A5076592473- Cloud Computing and Resource Management
- IoT and Edge/Fog Computing
- Caching and Content Delivery
- Data Management and Algorithms
- Distributed and Parallel Computing Systems
- Maritime Navigation and Safety
- Advanced Data Storage Technologies
- Time Series Analysis and Forecasting
- Advanced Database Systems and Queries
- Software System Performance and Reliability
- Computational Drug Discovery Methods
- Blockchain Technology Applications and Security
- Cloud Data Security Solutions
- Scientific Computing and Data Management
- Peer-to-Peer Network Technologies
- Human Mobility and Location-Based Analysis
- Geographic Information Systems Studies
- Radiomics and Machine Learning in Medical Imaging
- Bioinformatics and Genomic Networks
- Software-Defined Networks and 5G
- Augmented Reality Applications
- Maritime Transport Emissions and Efficiency
- Protein Structure and Dynamics
- Soft tissue tumor case studies
- Anomaly Detection Techniques and Applications
Harokopio University of Athens
2016-2024
National Technical University of Athens
2024
National and Kapodistrian University of Athens
2019
Eastern Health
2015-2016
Centre for Research and Technology Hellas
2016
RWTH Aachen University
2009
Westfälische Hochschule
2008
The COVID-19 pandemic in 2020 has highlighted the need to pull all available resources towards mitigation of devastating effects such "Black Swan" events. Towards that end, we investigated option employ technology order assist diagnosis patients infected by virus. As such, several state-of-the-art pre-trained convolutional neural networks were evaluated as their ability detect from chest X-Ray images. A dataset was created a mix publicly X-ray images with confirmed disease, common bacterial...
A bstract The COVID-19 pandemic in 2020 has highlighted the need to pull all available resources towards mitigation of devastating effects such “Black Swan” events. Towards that end, we investigated option employ technology order assist diagnosis patients infected by virus. As such, several state-of-the-art pre-trained convolutional neural networks were evaluated as their ability detect from chest X-Ray images. dataset was created a mix publicly X-ray images with confirmed disease, common...
In recent years, the emergence of XR (eXtended Reality) applications, including Holography, Augmented, Virtual and Mixed Reality, has resulted in creation rather demanding requirements for Quality Experience (QoE) Service (QoS). order to cope with such as ultra-low latency increased bandwidth, it is paramount importance leverage certain technological paradigms. The purpose this paper identify these QoE QoS then provide an extensive survey on technologies that are able facilitate Cloud-based...
Cloud-native services face unique cybersecurity challenges due to their distributed infrastructure. They are susceptible various threats like malware, DDoS attacks, and Man-in-the-Middle (MITM) attacks. Additionally, these often process sensitive data that must be protected from unauthorized access. On top of that, the dynamic scalable nature cloud-native makes it difficult maintain consistent security, as deploying new instances infrastructure introduces vulnerabilities. To address...
The emergence of Multiplayer Mobile Gaming (MMG) applications is intertwined with a plethora Quality Service and Experience requirements. Resource usage prediction can provide valuable insights into the corresponding orchestration management process in form several proactive functionalities resource scaling, service migration, task offloading scheduling. These processes are crucial Cloud Edge environments exploited by MMG applications. Thus, producing accurate predictions concerning these...
Abstract Several modern day problems need to deal with large amounts of spatio-temporal data. As such, in order meet the application requirements, more and systems are adapting specificities those The most prominent case is perhaps data storage systems, that have developed a number functionalities efficiently support operations. This work motivated by question which better suited address needs industrial applications. In particular, conducted, set identify efficient store system terms...
Due to the vast amount of available tracking sensors in recent years, high-frequency and high-volume streams data are generated every day. The maritime domain is no different as all larger vessels obliged be equipped with a vessel system that transmits their location periodically. Consequently, automated methodologies able extract meaningful information from high-frequency, large volumes need developed. automatic identification mobility patterns such real time utmost importance since it can...
Traditional Relational Database Management Systems are continuously being replaced by NoSQL data stores as a result of the growing demand for big applications. The emergence large number implementations such like systems is contributing indicator. This paper deals with analysis some key design characteristics and uses these their characterization based on capabilities. Furthermore, it highlights relationship between cloud infrastructures explains impact that existence one has to other.
Today's industry is flooded with tracking data originating from vessels across the globe that transmit their position at frequent intervals. These voluminous and high-speed streams of has led researchers to develop novel ways compress them in order speed-up processing without losing valuable information. To this end, several algorithms have been developed try vessel compromising spatio-temporal kinematic features. In paper, we present a wide range well-known trajectory compression evaluate...
In the field of edge-cloud computing environments, there is a continuous quest for new and simplified methods to automate deployment runtime adaptation application lifecycle changes. Towards that end, cloud providers promote their own service description languages describe processes, whereas developers opt cloud-agnostic open standards capable modeling applications. However, not all are able capture concepts relate underlying environment changes in lifecycle. our formal approach encapsulate...
Abstract During the last few years volumes of data that synthesize trajectories have expanded to unparalleled quantities. This growth is challenging traditional trajectory analysis approaches and solutions are sought in other domains. In this work, we focus on compression techniques with intention minimize size data, while, at same time, minimizing impact methods. To extent, evaluate five lossy algorithms: Douglas-Peucker (DP), Time Ratio (TR), Speed Based (SP), (TR_SP) (SP_TR). The...
The very fabric of Edge Computing is intertwined with the necessity to be able orchestrate and manage a huge number heterogeneous computational resources. On top that, rather demanding Quality Service (QoS) requirements Internet Things (IoT) applications that run on these resources, dictate it essential establish robust Fault Tolerance mechanisms. These mechanisms should guarantee will upheld regardless any potential changes in task production rate. To end, we suggest an Automated Pipeline...
<ns4:p>Microservices have taken the world of software development by storm. Application developers are struggling to understand new concepts and make transition so-called ``monolithic'' application approach microservices. This paper touches upon this delicate issue, providing a more concrete view developers' concerns together with recent responses these concerns. The objective is place concept microservices in most up-to-date context shed some light challenges that puzzle while they attempt...
Due to the continuous development of Internet Things (IoT), volume data these devices generate are expected grow dramatically in future. As a result, managing and processing such massive amounts at edge becomes vital issue. Edge computing moves computation closer client enabling latency- bandwidth-sensitive applications, that would not be feasible using cloud remote alone. Nevertheless, implementing an efficient edge-enabled storage system is challenging due distributed heterogeneous nature...
<h2>Abstract</h2> Platforms that utilize resources spanning from the Edge and Cloud continuum demand a monitoring system capable of reporting diverse metrics for various applications on heterogeneous resources. EdgeCloud Mon guarantees consistent application components, whether deployed or resources, while also addressing multitude computing power variations within continuum. Consequently, this mechanism is lightweight enough to operate efficiently yet robust deliver accurate results both
The paper introduces the CHARITY framework, a novel framework which aspires to leverage benefits of intelligent, network continuum autonomous orchestration cloud, edge, and resources, create symbiotic relationship between low high latency infrastructures. These infrastructures will facilitate needs emerging applications such as holographic events, virtual reality training, mixed entertainment. relies on different enablers technologies related cloud edge for offering suitable environment in...
Edge computing constitutes a promising paradigm of managing and processing the massive amounts data generated by Internet Things (IoT) devices. Data computation are moved closer to client, thus enabling latency- bandwidth-sensitive applications. However, distributed heterogeneous nature edge as well its limited resource capabilities pose several challenges in implementing or choosing an efficient edge-enabled storage system. Therefore, it is imperative for research community contribute...
This paper introduces the GreenKube framework, which aims to reduce energy consumption while meeting Quality of Service (QoS) requirements through use various AI methodologies such as deep learning time-series forecasting, reinforcement learning, and graph neural networks. The also explores limitations contemporary container orchestration frameworks, including Kubernetes, describes how progress beyond them. Additionally, presents a prototype framework that was evaluated in an extensive...
Nowadays, the increasing number of moving objects tracking sensors, results in continuous flow high-frequency and high-volume data streams. This phenomenon can especially be observed maritime domain since most vessels worldwide are now transmitting their positions periodically. Therefore, there is a strong necessity to extract meaningful information identify mobility patterns from such an automated fashion, eliminating need for experts' input. To this end, novel approach presented paper,...
Due to the advent of new mobile devices and tracking sensors in recent years, huge amounts data are being produced every day. Therefore, novel methodologies need emerge that dive through this vast sea information generate insights meaningful information. To end, researchers have developed several trajectory classification algorithms over years able annotate data. Similarly, we propose a software exploits image representations trajectories, called TraClets, order classify trajectories an...
As Edge and Cloud platforms increasingly become the basis for hosting applications, monitoring systems need to be able monitor both hosts deployed applications. Ensuring seamless of is most crucial factor, regardless whether they are virtual machines, Raspberry Pis, or even typical personal computers. The application orchestration process could benefit greatly from systems, as serve main source characterizing reporting metrics related users platforms. This paper introduces a Prometheus-based...
Traditional multi-path routing methods distribute evenly traffic across multiple paths in a network, which can lead to inefficient use of resources if some are significantly longer or less reliable than others. Weighted addresses this issue by introducing weights appropriately the available based on their state. This paper proposes novel approach weighted using multi-agent actor-critic framework, manner that is aligned with need keep up Quality Service requirements contemporary,...