Hong-Linh Truong

Hong-Linh Truong
Aalto University · Department of Computer Science

PhD

About

298
Publications
46,177
Reads
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4,726
Citations
Introduction
I am an associate professor at Aalto University. I am also a Priv.-Doz (adjunct associate professor) at TU Wien. I lead a team working on software and service systems in cloud computing, big data, IoT, and edge computing. More information are available at - https://users.aalto.fi/~truongh4/ - http://rdsea.github.io
Additional affiliations
February 2019 - present
TU Wien
Position
  • Professor (Associate)
October 2018 - present
Aalto University
Position
  • Professor (Associate)
September 2017 - September 2017
University of Southern California
Position
  • Visiting Scholar

Publications

Publications (298)
Conference Paper
Sharing real-time data originating from connected devices is crucial to real-world intelligent Internet of Things (IoT) applications, ie, based on artificial intelligence/machine learning (AI/ML). Such IoT data sharing involves multiple parties for different purposes and is usually based on data contracts that might depend on the dynamic change of...
Preprint
Full-text available
This paper presents a novel framework to enhance programmability of the IoT-edge-cloud continuum through the concept of Accelerators, runtime components, techniques, and languages that can be used to optimize resources and services. The framework accommodates rapid change through software composition and elastic adaptation. In particular, elasticit...
Preprint
Full-text available
The origin of the quiet Sun magnetism is under debate. Investigating the solar cycle variation observationally in more detail can give us clues about how to resolve the controversies. We investigate the solar cycle variation of the most magnetically quiet regions and their surface gravity oscillation ($f$-) mode integrated energy ($E_f$). We use 12...
Article
Full-text available
The maturity of machine learning (ML) development and the decreasing deployment cost of capable edge devices have proliferated the development and deployment of edge ML solutions for critical IoT-based business applications. The combination of edge computing and ML not only addresses the development cost barrier, but also solves the obstacles due t...
Article
Full-text available
The fast growth in the amount of connected devices with computing capabilities in the past years has enabled the emergence of a new computing layer at the Edge. Despite being resource-constrained if compared with cloud servers, they offer lower latencies than those achievable by Cloud computing. The combination of both Cloud and Edge computing para...
Conference Paper
Full-text available
Identifying mobile apps based on network traffic has multiple benefits for security and network management. However, it is a challenging task due to multiple reasons. First, network traffic is encrypted using an end-to-end encryption mechanism to protect data privacy. Second, user behavior changes dynamically when using different functionalities of...
Article
COVID-19 has turned service-based business continuity into a hot issue, due to the survival of enterprises under long-tailed changes of business caused by various abnormal socioeconomic events and disruptions. We analyze how current techniques enable small and medium enterprises to be resilient and elastic. From observations of service disruptions...
Preprint
Full-text available
The maturity of machine learning (ML) development and the decreasing deployment cost of capable edge devices have proliferated the development and deployment of edge ML services in developing countries for critical IoT-based business applications. The combination of edge computing and ML not only addresses the development cost barrier but also solv...
Article
Recent years have seen the rapid development and integration of the Internet of Things (IoT) and cloud computing. The market is providing various consumer-oriented smart IoT devices; the mainstream cloud service providers are building their software stacks to support IoT services. With this emerging trend even growing, the security of such smart Io...
Chapter
As blockchain becomes an essential part of many software systems in the edge and cloud, the developer starts to treat blockchain features like commodity software components that can be integrated into edge and cloud software systems. For the developer it is quite challenging to determine, customize, and evaluate suitable blockchain features for sof...
Conference Paper
Full-text available
Using machine learning (ML) services, both service customers and providers need to monitor complex contractual constraints of ML service that are strongly related to ML models and data. Therefore, establishing and monitoring comprehensive ML contracts are crucial in ML serving. This paper demonstrates a set of features and utilities of the QoA4ML f...
Article
Full-text available
Optimizing quality trade-offs in an end-to-end big data science process is challenging, as not only do we need to deal with different types of software components, but also the domain knowledge has to be incorporated along the process. This paper focuses on methods for tackling quality trade-offs in a common data science process for classifying Bui...
Article
Realizing the potential of edge computing and networks connecting the edge and the cloud, researchers from academia and industries have increasingly developed techniques and tools for edge infrastructures and applications. This paper focuses on supporting complex edge application interactions, which span different layers and subsystems in edge-clou...
Preprint
Important service-level constraints in machine learning (ML) services must be communicated and agreed among relevant stakeholders. Due to the lack of studies and support, it is unclear which and how ML-specific attributes and constraints should be specified and assured in service contracts for ML services. This paper examines service contracts in t...
Preprint
Full-text available
We have witnessed various degrees of disruption to service-based businesses in the society, caused by the Coronavirus pandemic (COVID-19). This paper studies service-oriented enterprises from the perspective of resilience and elasticity, aiming at uncovering the issues in current service development, maintenance and operation in pandemic ages. We p...
Preprint
Full-text available
Concerns of robustness, reliability, resilience and elasticity in machine learning (ML) systems are important and they must be considered in trade-off with efficiency factors. However, they need to be supported and optimized in an end-to-end manner, not just for ML models. In this paper we present an approach to architectural design and engineering...
Preprint
Full-text available
More widespread adoption requires swarms of robots to be more flexible for real-world applications. Multiple challenges remain in complex scenarios where a large amount of data needs to be processed in real-time and high degrees of situational awareness are required. The options in this direction are limited in existing robotic swarms, mostly homog...
Preprint
Optimizing quality trade-offs in an end-to-end big data science process is challenging, as not only we need to deal with different types of software components but also the domain knowledge has to be incorporated along the process. We focus on methods for tackling quality trade-offs in a common data science process for classifying Building Informat...
Article
Full-text available
The increasing availability of edge and IoT infrastructure-as-a-service allows us to develop lightweight IoT components and deploy them into edge/IoT infrastructures, enabling edge analytics and controls. This paper introduces the development of service contracts for IoT microservices from DevOps perspectives. We analyze stakeholders and present ou...
Chapter
Internet of Things (IoT) generate huge amount of data in real time. Utilization of such data requires appropriate data storage, analytics and computation techniques so that valuable information can be extracted and immediate actions could be taken place. In this paper, we present real time traffic applications, typical IoT-enabled big data applicat...
Chapter
In the IoT era, a massive number of smart sensors produce a variety of data at unprecedented scale. Edge storage has limited capacities posing a crucial challenge for maintaining only the most relevant IoT data for edge analytics. Currently, this problem is addressed mostly considering traditional cloud-based database perspectives, including storag...
Preprint
Full-text available
Realizing the potential of edge computing and fog networks connecting the edge and the cloud, researchers and industries have increasingly developed techniques and tools for testing edge infrastructures and applications. Simulating edge applications and systems plays a crucial role because not everyone can have access to a real-world deployment of...
Preprint
Full-text available
Incorporating blockchain features into edge services is on the rise. However, there is a lack of frameworks for sharing and recommending knowledge about blockchain software artefacts and deployments for edge services development. In this paper, we present various types of information linking blockchain performance with service deployments at differ...
Preprint
Full-text available
In the IoT domain, a massive number of smart sensors, devices and equipment produce a variety of data at unprecedented scale. To analyze these produced data for timely decision making, data ana-lytics at the network edge is a promising solution. Nevertheless, unlike scalable cloud-based storage services, edge storage has limited capacities posing a...
Preprint
A mature Business process is one of the core competencies of an enterprise. Nowadays, there are many process models which are owned by enterprises need to be integrated into new environments, such as state sharing. The new environment contains new demands that are often distributed according to the long tail effect which means it is very expensive...
Preprint
Full-text available
When provisioning "resources" for applications across edge and cloud infrastructures, most work deals with infrastructural containers and virtual machines (VMs) as resources. Such infrastructural resources can be acquired and scaled in an elastic manner for dynamic requirements from the applications. However, this type of low-level infrastructural...
Preprint
Full-text available
As blockchain becomes an essential part of many software systems in the edge and cloud, the developer starts to treat blockchain features like commodity software components that can be integrated into edge and cloud software systems. For the developer it is quite challenging in selecting, cus-tomizing and testing suitable blockchain features for so...
Article
Full-text available
Abstract Smart manufacturing is strongly correlated with the digitization of all manufacturing activities. This increases the amount of data available to drive productivity and profit through data-driven decision making programs. The goal of this article is to assist data engineers in designing big data analysis pipelines for manufacturing process...
Conference Paper
Full-text available
With the rise of Internet of Things, end-users expect to obtain data from well-connected smart devices and stations through data services being provisioned in distributed architectures. Such services could be aggregated in a number of smart ways to provide the end-users and third-party applications with sophisticated data (e.g., weather data couple...
Conference Paper
Full-text available
Dealing with interoperability in the IoT domain is a complex matter that requires various techniques for tackling data, protocol and middleware interoperability. We cannot solve IoT interoperability problems by just developing (new) software components and (semantic) data models. In this tutorial, we will present interoperability techniques for com...
Conference Paper
Full-text available
In the context of edge computing, IoT-as-a-Service (IoTaaS) with IoT data hubs and execution services allow IoT tenant applications (apps) to be executed next to IoT devices, enabling edge analytics and controls. However, this brings up new security challenges on controlling tenant apps in IoTaaS, whilst the great potential of IoTaaS can only be re...
Conference Paper
Full-text available
Within an IoT Cloud application, various subsystems and layers of IoT, edge and cloud infrastructures are involved and we need to make sure that the involved components and data are interoperable w.r.t. data models, protocols and access policies. Such requirements must be addressed by IoT Cloud applications and platforms. Furthermore, such requirem...
Preprint
Smart manufacturing is strongly correlated with the digitization of all manufacturing activities. This increases the amount of data available to drive productivity and profit through data-driven decision making programs. The goal of this article is to assist data engineers in designing big data analysis pipelines for manufacturing process data. Thu...
Preprint
Full-text available
In the context of edge computing, IoT-as-a-Service (IoTaaS) with IoT data hubs and execution services allow IoT tenant applications (apps) to be executed next to IoT devices, enabling edge analytics and controls. However, this brings up new security challenges on controlling tenant apps in IoTaaS, whilst the great potential of IoTaaS can only be re...
Presentation
Full-text available
presentation on mobile edge cloud analytics at IEEE Cloud 2018
Preprint
Full-text available
Within an IoT Cloud application, various subsystems and layers of IoT, edge and cloud infrastructures are involved and we need to make sure that the involved components and data are interoperable w.r.t. data models, protocols and access policies. Such requirements must be addressed by IoT Cloud applications and platforms. Furthermore, such requirem...
Preprint
Full-text available
For predictive maintenance of equipment with Industrial Internet of Things (IIoT) technologies, complex IoT Cloud systems provide strong monitoring and data analysis capabilities for detecting and predicting status of equipment. We need to support complex interactions among different software components and human activities to provide an integrated...
Conference Paper
Full-text available
Interoperability for IoT is a challenging problem because it requires us to tackle (i) cross-system interoperability issues at the IoT platform sides as well as relevant network functions and clouds in the edge systems and data centers and (ii) cross-layer interoperability, e.g., w.r.t. data formats, communication protocols, data delivery mechanism...
Presentation
Full-text available
presentation at Globe-IoT@IC2E
Preprint
Full-text available
To enhance the competitiveness, companies need continuously improving the capability of timely decision making in collaboration with different enterprises through the whole supply chain, instantly responding to the rapid changing environments. Consequently the challenges are how to enable processes to acquire and react with real-time information fr...
Preprint
Full-text available
Emerging edge/fog computing models have fostered new types of applications whose software components and dependent services are provisioned across distributed edge and cloud infrastructures. The design of edge cloud systems is complex, thus it is important to understand suitable deployment models and test them. Since edge cloud computing and its de...
Preprint
Full-text available
The increasing availability of IoT infrastructure-as-a-service not only allows us to easily develop IoT components and deploy them into IoT infrastructures, enabling edge analytics and controls, but also brings challenges for ensuring service contracts between the infrastructures providers and owners of IoT components using the infrastructures. Due...
Article
Full-text available
Many advances have been introduced recently for service-oriented computing and applications (SOCA). The Internet of Things (IoT) has been pervasive in various application domains. Fog/Edge computing models have shown techniques that move computational and analytics capabilities from centralized data centers where most enterprise business services h...
Conference Paper
Full-text available
LoRaWAN is a promising network solution for various application domains, especially in developing countries. While its network architecture is highly distributed, the network architecture aims at aggregating data into a centralized location, mainly the cloud-based data center. With such an architecture, we can bring data from distributed sensing so...
Chapter
With the emerging IoT and Cloud-based networked systems that rely heavily on virtualization technologies, elasticity becomes a dominant system engineering attribute for providing QoS-aware services to their users. Although the concept of elasticity can introduce significant QoS and cost benefits, its implementation in real systems is full of challe...
Preprint
Full-text available
Systems for big Internet of Things (IoT) data an-alytics are extremely complex. Different software components at different software stacks from different infrastructures and providers are involved in handling different types of data. Various types of incidents may occur during execution of such systems due to problems occurring in software stacks,...
Conference Paper
Modern Cyber-Physical Systems (CPS) and Internet of Things (IoT) systems consist of both loosely and tightly interactions among various resources in IoT networks, edge servers and cloud data centers. These elements are being built atop virtualization layers and deployed in both edge and cloud infrastructures. They also deal with a lot of data throu...
Presentation
Full-text available
Today’s crucial applications in, e.g., smart cities, logistics, health-care and manufacturing rely on complex Internet of Things (IoT) and cloud system infrastructures. Such infrastructures consist of IoT devices, distributed storage, processing, and management services that need to elastic, i.e., adaptable to evolving physical and execution enviro...
Presentation
Full-text available
This presentation is about reporting experiences and challenges on combining model-driven engineering (MDE) methodologies with elastic execution models to design and test the uncertainty of real-world CPS.
Presentation
Full-text available
Monitoring, Managing and Testing Resource slices of IoT, Network functions and Cloud resources for edge and cloud computing
Conference Paper
Full-text available
Today’s cyber-physical systems (CPS) span IoT and cloud-based datacenter infrastructures, which are highly heterogeneous with various types of uncertainty. Thus, testing uncertainties in these CPS is a challenging and multidisciplinary activity. We need several tools for modeling, deployment, control, and analytics to test and evaluate uncertaintie...
Conference Paper
Full-text available
Internet of Things (IoT) services are increasingly deployed at the edge to access and control Things. The execution of such services needs to be monitored to provide information for security, service contract, and system operation management. Although different techniques have been proposed for deploying and executing IoT services in IoT gateways a...
Article
Hybrid Diversity-aware Collective Adaptive Systems (HDACAS) are a new generation of socio-technical systems where both human and machine peers collectively participate in complex cognitive and physical tasks. These systems are characterized by the fundamental properties of hybridity and collectiveness, hiding from users the complexities associated...