Autoscaling system can reconfigure cloud-based services and applications, through various
configurations of cloud software and provisions of hardware resources, to adapt to the …

Emerging cloud-based software services have proposed request for self-adaptive resource
allocation that provides to dynamically adjust resources on demand. Traditional self …

Energy consumption limits battery life in mobile devices and increases costs for servers and
data centers. Approximate computing addresses energy concerns by allowing applications …

Medical conditions and accidents might cause immobility in certain parts of the body. In
order to assist people in the rehabilitation process, sensors obtaining bio-signals from the …

Pre-trained deep learning models are increasingly being used to offer a variety of compute-
intensive predictive analytics services such as fitness tracking, speech, and image …

An apparatus and method are provided to perform constrained optimization of a constrained
property of an apparatus, which is complex due to having several components, and these …

An increasing number of software applications incorporate runtime Deep Neural Networks
(DNNs) to process sensor data and return inference results to humans. Effective deployment …

Elastic auto-scaling in cloud platforms has primarily used horizontal scaling by assigning
application instances to distributed resources. Owing to rapid advances in hardware, cloud …

Modern software systems often have a huge number of configurations whose performance
properties are poorly documented. Unfortunately, obtaining a good understanding of these …

In this paper, we present a framework for resource management of Streaming Data Analytics
Flows (SDAF). Using advanced techniques in control and optimization theory, we design an …