Docker containers are the lightweight-virtualization technology prevailing today for the provision of microservices. This work raises and discusses two main challenges in Docker containers’ scheduling in cloud-fog-internet of things (IoT) netwo...
In recent years, there have been a number of new application architectures developed (examples include microservices and containerisation) that introduce significant security challenges for inter-service communication. Whereas internal calls made wit...
This study proposes an integrated approach to developing a Microservice, Cloud Computing, and Software as a Service (SaaS)-based Real-Time Storm Sewer Simulation System (MBSS). The MBSS combined the Storm Water Management Model (SWMM) microservice ru...
DevOps methodology and tools, which provide standardized ways for continuous integration (CI) and continuous deployment (CD), are invaluable for efficient software development. Current DevOps solutions, however, lack a useful functionality: they do n...
This article proposes a new concept of microservice-based architecture for the future of distributed systems. This architecture is a bridge between Internet-of-Things (IoT) devices and applications that are used to monitor cattle health in real time...
Latency and connectivity problems in traditional cloud computing platforms regularly hinder the use of Internet of Things (IoT) systems for smart agriculture, especially in remote rural areas. Network quality is an essential element of centralized ar...
Professional live video production has traditionally been limited by proprietary hardware mixers and monolithic desktop applications, which impose prohibitive costs and restrict scalable, command-line-based implementation for remote integration (REMI...
In this paper, we examine the relevant vulnerabilities and security controls for ensuring the security of applications built on microservice architectures. Zero Trust security principles are used to conceptualize and implement a secure ecosystem usin...
Microservices, Continuous Integration and Delivery, Docker, DevOps, Infrastructure as Code—these are the current trends and buzzwords in the technological world of 2020. A popular tool which can facilitate the deployment and maintenance of microservi...
With the advent of microservice-based software architectures, an increasing number of modern cloud environments and enterprises use operating system level virtualization, which is often referred to as container infrastructures. Docker Swarm is one of...
Cloud-native computing enhances the deployment of microservice architecture (MSA) applications by improving scalability and resilience, particularly in Beyond 5G (B5G) environments such as Sixth-Generation (6G) networks. This is achieved through the...
The use of collaborative tools has notably increased recently. It is common to see distinct users that need to work simultaneously on shared documents. In most cases, large companies provide tools whose implementations have been a very complicated an...
Most enterprise customers now choose to divide a large monolithic service into large numbers of loosely-coupled, specialized microservices, which can be developed and deployed separately. Docker, as a light-weight virtualization technology, has been...
Traditional hypervisor-assisted virtualization is a leading virtualization technology in data centers, providing cost savings (CapEx and OpEx), high availability, and disaster recovery. However, its inherent overhead may hinder performance and seems...
The growth of IoT devices has generated an increasing demand for effective, agile, and scalable deployment frameworks. Traditional IoT architectures are generally strained by interoperability, real-time responsiveness, and resource optimization due t...
The demand for deep learning frameworks capable of running in edge computing environments is rapidly increasing due to the exponential growth of data volume and the need for real-time processing. However, edge computing environments often have limite...
The landslide early warning system (LEWS) relies on various models for data processing, prediction, forecasting, and warning level discrimination. The potential different programming implementations and dependencies of these models complicate the dep...
The adoption of advanced Internet of Things (IoT) technologies has impressively improved in recent years by placing such services at the extreme Edge of the network. There are, however, specific Quality of Service (QoS) trade-offs that must be consid...
The acquisition, storage, and processing of huge amounts of data and their fast analysis to generate information is not a new approach, but it becomes challenging through smart decision-making on the choice of hardware and software improvements. In t...
Current medical informatics systems face critical challenges, including limited scalability across distributed institutions, insufficient real-time AI-driven decision support, and lack of standardized interoperability for heterogeneous medical data e...
Smart microgrids combining photovoltaic arrays, wind turbines, and battery storage generate telemetry that existing open-source monitoring tools cannot process with per-mechanism energy loss visibility in real time. This paper presents the design, im...
Collecting and preserving the smart environment logs connected to cloud storage is challenging due to the black-box nature and the multi-tenant cloud models which can pervade log secrecy and privacy. The existing work for log secrecy and confidential...
We present a combined ML/NLP (Machine Learning, Natural Language Processing) pipeline for protecting cloud-based APIs (Application Programming Interfaces), which works both at the level of individual HTTP (Hypertext Transfer Protocol) requests and at...
The reliable and continuous acquisition of seismic data from multiple open sources is essential for real-time monitoring, hazard assessment, and early-warning systems. However, the heterogeneity among existing data providers such as the United States...