相关论文: MS2M: A message-based approach for live stateful m…

This paper presents our preliminary results with ABEONA, an edge-to-cloud architecture that allows migrating tasks from low-energy, resource-constrained devices on the edge up to the cloud. Our preliminary results on artificial and real…

Future real-time applications like smart cities will use complex Machine Learning (ML) models for a variety of tasks. Timely status information is required for these applications to be reliable. Offloading computation to a mobile edge cloud…

We present a model for measuring the impact of offloading soft real-time jobs over multi-tier cloud infrastructures. The jobs originate in mobile devices and offloading strategies may choose to execute them locally, in neighbouring devices,…

In the last few years, the cloudification of applications requires new concepts and techniques to fully reap the benefits of the new computing paradigm. Among them, the microservices architectural style, which is inspired by…

Future mobile networks supporting Internet of Things are expected to provide both high throughput and low latency to user-specific services. One way to overcome this challenge is to adopt network function virtualization and Multi-access…

Serverless computing -- an emerging cloud-native paradigm for the deployment of applications and services -- represents an evolution in cloud application development, programming models, abstractions, and platforms. It promises a real…

As we move from 5G to 6G, edge computing is one of the concepts that needs revisiting. Its core idea is still intriguing: instead of sending all data and tasks from an end user's device to the cloud, possibly covering thousands of…

Network softwarization triggered a new wave of innovation in modern network design. The next generation of mobile networks embraces this trend. Mobile-edge computing (MEC) is a key part of emerging mobile networks that enables ultra-low…

Microservice architecture has become a dominant paradigm in application development due to its advantages of being lightweight, flexible, and resilient. Deploying microservice applications in the container-based cloud enables fine-grained…

Vehicular crowdsensing is anticipated to become a key catalyst for data-driven optimization in the Intelligent Transportation System (ITS) domain. Yet, the expected growth in massive Machine-type Communication (mMTC) caused by…

Microservices are used to build complex applications composed of small, independent and highly decoupled processes. Recently, microservices are often mentioned in one breath with container technologies like Docker. That is why operating…

The rise of LLMs such as ChatGPT and Claude fuels the need for AI agents capable of real-time task handling. However, migrating data-intensive, multi-modal edge workloads to cloud data centers, traditionally used for agent deployment,…

The next generation of mobile networks, namely 5G, and the Internet of Things (IoT) have brought a large number of delay sensitive services. In this context Cloud services are migrating to the edge of the networks to reduce latency. The…

Microservice and serverless computing systems open up massive versatility and opportunity to distributed and datacenter-scale computing. In the meantime, the deployments of modern datacenter resources are moving to disaggregated…

We present an Edge-as-a-Service (EaaS) platform for realising distributed cloud architectures and integrating the edge of the network in the computing ecosystem. The EaaS platform is underpinned by (i) a lightweight discovery protocol that…

Although the machine to machine (M2M) communication has been emerging in recent years, many vendors' specific proprietary solutions are not suitable for vital M2M applications. While the main focus of those solutions is management and…

Cloud computing has grown rapidly in recent years, mainly due to the sharp increase in data transferred over the internet. This growth makes load balancing a key part of cloud systems, as it helps distribute user requests across servers to…

Edge computing is a promising solution to enable low-latency IoT applications, by shifting computation from remote data centers to local devices, less powerful but closer to the end user devices. However, this creates the challenge on how…

With the pervasiveness of IoT devices, smart-phones and improvement of location-tracking technologies huge volume of heterogeneous geo-tagged (location specific) data is generated which facilitates several location-aware services. The…

Edge-cloud computing offloads parts of the computations that traditionally occurs in the cloud to edge nodes,e.g., CDN servers, in order to get closer to the users and reduce latency. To improve performance even further, WebAssembly is…