Ubiquitous sensors and smart devices from factories and communities are generating
massive amounts of data, and ever-increasing computing power is driving the core of …

Fog computing is an emerging computing paradigm that uses processing and storage
capabilities located at the edge, in the cloud, and possibly in between. Testing and …

A distributed database utilizing the wide-spread edge computing servers to provide low-
latency data access with the serializability guarantee is highly desirable for emerging edge …

Multi-access Edge Computing (MEC) brings storage and computational capabilities at the
edge of the network into so-called Edge Data Centers (EDCs) to better low-latency …

Deciding what combination of operators to use across the Edge AI tiers to achieve specific
latency and model performance requirements is an open question for MLOps engineers …

To help MLOps engineers decide which operator to use in which deployment scenario, this
study aims to empirically assess the accuracy vs latency trade-off of white-box (training …

Extensive deployment of AI services, especially mobile AI, requires the support of edge
computing. This support is not just at the network architecture level, the design, adaptation …

In the past decade, Cloud Computing revolutionized the Information Technology industry by
enabling cost-effective high computational power for various services. However, the …

Urban computing is an emerging computing paradigm for processing urban data to serve
urban applications, which is an important manner to realize smart cities. To be specific …

The edge computing paradigm is an important supplement to the traditional cloud computing
paradigm in current IoT application scenarios. However, edge computing is highly related to …