Sanglu Lu's research while affiliated with Nanjing University and other places
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Publications (382)
Conducting federated learning across distributed sites with In-Band Network Telemetry (INT) based data collection faces critical challenges, including control decisions of different frequencies, convergence of the models being trained, and resource provisioning coupled over time. To study this problem, we formulate a non-linear mixed-integer progra...
Multi-party interactive live video streaming applications have attracted millions of daily active users and are anticipated a blooming market in the next few years. A fundamental research problem in live streaming is bitrate coordination, which selects the proper upload/download bitrate for multiple participants in the system to maximize the users’...
Graph stream data is widely applied to describe the relationships in networks such as social networks, computer networks and hyperlink networks. Due to the large volume and high dynamicity of graph streams, several graph sketches were proposed to summarize them for fast queries. However, the existing graph sketches suffer from low performance on gr...
There are two problems that widely exist in current end-to-end sign language processing architecture. One is the CTC spike phenomenon which weakens the visual representational ability in Continuous Sign Language Recognition (CSLR). The other one is the exposure bias problem which leads to the accumulation of translation errors during inference in S...
Graph meta learning aims to learn historical knowledge from training graph neural networks (GNNs) models and adapt it to downstream learning tasks in a target graph, which has drawn increasing attention due to its ability of knowledge transfer and fast adaptation. While existing graph meta learning approaches assume the learning tasks are from the...
Despite being widely deployed in safety-critical applications such as autonomous driving and health care, deep neural networks (DNNs) still suffer from non-negligible reliability issues. Numerous works had reported that DNNs were vulnerable to either natural environmental noises or man-made adversarial noises. How to repair DNNs in deployment with...
Multivariable time series (MTS) clustering is an important topic in time series data mining. The major challenge of MTS clustering is to capture the temporal correlations and the dependencies between multiple variables. In this paper, we propose a novel MTS clustering approach based on graph convolutional network (GCN), which is a powerful feature...
In industrial production, the orientation of facility components can indicate whether the facility is on a regular operating track. For example, when a component get loose, the orientation variation of the component would exceed the normal range. A common approach for orientation measurement is to attach an inertial measurement unit (IMU) to the ta...
Loosely coupled and highly cohesived microservices running in containers are becoming the new paradigm for application development. Compared with monolithic applications, applications built on microservices architecture can be deployed and scaled independently, which promises to simplify software development and operation. However, the dramatic inc...
Influence maximization is the problem of finding a set of seed nodes in the network that maximizes the influence spread, which has become an important topic in social network analysis. Conventional influence maximization algorithms cause “unfair" influence spread among different groups in the population, which could lead to severe bias in public op...
Deploying microservice instances on the edge device close to end users can provide on-site processing thus reducing request response time. Each microservice has multiple instances that can process requests in parallel. To achieve high processing efficiency, the number of these instances is scaled according to the workload, which is also known as au...
The software-defined network (SDN) enabled mobile edge network greatly facilitates network resource management and promotes many emerging applications. However, user mobility may cause the SDN controller to set flow rules frequently, introduce additional flow setup latency, cause delay jitter, and undermine latency-sensitive services. Proactive flo...
With the rising of demands for novel Human-Computer Interaction (HCI) approaches in the 3D space, a number of intelligent approaches have been proposed to achieve the HCI by tracking the translation and rotation of the target devices. In this paper, we propose to realize a light-weight, battery-free, 3D motion tracking solution by leveraging a spin...
Video streaming is one of the most popular Internet applications that makes up a large amount of Internet traffic. A fundamental mechanism in video streaming is adaptive bitrate (ABR) selection which decides the proper compression level for each chunk of a video to optimize the users' quality of experience (QoE). The existing ABR algorithms require...
Nowadays, to realize the intelligent manufacturing in Industrial Internet of Things (IIoT) scenarios, novel approaches in computer vision are in great demand to tackle the new challenges in IIoT environment. These approaches, which we call
Industrial Vision
, are expected to offer customized solutions for intelligent manufacturing in an accurate,...
The usage of live streaming services has led to a substantial increase in live video traffic. However, the perceived quality of experience of users is frequently limited by variations in the upstream bandwidth of streamers. To address this issue, several adaptive bitrate (ABR) algorithms have been developed to mitigate bandwidth variations. Neverth...
Over the last decade, the mobile crowdsourcing has become a paradigm to conduct the manual annotation and further analytics by recruited workers, with their rewards depending on the result quality. Existing dispatchers cannot precisely capture the resource-quality trade-off for video analytics, because the configurations supported by recruited work...
Speech is a natural communication way between people and a good way for human-computer interaction. However, speech with audible voices often faces the following problems, e.g., being affected by surrounding noises, breaking the quiet environment, leaking privacy, etc. Therefore, silent speech was proposed, especially lip reading, which aims to rec...
As an essential part of modern human-computer interaction, gesture recognition is widely used in industry, society, medical care and entertainment. Existing gesture recognition solutions either rely on computer vision, which suffers from the light condition, or use inertial sensors, which are limited by the battery life. In this paper, we propose a...
Anomaly detection on multivariate time series (MTS) is an important research topic in data mining, which has a wide range of applications in information technology, financial management, manufacturing system, etc. However, the state-of-the-art unsupervised deep learning models for MTS anomaly detection are vulnerable to noise and have poor performa...
With the rapid development of wireless technology and the edge computing applications, an increasing number of 4G/5G infrastructure are densely deployed to meet the booming cellular traffic demands. Monitoring and forecasting urban cellular traffic is fundamental for urban planning, network resources allocation, traffic engineering, etc. In this pa...
Inferences easily incur computation overload at the edge of the network, since they often consume plenty of resources and are often implemented by using deep neural networks (DNNs). Traditional approach via offloading those inference tasks to remote cloud is unsuitable, since the round-trip time is often a burden. As a result, offloading by using n...
Gait rehabilitation is a common method of postoperative recovery after the user sustains an injury or disability. However, traditional gait rehabilitations are usually performed under the supervision of rehabilitation specialists, which implies that the patients cannot receive adequate gait assessment anytime and anywhere. In this article, we propo...
Nowadays, detecting and evaluating the internal structure of packages becomes a crucial task for logistics systems to guarantee reliability and security. However, prior solutions such as X-ray diffraction and WiFi-based detection are not suitable for this purpose. X-ray-based methods usually require manual analysis or image processing algorithms wi...
Many journaling file systems currently use non-volatile memory-express (NVMe) solid-state drives (SSDs) as external journal devices to improve the input and output (I/O) performance. However, when facing microwrite workloads, which are typical of many applications, they suffer from severe I/O fluctuations and the NVMe SSD utilization is extremely l...
With the rapid development of machine-to-machine (M2M) mobile smart terminals, M2M services can be used in a wide range of industries, including such as tele-medicine, remote meter reading and public security. Since different industries and enterprise users have different requirements for M2M specific applications, the security identity authenticat...
Mobile cloud gaming (MCG), which is proposed to deliver high-quality gaming experience to users anywhere and anytime, suffers from tremendous wide-area traffic and long network delays. In order to shorten the delays and provide the gaming services in close proximity to end users, the mobile edge computing (MEC) is envisioned as a promising approach...
Multivariate time series (MTS) clustering is an important technique for discovering co-evolving patterns and interpreting group characteristics in many areas including economics, bioinformatics, data science, etc. Although time series clustering has been widely studied in the past decades, no enough attention has been paid to capture time-varying c...
Pen-based handwriting has become one of the major human-computer interaction methods. Traditional approaches either require writing on the specific supporting device like the touch screen, or limit the way of using the pen to pure rotation or translation. In this paper, we propose Handwriting-Assistant, to capture the free handwriting of ordinary p...
The unprecedented success of speech recognition methods has stimulated the wide usage of intelligent audio systems, which provides new attack opportunities for stealing the user privacy through eavesdropping on the loudspeakers. Effective eavesdropping methods employ a high-speed camera, relying on LOS to measure object vibrations, or utilize WiFi...
Performing federated learning continuously in edge networks while training data are dynamically and unpredictably streamed to the devices faces critical challenges, including the global model convergence, the long-term resource budget, and the uncertain stochastic network and execution environment. We formulate an integer program to capture all the...
In the multi-access edge computing environment, app vendors deploy their services and applications at the network edges, and edge users offload their computation tasks to edge servers. We study the user-perceived delay-aware service placement and user-allocation problem in edge environment. We model the MEC-enabled network, where the user-perceived...
The emergence of edge computing has enabled mobile Augmented Reality (AR) on edge servers. We notice that the video configurations, i.e., frames per second (fps) and resolution, significantly affect the key metrics such as detection accuracy, data transmission latency and energy consumption in real AR application. Besides the time-varying bandwidth...
Mobile and wearable devices have become more and more popular. However, the tiny touch screen leads to inefficient interaction with these devices, especially for text input. In this article, we propose
DynaKey
, which allows people to type on a virtual keyboard printed on a piece of article or drawn on a desk, for inputting text into a head-mount...
In the federated learning paradigm, multiple mobile clients train their local models independently based on the datasets generated by edge devices, and the server aggregates the model parameters received from multiple clients to form a global model. Conventional methods aggregate gradient parameters and statistical parameters without distinction, w...
Major cities worldwide have millions of cameras deployed for surveillance, business intelligence, traffic control, crime prevention, etc. Real-time analytics on video data demands intensive computation resources and high energy consumption. Traditional cloud-based video analytics relies on large centralized clusters to ingest video streams. With ed...
Mobile Edge Computing (MEC) has become an attractive solution to enhance the computing and storage capacity of mobile devices by leveraging available resources on edge nodes. In MEC, the arrivals of tasks are highly dynamic and are hard to predict precisely. It is of great importance yet very challenging to assign the tasks to edge nodes with guara...
System logs produced by modern computer systems are valuable resources for detecting anomalies, debugging performance issues, and recovering application failures. With the increasing scale and complexity of the log data, manual log inspection is infeasible and man-power expensive. In this paper, we proposed LogAttn, an autoencoder model that combin...
Nowadays, authentication systems are usually required to provide continuous, contactless, and non-intrusive services. In this paper, we propose
RF-Badge
, a vital sign-based authentication scheme on human subjects to meet the above requirements by using RFID technology. We consider two biometric features with individual diversity to characterize...
As an important indicator of the infusion monitoring for clinical treatment, the drip rate is expected to be monitored in an accurate and real-time manner. However, state-of-the-art drip rate monitoring schemes either suffer from high maintenance or incur high hardware cost. In this paper, we propose DropMonitor, an RFID-based approach to perform t...
We consider the multiuser detection (MUD) problem, i.e., how to separate and decode colliding data streams, in the uplink of massive Machine Type Communications (mMTC) at millimeter wave (mmWave). Operating on factor-graphs by passing messages, the sum-product algorithm and its variants are widely applied in many other scenarios. However, in this p...
Congestion control is a fundamental mechanism for TCP protocol, which has been extensively studied in the past three decades. However, our experimental evaluations show that the state-of-art congestion control algorithms such as Cubic and BBR are far from optimal: they have unresolved issues such as insufficient usage of available bandwidth, inadap...
Efficiently analyzing geo-distributed datasets is emerging as a major demand in a cloud-edge system. Since the datasets are often generated in closer proximity to end users, traditional works mainly focus on offloading proper tasks from those hotspot edges to the datacenter to decrease the overall completion time of submitted jobs in a one-shot man...
A graph stream is a kind of dynamic graph representation that consists of a consecutive sequence of edges where each edge is represented by two endpoints and a weight. Graph stream is widely applied in many application scenarios to describe the relationships in social networks, communication networks, academic collaboration networks, etc. Graph ske...
In traditional device-to-device (D2D) communication based on wireless channel, identity authentication and spontaneous secure connections between smart devices are essential requirements. In this paper, we propose an imitation-resistant secure pairing framework including authentication and key generation for smart devices, by shaking these devices...
Instead of relying on remote clouds, today’s Augmented Reality (AR) applications usually send videos to nearby edge servers for analysis (such as objection detection) so as to optimize the user’s quality of experience (QoE), which is often determined by not only detection latency but also detection accuracy, playback fluency, etc. Therefore, many s...
Human activity recognition (HAR) based on sensing data from wearable and mobile devices has become an active research area in ubiquitous computing, and it envisions a wide range of application scenarios in mobile social networking, environmental context sensing, health and well-being monitoring, etc. However, activity recognition based on manually...
Predicting future performance curve and mining the top-K influential KPIs are two important tasks for Database Management System (DBMS) operations. In this paper, we propose a multi-task sequence learning approach to address the two tasks in a uniform framework. The proposed approach adopts a Long Short-Term Memory (LSTM) based deep neural network...
The booming of Convolutional Neural Networks (CNNs) has empowered lots of computer-vision applications. Due to its stringent requirement for computing resources, substantial research has been conducted on how to optimize its deployment and execution on resource-constrained devices. However, previous works have several weaknesses, including limited...
Multipath data transmission techniques have been proposed to aggregate the resource of multiple heterogeneous access networks to enhance the robustness and throughput of multi-homed mobile devices.The Multipath TCP (MPTCP) protocol has been standardized by the IETF as an extension of conventional TCP, which enables establishing several subflows ove...
Due to the widespread use of mobile devices, it is essential to authenticate users on mobile devices to prevent sensitive information leakage. In this paper, we propose TouchID, which combinedly uses the touch sensor and the inertial sensor for gesture analysis, to provide a touch gesture based user authentication scheme. Specifically, TouchID util...
Katz centrality is a fundamental concept to measure the influence of a vertex in a social network. However, existing approaches to calculating Katz centrality in a large-scale network are unpractical and computationally expensive. In this article, we propose a novel method to estimate Katz centrality based on graph sampling techniques, which object...
The popularity of smartphones has witnessed the rapid growth of the number of mobile applications. Nowadays, there are millions of applications available, and at the same time, many applications are already installed on people’s smartphones. Installing numerous apps will cause some troubles in finding the specific apps promptly. Hence it is necessa...
The emergence of Mobile Edge Computing (MEC) alleviates the large transmission latency resulting from the traditional cloud computing. For the compute-intensive requests such as video analysis, mobile users prefer to obtain a desired quality of experience (QoE) with neglected latency and reduced energy consumption. The popularity of smart devices a...
Among all the road accidents, speeding is the most deadly factor. To reduce speeding, it is essential to devise efficient schemes for ubiquitous speed monitoring. Traditional approaches either suffers from using special equipment or special deployment. In this paper, we propose SpeedTalker, a mobile phone-based approach to perform speed detection o...
Assessing individual's personality traits has important implications in psychology, sociology, and economics. Conventional personality measurement methods were questionnaire-based, which are time-consuming and manpower-expensive. With the pervasive deployment of mobile communication applications, smartphone usage data was found to relate to people'...
Nowadays smartphone users have installed dozens or even hundreds of APPs on their phones. Predicting APP usage not only helps the mobile phone system to speed up APP launching but also reduces the time for users to search them. In this paper, we focus on a novel session-based APP usage prediction problem that tends to predict a sequence of APPs to...
In this paper, we propose RF-Dial to realize a light-weight, battery-free and functional 2D human-computer interaction solution via RFID. What RF-Dial shines is that it can easily turn an ordinary object, e.g., a board eraser, into an intelligent interaction device. By deploying a tag array on the side face of the object together with a dipole tag...
Mobile Augmented Reality (MAR) applications usually contain computation-intensive tasks which far outstrip the capability of mobile devices. One way to overcome this is offloading computation-intensive MAR tasks to remote clouds. However, the wide area network delay is hard to reduce. Thanks to edge computing, we can offload MAR tasks to nearby ser...
Both network function virtualization (NFV) and edge computing (EC), especially the latter, are attracting more and more attention in recent years. A growing number of network service providers are migrating their services from the cloud to the edge for better QoS services, while the recent researches on NFV also concentrate on deploying NFV service...
Emotion detection in online social networks (OSNs) can benefit kinds of applications, such as personalized advertisement services, recommendation systems, etc. Conventionally, emotion analysis mainly focuses on the sentence level polarity prediction or single emotion label classification, however, ignoring the fact that emotions might coexist from...
Due to its limited error correction capability, 802.11 can hardly work in scenarios where the channel fading or interference is very severe, such as industrial internet of things. In this paper, we propose Rateless802.11, a cross-layer scheme which can work as a middleware over common commodity 802.11 devices, that extends the applicability of 802....