Related papers: Edge computing server placement with capacitated l…
Capacitated spatial clustering, a type of unsupervised machine learning method, is often used to tackle problems in compressing, classifying, logistic optimization and infrastructure optimization. Depending on the application at hand, a…
Edge computing is an emerging paradigm to enable low-latency applications, like mobile augmented reality, because it takes the computation on processing devices that are closer to the users. On the other hand, the need for highly scalable…
Mobile edge computing is a new cloud computing paradigm which makes use of small-sized edge-clouds to provide real-time services to users. These mobile edge-clouds (MECs) are located in close proximity to users, thus enabling users to…
The vast data deluge at the network's edge is raising multiple challenges for the edge computing community. One of them is identifying edge storage servers where data from edge devices/sensors have to be stored to ensure low latency access…
Edge computing has become a very popular service that enables mobile devices to run complex tasks with the help of network-based computing resources. However, edge clouds are often resource-constrained, which makes resource allocation a…
Edge computing (EC) is a promising paradigm providing a distributed computing solution for users at the edge of the network. Preserving satisfactory quality of experience (QoE) for users when offloading their computation to EC is a…
Edge computing is the practice of placing computing resources at the edges of the Internet in close proximity to devices and information sources. This, much like a cache on a CPU, increases bandwidth and reduces latency for applications but…
Many cloud-based applications employ a data centre as a central server to process data that is generated by edge devices, such as smartphones, tablets and wearables. This model places ever increasing demands on communication and…
We consider the setting where a service is hosted on a third-party edge server deployed close to the users and a cloud server at a greater distance from the users. Due to the proximity of the edge servers to the users, requests can be…
The growing need for low-latency access to computing resources has motivated the introduction of edge computing, where resources are strategically placed at the access networks. Unfortunately, edge computing infrastructures like fogs and…
The Internet of Things (IoT) requires a new processing paradigm that inherits the scalability of the cloud while minimizing network latency using resources closer to the network edge. Building up such flexibility within the edge-to-cloud…
Edge computing has emerged as a distributed computing paradigm to overcome practical scalability limits of cloud computing. The main principle of edge computing is to leverage on computational resources outside of the cloud for performing…
In this paper, we consider the service caching and the computing resource allocation in edge computing (EC) enabled networks. We introduce a random service caching design considering multiple types of latency sensitive services and the base…
Fog/Edge computing model allows harnessing of resources in the proximity of the Internet of Things (IoT) devices to support various types of real-time IoT applications. However, due to the mobility of users and a wide range of IoT…
We present a framework for performance optimization in serverless edge-cloud platforms using dynamic task placement. We focus on applications for smart edge devices, for example, smart cameras or speakers, that need to perform processing…
Server deployment is a fundamental task in mobile edge computing: where to place the edge servers and what user cells to assign to them. To make this decision is context-specific, but common goals are 1) computing efficiency: maximize the…
We study how to design edge server placement and server scheduling policies under workload uncertainty for 5G networks. We introduce a new metric called resource pooling factor to handle unexpected workload bursts. Maximizing this metric…
Mobile Edge Computing (MEC) is a promising approach for enhancing the quality-of-service (QoS) of AI-enabled applications in the B5G/6G era, by bringing computation capability closer to end-users at the network edge. In this work, we…
Mobile edge computing (MEC) is a promising technique for providing low-latency access to services at the network edge. The services are hosted at various types of edge nodes with both computation and communication capabilities. Due to the…
Hierarchical edge-cloud computing-aided Internet of Things (IoT) networks offer low-latency and cost-efficient services to a growing number of data-intensive IoT devices. However, optimizing service placement, which involves determining the…