Huaming Wu

Huaming Wu
Tianjin University | tju · Center for Applied Mathematics

PhD Freie Universität Berlin

About

127
Publications
22,788
Reads
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1,649
Citations
Citations since 2016
106 Research Items
1592 Citations
20162017201820192020202120220100200300400500600
20162017201820192020202120220100200300400500600
20162017201820192020202120220100200300400500600
20162017201820192020202120220100200300400500600
Additional affiliations
July 2018 - January 2019
Tianjin University
Position
  • Professor (Associate)
May 2016 - June 2018
Tianjin University
Position
  • Professor (Assistant)

Publications

Publications (127)
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
As a powerful tool for storing digital information in chemically synthesized molecules, DNA-based data storage has undergone continuous development and received increasingly more attention. Efficiently recovering information from large-scale DNA strands that suffer from insertions, deletions, and substitution errors (collectively referred to as edi...
Article
In order to meet people’s demands for intelligent and user-friendly Internet of Things (IoT) services, the amount of computation is increasing rapidly and the requirements of task delay are becoming increasingly more stringent. However, the constrained battery capacity of IoT devices greatly limits the user experience. Energy harvesting technologie...
Article
Identifying high-order Single Nucleotide Polymorphism (SNP) interactions of additive genetic model is crucial for detecting complex disease gene-type and predicting pathogenic genes of various disorders. We present a novel framework for high-order gene interactions detection, not directly identifying individual site, but based on Deep Learning (DL)...
Article
Deoxyribonucleic acid (DNA) is an attractive medium for long-term digital data storage due to its extremely high storage density, low maintenance cost and longevity. However, during the process of synthesis, amplification and sequencing of DNA sequences with homopolymers of large run-length, three different types of errors, namely, insertion, delet...
Article
Deoxyribonucleic acid (DNA)-based data storage has grown rapidly due to its advantages with the increase in infrequently large amounts of data. However, when the maximum homopolymer runlength (RLL) of the DNA strand is large and the GC-content is either too high or too low, the DNA synthesis and sequencing processes are prone to substitution, delet...
Article
The startling rise in smart vehicles stimulates the rapid development of new paradigms such as Social Internet of Vehicle (SIoV) and Vehicular Fog Computing (VFC). Trustworthiness has been regarded as a dominating issue in all the have-to-be-addressed issues in SIoV, and many reputation-based countermeasures have been adopted to solve the trustines...
Article
With the increasingly humanized and intelligent operation of Industrial Internet of Things (IIoT) systems in Industry 5.0, Delay-Sensitive and Compute-Intensive (DSCI) devices have proliferated, and their demand for low latency and low power consumption has become more and more eager. In order to extend the battery life and improve the quality of u...
Article
Object detection, as a fundamental problem in computer vision, has been widely used in many industrial applications, such as intelligent manufacturing and intelligent video surveillance. In this work, we find that classification and regression have different sensitivities to the object translation, from the investigation about the availability of h...
Article
The application of DNA as a powerful tool for storing digital information in chemically synthesized molecules has undergone continuous development. To explore its potential and limitations, we model the DNA storage channel as a cascade of a series of parallel and independent DNA noisy synchronization error channels and a shuffling-sampling channel,...
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...
Article
Deoxyribonucleic acid (DNA)-based data storage is a promising new storage technology which has the advantage of high storage capacity and long storage time compared with traditional storage media. However, the synthesis and sequencing process of DNA can randomly generate many types of errors, which makes it more difficult to cluster DNA sequences t...
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
Network embedding is an important class of link prediction methods, which can use the distance between learned low-dimensional node representations to characterize the similarity between nodes. Traditional network embedding methods focus on single-layer networks, while in reality, a large part of complex networks are not isolated, but interdependen...
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
With the rapid development of Artificial Intelligence (AI) and the Internet of Vehicles (IoV), there is an increasing demand for deploying various intelligent applications on vehicles. Vehicular Edge Computing (VEC) is receiving extensive attention from both the industry and academia due to its benefits from the edge computing paradigm, which pushe...
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...
Article
With the rapid development of the Internet of Things (IoT) and communication technology, Deep Neural Network (DNN) applications have been widely used in IoT devices. However, due to resource constraints on these devices, IoT devices cannot support complicated DNN operation effectively and thus fail to fulfill the requirements of Quality of Service...
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...
Chapter
Spectral clustering is a widely used clustering algorithm based on the advantages of simple implementation, small computational cost, and good adaptability to arbitrarily shaped data sets. However, due to the lack of data protection mechanism in spectral clustering algorithm and the fact that the processed data often contains a large amount of sens...
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
Full-text available
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...