Huaming Wu

Huaming Wu
Tianjin University | tju · Center for Applied Mathematics

PhD Freie Universität Berlin

About

115
Publications
19,616
Reads
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1,151
Citations
Additional affiliations
July 2018 - January 2019
Tianjin University
Position
  • Professor (Associate)
May 2016 - June 2018
Tianjin University
Position
  • Professor (Assistant)

Publications

Publications (115)
Conference Paper
Full-text available
Cloud computation offloading is a promising method that sending heavy computation to resourceful servers on cloud and then receiving the results from them. In this paper, we study the offloading techniques and further explore the tradeoff between shortening execution time and extending battery life of mobile devices. A novel adaptive offloading sch...
Article
Full-text available
—Mobile cloud offloading that migrates heavy computation from mobile devices to powerful cloud servers through communication networks can alleviate the hardware limitations of mobile devices thus providing higher performance and saving energy. Different applications usually give different relative importance to response time and energy consumption....
Article
Convolutional Neural Networks (CNNs) are getting deeper and wider to improve their performance and thus increase their computational complexity. We apply channel pruning methods to accelerate CNNs and reduce its computational consumption. A new pruning criterion is proposed based on the mean gradient for convolutional kernels. To significantly redu...
Article
Full-text available
Application partitioning that splits the executions into local and remote parts, plays a critical role in high-performance mobile offloading systems. Mobile devices can obtain the most benefit from Mobile Cloud Computing (MCC) or Mobile Edge Computing (MEC) through optimal partitioning. Due to unstable resources at the wireless network (network dis...
Article
Full-text available
Mobile cloud offloading migrates heavy computation from mobile devices to remote cloud resources or nearby cloudlets. It is a promising method to alleviate the struggle between resource-constrained mobile devices and resource-hungry mobile applications. Caused by frequently changing location mobile users often see dynamically changing network condi...
Article
Full-text available
Autonomic computing investigates how systems can achieve (user) specified “control” outcomes on their own, without the intervention of a human operator. Autonomic computing fundamentals have been substantially influenced by those of control theory for closed and open-loop systems. In practice, complex systems may exhibit a number of concurrent and...
Preprint
While Identity Document Verification (IDV) technology on mobile devices becomes ubiquitous in modern business operations, the risk of identity theft and fraud is increasing. The identity document holder is normally required to participate in an online video interview to circumvent impostors. However, the current IDV process depends on an additional...
Article
With the rapid development of Artificial Intelligence (AI) and Internet of Things (IoT), we have to perform increasingly more resource-hungry and compute-intensive applications on IoT devices, where the available computing resources are insufficient. With the assistance of Mobile Edge Computing (MEC), offloading partial complex tasks from mobile de...
Article
Temporal community detection is helpful to discover and analyze significant groups or clusters hidden in dynamic networks in the real world. A variety of methods, such as modularity optimization, spectral method, and statistical network model, has been developed from diversified perspectives. Recently, network embedding-based technologies have made...
Article
Full-text available
Big data frameworks such as Apache Spark are becoming prominent to perform large-scale data analytics jobs. However, local or on-premise computing resources are often not sufficient to run these jobs. Therefore, public cloud resources can be hired on a pay-per-use basis from the cloud service providers to deploy a Spark cluster entirely on the clou...
Article
As a distributed computing paradigm, edge computing has become a key technology for providing timely services to mobile devices by connecting Internet of Things (IoT), cloud centers and other facilities. By offloading compute-intensive tasks from IoT devices to edge/cloud servers, the communication and computation pressure caused by the massive dat...
Article
Full-text available
The advent of vehicular edge computing (VEC) has generated enormous attention in recent years. It pushes the computational resources in close proximity to the data sources and thus caters for the explosive growth of vehicular applications. Owing to the high mobility of vehicles, these applications are of latency-sensitive requirements in most cases...
Preprint
Full-text available
Cloud computing has been regarded as a successful paradigm for IT industry by providing benefits for both service providers and customers. In spite of the advantages, cloud computing also suffers from distinct challenges, and one of them is the inefficient resource provisioning for dynamic workloads. Accurate workload predictions for cloud computin...
Preprint
Full-text available
Autonomic computing investigates how systems can achieve (user) specified control outcomes on their own, without the intervention of a human operator. Autonomic computing fundamentals have been substantially influenced by those of control theory for closed and open-loop systems. In practice, complex systems may exhibit a number of concurrent and in...
Article
With the popularity of mobile devices, intelligent applications, e.g., face recognition, intelligent voice assistant, and gesture recognition, have been widely used in our daily lives. However, due to the lack of computing capacities, it is difficult for mobile devices to support complex Deep Neural Network (DNN) inference. To alleviate the pressur...
Article
Full-text available
The recent surge in the number of connected vehicles and vehicular applications really benefits citizens. Various vehicular applications are developed to cater for the increasingly sophisticated demands of drivers. Against this background, vehicular edge computing (VEC) is put forward as a promising solution to meet the strict latency requirement o...
Article
A variety of methods have been proposed for modeling and mining dynamic complex networks, in which the topological structure varies with time. As the most popular and successful network model, the stochastic block model (SBM) has been extended and applied to community detection, link prediction, anomaly detection, and evolution analysis of dynamic...
Article
Advances in information and communication technologies have significantly influenced the operation of low-voltage distribution grids. As essential elements of distribution grids, user-side smart meters find many smart grid applications, for example to measure electrical energy use and facilitate communications. However, the service models of distri...
Chapter
The next generation Internet of Things (IoT) applications are offering multiple services and run in a distributed heterogeneous environment. In such applications, Quality of Service (QoS) requirements are in jeopardy when the computing operations are only outsourced to the public cloud. For IoT applications, a comprehensive framework that supports...
Conference Paper
Full-text available
The fast-growing Internet of Thing (IoT) has generated a vast number of tasks which need to be performed efficiently. Owing to the drawback of the sensor-to-cloud com�puting paradigm in IoT, mobile edge computing (MEC) has become a hot topic recently. Against this backdrop, we focus on the offloading of tasks characterized by intrinsic correlations...
Article
Vehicular edge computing (VEC) pushes the computational resources to the logical edge of the networks, thus enabling vehicles to run resource-hungry and time-sensitive applications by outsourcing operations. Many studies revolved around VEC focus on the optimization of response latency, energy consumption, or both of them, assuming that the computa...
Article
Anomaly detection in dynamic networks aims to find network elements with significantly different behaviors from the vast majority. Most existing methods focus on one specific task, that is, only detect anomalies of one type of element isolated, so they lose the ability to model the correlation and driving mechanism between different abnormal behavi...
Chapter
Full-text available
The development of Internet of Things (IoT) technology enables the rapid growth of connected smart devices and mobile applications. However, due to the constrained resources and limited battery capacity, there are bottlenecks when utilizing the smart devices. Mobile edge computing (MEC) offers an attractive paradigm to handle this challenge. In thi...
Article
In most cases, the block structures and evolution characteristics always coexist in dynamic networks. This leads to inaccurate results of temporal community structure analysis with a two-step strategy. Fortunately, a few approaches take the evolution characteristics into account for modeling temporal community structures. But the number of communit...
Article
With the rapid development of Internet of Things (IoT) and next-generation communication technologies, resource-constrained mobile devices fail to meet the demand of resource-hungry and compute-intensive applications. To cope with this challenge, with the assistance of Mobile Edge Computing (MEC), offloading complex tasks from mobile devices to edg...
Article
With the rapid development of the Internet of Things (IoT) and communication technology, Deep Neural Network (DNN) applications like computer vision, can now be widely used in IoT devices. However, due to the insufficient memory, low computing capacity, and low battery capacity of IoT devices, it is difficult to support the high-efficiency DNN infe...
Article
Internet of things (IoT) applications are becoming more resource-hungry and latency-sensitive, which are severely constrained by limited resources of current mobile hardware. Mobile cloud computing (MCC) can provide abundant computation resources, while mobile edge computing (MEC) aims to reduce the transmission latency by offloading complex tasks...
Article
Two functions are essential and necessary for wireless powered communication network, which are energy beamforming and localization. On one hand, energy beamforming controls the wireless energy waves of energy access point (E-AP) in order to activate the nodes for transmitting information. On the other hand, locating the nodes is important to netwo...
Article
Network embedding has been successfully used for a variety of tasks, e.g., node clustering, community detection, link prediction and evolution analysis on complex networks. For a given network, embedding methods are usually designed based on first-order proximity, second-order proximity, community constraints, etc. However, they are incapable of ca...
Article
Full-text available
Great achievements have been made in network embedding based on single-layer networks. However, there are a variety of scenarios and systems that can be presented as multiplex networks, which can reveal more interesting patterns hidden in the data compared to single-layer networks. In the field of network embedding, in order to project the multiple...
Article
Recently, network embedding (NE) is an amazing research point in complex networks and devoted to a variety of tasks. Nearly, all the methods and models of NE are based on the local, high-order, or global similarity of the networks, and few studies have focused on the role discovery or structural similarity, which is of great significance in spreadi...
Article
As a key technology in the 5G era, mobile edge computing (MEC) has developed rapidly in recent years. MEC aims to reduce the service delay of mobile users, while alleviating the processing pressure on the core network. MEC can be regarded as an extension of cloud computing on the user side, which can deploy edge servers and bring computing resource...
Article
Full-text available
It is a common paradigm in object detection frameworks that the samples in training and testing have consistent distributions for the two main tasks: Classification and bounding box regression. This paradigm is popular in sampling strategy for training an object detector due to its intuition and practicability. For the task of localization quality...
Article
Full-text available
In the smart mariculture, batch testing of breeding traits is a key issue in the breeding of improved fish varieties. The body length (BL), body width (BW) and body area (BA) features of fish are important indicators. They are of great significance in breeding, feeding and classification. To accurately and intelligently obtain the morphological cha...
Preprint
Full-text available
As a key technology in the 5G era, Mobile Edge Computing (MEC) has developed rapidly in recent years. MEC aims to reduce the service delay of mobile users, while alleviating the processing pressure on the core network. MEC can be regarded as an extension of cloud computing on the user side, which can deploy edge servers and bring computing resource...
Article
With the explosive growth of mobile data and the unprecedented demand for computing power, resource-constrained edge devices cannot effectively meet the requirements of Internet of Things (IoT) applications and Deep Neural Network (DNN) computing. As a distributed computing paradigm, edge offloading that migrates complex tasks from IoT devices to e...
Article
Network representation learning or embedding aims to project the network into a low-dimensional space that can be devoted to different network tasks. Temporal networks are an important type of network whose topological structure changes over time. Compared with methods on static networks, temporal network embedding (TNE) methods are facing three ch...
Article
Full-text available
The automotive industry, a key part of Industrial Internet of Things (IIoT), is now converging with cognitive computing (CC) and leading to industrial Cognitive Internet of Vehicles (CIoV). As the major data source of industrial CIoV, social media has huge impact on the quality of service (QoS) of automotive industry. To provide vehicular social me...
Article
Among the novel IT paradigms, Cloud Computing and the Internet of Things (CloudIoT) are two complementary areas designed to support the creation of smart cities and application services. The CloudIoT not only presents ubiquitous services through IoT nodes, but it also provides virtually unlimited resources through services composition. Services com...
Article
With the rapid development of blockchain technology, the cross-blockchain asset transfer has been in great demand. However, most existing cross-blockchain solutions encounter low efficiency problems due to the centralized features, unfriendly development environment, and difficulty in cooperation. This paper proposes an interaction protocol for sec...
Article
With the proliferation of compute-intensive and delay-sensitive mobile applications, large amounts of computational resources with stringent latency requirements are required on Internet of Things (IoT) devices. One promising solution is to offload complex computing tasks from IoT devices either to Mobile Edge Computing (MEC) or Mobile Cloud Comput...
Chapter
Social internet of vehicle (SIoV), also termed vehicular social network (VSN), endeavors to integrate social networking related concepts into IoV, with an aim to make vehicles capable of social communication and low-cost infotainment service provisioning. In spite of potential prospects, some issues pertaining to SIoV remain to be addressed such as...
Preprint
The development of Internet of Things (IoT) technology enables the rapid growth of connected smart devices and mobile applications. However, due to the constrained resources and limited battery capacity, there are bottlenecks when utilizing the smart devices. Mobile edge computing (MEC) offers an attractive paradigm to handle this challenge. In thi...
Article
Full-text available
Identification of community structures and the underlying semantic characteristics of communities are essential tasks in complex network analysis. However, most methods proposed so far are typically only applicable to assortative community structures, that is, more links within communities and fewer links between different communities, which ignore...
Article
Channel state information (CSI) feedback plays an important part in frequency division duplex (FDD) massive multiple-input multiple-output (MIMO) systems. However, it is still facing many challenges, e.g., excessive feedback overhead, low feedback accuracy and a large number of training parameters. In this paper, to address these practical concerns...
Preprint
With the continuous growth of mobile data and the unprecedented demand for computing power, resource-constrained edge devices cannot effectively meet the requirements of Internet of Things (IoT) applications and Deep Neural Network (DNN) computing. As a distributed computing paradigm, edge offloading that migrates complex tasks from IoT devices to...
Conference Paper
Full-text available
Social internet of vehicle (SIoV), also termed vehicular social network (VSN), endeavors to integrate social networking related concepts into IoV, with an aim to make vehicles capable of social communication and low-cost infotainment service provisioning. In spite of potential prospects, some issues pertaining to SIoV remain to be addressed such as...
Article
Community detection and community evolution tracking are two important tasks in dynamic complex network analysis. Recently, a variety of models and methods have been proposed for detecting the community structure and analyzing their evolution. However, all these methods are only committed to improving the performance of community detection or ident...
Article
City Internet-of-Things (IoT) applications are becoming increasingly complicated and thus require large amounts of computational resources and strict latency requirements. Mobile cloud computing (MCC) is an effective way to alleviate the limitation of computation capacity by offloading complex tasks from mobile devices (MDs) to central clouds. Besi...
Article
Full-text available
Intelligent transportation system (ITS) has attracted extensive attention in both academia and industry for its potential benefits. For example, ITS is dedicated to convenient, economical and environmentally friendly service provisioning for the drivers and passengers in vehicles via advanced technologies including artificial intelligence (AI), kno...
Article
As a powerful tool for machine learning on the graph, network embedding, which projects nodes into low-dimensional spaces, has a variety of applications on complex networks. Most current methods and models are not suitable for bipartite networks, which have two different types of nodes and there are no links between nodes of the same type. Furtherm...
Article
Full-text available
Abstract Future wireless communications are becoming increasingly complex with different radio access technologies, transmission backhauls, and network slices, and they play an important role in the emerging edge computing paradigm, which aims to reduce the wireless transmission latency between end-users and edge clouds. Deep learning techniques, w...
Article
Full-text available
With the proposed of Generative Adversarial Networks (GANs), the generative adversarial models have been extensively studied in recent years. Although probability-based methods have achieved remarkable results in image synthesis tasks, there are still some unsolved challenges that are difficult to overcome. In this paper, we propose a novel model,...
Article
Full-text available
Fog/Edge computing emerges as a novel computing paradigm that harnesses resources in the proximity of the Internet of Things (IoT) devices so that, alongside with the cloud servers, provide services in a timely manner. However, due to the ever-increasing growth of IoT devices with resource-hungry applications, fog/edge servers with limited resource...