[HTML][HTML] Adaptive approximate computing in edge AI and IoT applications: A review
Recent advancements in hardware and software systems have been driven by the
deployment of emerging smart health and mobility applications. These developments have …
deployment of emerging smart health and mobility applications. These developments have …
Distributed and collective deep reinforcement learning for computation offloading: A practical perspective
Mobile edge computing (MEC) is a promising solution to support resource-constrained
devices by offloading tasks to the edge servers. However, traditional approaches (eg, linear …
devices by offloading tasks to the edge servers. However, traditional approaches (eg, linear …
Scheduling real-time security aware tasks in fog networks
Fog computing brings the cloud closer to a user with the help of a micro data center (),
leading to lower response times for delay sensitive applications. RT-SANE (R eal-T ime S …
leading to lower response times for delay sensitive applications. RT-SANE (R eal-T ime S …
Efficiency in the serverless cloud paradigm: A survey on the reusing and approximation aspects
C Denninnart, T Chanikaphon… - Software: Practice and …, 2023 - Wiley Online Library
Serverless computing along with Function‐as‐a‐Service (FaaS) is forming a new computing
paradigm that is anticipated to found the next generation of cloud systems. The popularity of …
paradigm that is anticipated to found the next generation of cloud systems. The popularity of …
Edge-cloud orchestration: Strategies for service placement and enactment
As devices existing at the edge of the network improve in their processing and data storage
capacity, there is increasing potential to host and enact services on such devices. A …
capacity, there is increasing potential to host and enact services on such devices. A …
Energy Efficient Wireless Signal Detection: A Revisit through the Lens of Approximate Computing
In the pursuit of energy efficiency in next-generation communication systems, approximate
computing is emerging as a promising technique. In the proposed work, efforts are made to …
computing is emerging as a promising technique. In the proposed work, efforts are made to …
Supporting data-driven workflows enabled by large scale observatories
AR Zamani, M AbdelBaky… - 2017 IEEE 13th …, 2017 - ieeexplore.ieee.org
Large scale observatories are shared-use resources that provide open access to data from
geographically distributed sensors and instruments. This data has the potential to accelerate …
geographically distributed sensors and instruments. This data has the potential to accelerate …
Ensemble-based network edge processing
Estimating energy costs for an industrial process can be computationally intensive and time
consuming, especially as it can involve data collection from different (distributed) monitoring …
consuming, especially as it can involve data collection from different (distributed) monitoring …
Quality of Service‐aware matchmaking for adaptive microservice‐based applications
Applications that make use of Internet of Things (IoT) can capture an enormous amount of
raw data from sensors and actuators, which is frequently transmitted to cloud data centers for …
raw data from sensors and actuators, which is frequently transmitted to cloud data centers for …
Submarine: A subscription‐based data streaming framework for integrating large facilities and advanced cyberinfrastructure
AR Zamani, M AbdelBaky… - Concurrency and …, 2020 - Wiley Online Library
Large scientific facilities provide researchers with instrumentation, data, and data products
that can accelerate scientific discovery. However, increasing data volumes coupled with …
that can accelerate scientific discovery. However, increasing data volumes coupled with …