challenging. In this work, we considered three main data types ge...

The rapid development of the Industrial Internet of Things (IIoT) enables IIoT devices to offload their computation-intensive tasks to nearby edges via wireless Base Stations (BSs) and thus relieve their resource constraints. To better guarantee Quality-of-Service (QoS), it has become necessary to cooperate multiple edges instead of letting them wo...

Federated Learning (FL) has been employed for tremendous privacy-sensitive applications, where distributed devices collaboratively train a global model. In Industrial Internet-of-Things (IIoT) systems, training latency is the key performance metric as the automated manufacture usually requires timely processing. The existing works increase the numb...

Fractured-vuggy carbonate reservoirs have complex geological structures including pores, caves and fractures, which causes frequent working system adjustments and makes the production prediction extremely challenging. Currently, the most widely used methods in such prediction are the water drive characteristic curve methods and machine learning bas...

The emerging technologies, such as smart sensors, 5G/6G wireless communication, artificial intelligence, etc., have being maturing the future Internet of Things (IoT) by connecting massive number of devices, which are expected to consistently collect and transmit real-time data to support business intelligence in an efficient and privacy-preserving...

The booming of Social Internet of Things (SIoT) has witnessed the significance of graph mining and analysis for social network management. Online Social Networks (OSNs) can be efficiently managed by monitoring users behaviors within a cohesive social group represented by a maximal clique. They can further provide valued social intelligence for thei...

The last few decades have witnessed an explosive growth of the Internet-of-Things (IoT) systems, which provide ubiquitous sensing and computing services. When adopted in the industrial and manufacturing environments, IoT is referred to as the Industrial IoT (IIoT), which has attracted increasing research attention. Energy efficiency is one of the m...

Energy costs have dramatically increased in data center networks as an increasing number of large-scale Internet applications are used. In software-defined vehicular networks (SDVN), the communication delay between two vehicles and between vehicles and the controller will dramatically climb up as the number of vehicles increases. This requires more...

With the remarkable development of the 5G technologies, more and more real-time and complex computational tasks from the Internet-of-Things (IoT) systems can be fulfilled by 5G edge servers. While the ultra-dense deployment is required for 5G edge services, in the upcoming era of 6G with an even more limited communication range, it is almost imposs...

Mobile Opportunistic Networks (MONs) are characterized by the lack of continuous end-to-end connectivity between two nodes due to node mobility, sparse deployment, and constrained resources. In order to fulfill ubiquitous communication requirements of them, social-aware routing, which exploits social ties and behaviors among nodes to make forwardin...

The future mobile communication system is expected to provide ubiquitous connectivity and unprecedented services over billions of devices. The flying drone, also known as unmanned aerial vehicle, is prominent in its flexibility and low cost, and has emerged as a significant network entity to realize such ambitious targets. However, the distributed...

Datacenters are critical to the commercial and social activities of modern society but are also major electricity consumers. To minimize their environmental impact, we must make datacentres more efficient whilst keeping the quality of service high. In this work we consider how a key datacenter component, Virtual Network Functions (VNFs), can be pla...

The safety of the transmission lines maintains the stable and efficient operation of the smart grid. Therefore, it is very important and highly desirable to diagnose the health status of transmission lines by developing an efficient prediction model in the grid sensor network. However, the traditional methods have limitations caused by the characte...

Online social networks provide convenience for users to propagate ideas, products, opinions, and many other items that compete with different items for influence spread. How to accurately model the spread of competitive influence is still a challenging problem. Almost all reported methods ignore the effect of trust relationships in the spread of co...

Flying Ad hoc Network (FANET) has drawn significant interests from industry and academy owing to its rapid advancement and extensive use in civil and military applications. However, due to high mobility, its limited resources and distributed nature have posed a new challenge on the development of a secure and efficient routing scheme for FANET. Thi...

Flying devices, e.g., Unmanned Aerial Vehicles (UAV) and High Altitude Platforms (HAP) are showing great potentials to revolutionise human society with unprecedented efficiency and convenience. 5G and beyond (5GB) networks have been considered as an important infrastructure for supporting flying devices to accomplish mission-critical applications....

The epoch of the Internet of Things (IoT) has come by enabling almost everything to gather and share electronic information. Considering the unreliable factors of public IoT, how to outsource huge amounts of indispensable stream data generated by the nodes to the remote storage efficiently and securely is one of the most challenging issues. In this...

The data privacy concerns are increasingly affecting the Internet of things (IoT) and artificial intelligence (AI) applications, in which it is very challenging to protect the privacy of the underlying data. In recent, the advancements in the performances of homomorphic encryption (HE) make it possible to help protect sensitive and personal data in...

With the explosive growth of smart devices and development of wireless technology, numerous new applications such as Augmented Reality (AR), Virtual Reality (VR), Mixed Reality (MR), autonomous driving and intelligent manufactory enter our daily life and put stringent requirements on the current communications technologies. Boosted by multimedia ap...

Network slicing has emerged as a promising networking paradigm to provide resources tailored for Industry 4.0 and diverse services in 5G networks. However, the increased network complexity poses a huge challenge in network management due to virtualised infrastructure and stringent Quality-of-Service (QoS) requirements. Digital twin (DT) technology...

Multi-access Edge Computing (MEC) is a key technology in the fifth-generation (5G) network and beyond. MEC extends cloud computing to the network edge (e.g., base stations, MEC servers) to support emerging resource-intensive applications on mobile devices. As a crucial problem in MEC, service migration needs to decide where to migrate user services...

To provide efficient networking services at the edge of Internet-of-Vehicles (IoV), Software-Defined Vehicular Network (SDVN) has been a promising technology to enable intelligent data exchange without giving additional duties to the resource constrained vehicles. Compared with conventional centralized SDVNs, hybrid SDVNs combine the centralized co...

As the network security gradually deviates from the virtual environment to the real environment, the security problems caused by abnormal users in social networks are becoming increasingly prominent. These abnormal users usually form a group which can be regarded as an isolated network. This paper aims to detect the isolated maximal cliques from a...