With the development of the Internet of Things, the data that needs to be processed is
increasing rapidly. Therefore, the collaboration of cloud and edge emerges as the times …

Cloud providers leverage live migration of virtual machines to reduce energy consumption
and allocate resources efficiently in data centers. Each migration decision depends on three …

Supported by cloud computing, Federated Learning (FL) has experienced rapid
advancement, as a promising technique to motivate clients to collaboratively train models …

Edge Intelligence (EI), a burgeoning research area, motivates App vendors to cache data
replicas on geographically distributed edge servers to deliver better services. On the …

Edge intelligence, an emerging distributed paradigm, is driven by the increasing number of
Internet of Things devices and the development of edge computing and artificial intelligence …

Large-scale Internet applications running on data centers are typically instantiated as a set
of containers. Assigning a container to its affinity machine can reduce communication and …

Data centers already account for over 250TWh of energy usage every year and their energy
demand will grow above 1PWh until 2030 even in the best-case scenarios of some studies …

This chapter presents an overview and retrospective on the emergence, development, and
evolution of one of the industry's most popular standard benchmarks for computing systems …

We investigate three scenarios of reinforcement learning where the reward function or the
underlying process dynamics are not accurately known. In the first scenario, we develop two …

Cloud providers leverage live migration of virtual machines to reduce energy consumption
and allocate resources efficiently in data centers. Each migration decision depends on three …