Related papers: Dynamic Service Provisioning in the Edge-cloud Con…
Today's Cloud applications are dominated by composite applications comprising multiple computing and data components with strong communication correlations among them. Although Cloud providers are deploying large number of computing and…
As mobile edge computing (MEC) finds widespread use for relieving the computational burden of compute- and interaction-intensive applications on end user devices, understanding the resulting delay and cost performance is drawing significant…
Due to the limited resource capacity of edge servers and the high purchase costs of edge resources, service providers are facing the new challenge of how to take full advantage of the constrained edge resources for Internet of Things (IoT)…
The Mobile Edge Computing (MEC) system located close to the client allows mobile smart devices to offload their computations onto edge servers, enabling them to benefit from low-latency computing services. Both cloud service providers and…
Edge computing has become increasingly popular across many domains and enterprises. However, given the locality constraint of edges (i.e., only close-by edges are useful), multiplexing diverse workloads becomes challenging. This results in…
In order to better accommodate the dramatically increasing demand for data caching and computing services, storage and computation capabilities should be endowed to some of the intermediate nodes within the network. In this paper, we design…
A vast and growing number of IoT applications connect physical devices, such as scientific instruments, technical equipment, machines, and cameras, across heterogenous infrastructure from the edge to the cloud to provide responsive,…
Modern Cyber-physical Systems (CPS) include applications like smart traffic, smart agriculture, smart power grid, etc. Commonly, these systems are distributed and composed of end-user applications and microservices that typically run in the…
The increasing popularity of cloud computing has resulted in a proliferation of data centers. Effective placement of data centers improves network performance and minimizes clients' perceived latency. The problem of determining the optimal…
This paper presents the idea and the concepts behind the vision of an Ephemeral Cloud/Edge Continuum, a cloud/edge computing landscape that enables the exploitation of a widely distributed, dynamic, and context-aware set of resources. The…
Achieving sustainable, explainable, and maintainable automation for resource optimization is a core challenge across the edge-cloud continuum. Persistent overprovisioning and operational complexity often stem from heterogeneous platforms…
In the edge computing paradigm, mobile devices offload the computational tasks to an edge server by routing the required data over the wireless network. The full potential of edge computing becomes realized only if a smart device selects…
The computing continuum extends the high-performance cloud data centers with energy-efficient and low-latency devices close to the data sources located at the edge of the network. However, the heterogeneity of the computing continuum raises…
In mobile edge computing, local edge servers can host cloud-based services, which reduces network overhead and latency but requires service migrations as users move to new locations. It is challenging to make migration decisions optimally…
Edge systems promise to bring data and computing closer to the users of time-critical applications. Specifically, edge storage systems are emerging as a new system paradigm, where users can retrieve data from small-scale servers…
Multiple access mobile edge computing is an emerging technique to bring computation resources close to end mobile users. By deploying edge servers at WiFi access points or cellular base stations, the computation capabilities of mobile users…
Future scenarios, such as AR/VR, pose challenging latency and bandwidth requirements in 5G. This need is complemented by the adoption of cloud principles for providing services, particularly for virtualizing service components with which…
The demand for distributed applications has significantly increased over the past decade, with improvements in machine learning techniques fueling this growth. These applications predominantly utilize Cloud data centers for high-performance…
Network virtualization and programmability allow operators to deploy a wide range of services over a common physical infrastructure and elastically allocate cloud and network resources according to changing requirements. While the elastic…
The explosive growth of user devices and emerging applications is driving unprecedented traffic demands, accompanied by stringent Quality of Service (QoS) requirements. Addressing these challenges necessitates innovative service…