Adaptive Energy Efficiency Optimization Framework for Cloud Computing

Project: Monitored by Research Administration

Project Details

Grant Program

Faculty Development Competitive Research Grant Program 2021-2023

Project Description

recent years, the usage of large-scale computing systems has exceeded the peak
beyond remote data persistence and remote virtual instances. Nowadays, these
systems are popularly used for computational and data-intensive processes,
outgrowing themselves from traditional in-house clusters environments. All the
major corporations, including Amazon, Microsoft, Google, and IBM, provide large-scale computing systems in the shape of cloud platforms
designed for both scientific and personal needs. Rising as an operational
model, cloud computing has gradually gained popularity and become the standard orchestrator for data centers. In essence, cloud computing indeed
changes the routine of scaling the physical infrastructure and service level.
Instead of irrationally utilizing many arbitrary configurations of servers,
storage, and network facilities for similar purposes, it would be more
convenient and robust to provide transparent access to the computing resources
via the virtualization. This can be seen as an effort to unify the capacity of
multiple computing nodes in order to achieve a much higher level of service
composition. Furthermore, with the unification of facilities, cloud computing
makes it possible to engage in various optimized strategies in massive-scale.
These strategies mainly help to reduce the management cost as well as
energy consumption. In this proposal, we would like to kindly introduce our
effort to actualize one potential approach of these massive strategies, namely
Adaptive Energy Efficiency Optimization
Framework for Cloud Computing
Effective start/end date1/1/2112/31/23


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