Artificial Intelligence (AI) fosters enormous business opportunities that build and utilize private AI models. Implementing AI models at scale and ensuring cost-effective production of AI-based technologies through entirely in-house capabilities is a ...

Performance diagnosis systems are defined as detecting abnormal performance phenomena and play a crucial role in cloud applications. An effective performance diagnosis system is often developed based on artificial intelligence (AI) approaches, which can ...

The development of the Internet of Things (IoT) paradigm and its significant spread as an affordable data source has brought many challenges when pursuing efficient data collection, distribution, and storage. Since such hierarchical logical architecture ...

Deep learning (DL) has demonstrated its remarkable success in a wide variety of fields. The development of a DL model is a time-consuming and resource-intensive procedure. Hence, dedicated GPU accelerators have been collectively constructed into a GPU ...

Edge computing facilitates low-latency services at the network’s edge by distributing computation, communication, and storage resources within the geographic proximity of mobile and Internet-of-Things devices. The recent advancement in Unmanned Aerial ...

The scope of the Industrial Internet of Things (IIoT) has stretched beyond manufacturing to include energy, healthcare, transportation, and all that tomorrow’s smart cities will entail. The realm of IIoT includes smart sensors, actuators, programmable ...

With the proliferation of connected devices including smartphones, novel network connectivity and management methods are needed to meet user Quality of Experience (QoE) and computational demands of contemporary applications. Service caching and ...

Fog computing is a paradigm that allows the provisioning of computational resources and services at the edge of the network, closer to the end devices and users, complementing cloud computing. The heterogeneity and large number of devices are challenges ...

With the evolution of 5G and Internet of Things technologies, Mobile Edge Computing (MEC) has emerged as a major computing paradigm. Compared to cloud computing, MEC integrates network control, computing, and storage to customizable, fast, reliable, and ...

The rapid development of cloud computing with virtualization technology has benefited both academia and industry. For any cloud data center at scale, one of the primary challenges is how to effectively orchestrate a large number of virtual machines (VMs) ...

Information technology (IT) departments are increasingly challenged to replace legacy applications with novel public cloud software as a service (SaaS) to innovate the organization's business processes. The resulting hybrid cloud is formed by integrating ...

GraphQL is a query language and execution engine for web application programming interfaces (APIs) proposed as an alternative to improve data access problems and versioning of representational state transfer APIs. In this article, we thoroughly study the ...

Since its release in 2014, Kubernetes has become a popular choice for orchestrating containerized workloads at scale. To determine the most appropriate node to host a given workload, Kubernetes makes use of a scheduler that takes into account a set of ...

The emerging serverless computing paradigm has attracted attention from both academia and industry. This paradigm brings benefits such as less operational complexity, a pay-as-you-go pricing model, and an auto-scaling feature. The paradigm opens up new ...

Containerization is a lightweight application virtualization technology, providing high environmental consistency, operating system distribution portability, and resource isolation. Existing mainstream cloud service providers have prevalently adopted ...

The development of cloud infrastructures inspires the emergence of cloud-native computing. As the most promising architecture for deploying microservices, serverless computing has recently attracted more and more attention in both industry and academia. ...

The proliferation of services and service interactions within microservices and cloud-native applications, makes it harder to detect failures and to identify their possible root causes, which is, on the other hand crucial to promptly recover and fix ...

This is a survey article that explores six Cloud-based deployment archetypes for Cloud applications and the tradeoffs between them to achieve high availability, low end-user latency, and acceptable costs. These are (1) Zonal, (2) Regional, (3) Multi-...

Task scheduling is a critical issue in distributed computing environments like cloud and fog. The objective is to provide an optimal distribution of tasks among the resources. Several research initiatives to use metaheuristic techniques for finding near-...

Fog computing is a paradigm that brings computational resources and services to the network edge in the vicinity of user devices, lowering latency and connecting with cloud computing resources. Unlike cloud computing, fog resources are based on ...