In today's world, ruled by a great amount of data and mobile devices, cloud-based systems
are spreading all over. Such phenomenon increases the number of connected devices …

Convolutional neural networks (CNNs) have been successfully applied in artificial intelligent
systems to perform sensory processing, sequence learning, and image processing. In …

Existing primary deduplication techniques either use inline caching to exploit locality in
primary workloads or use post-processing deduplication to avoid the negative impact on I/O …

Most modern multi-core edge devices work in outdoor situations with limited power supplies
like energy harvester and batteries. Therefore, energy consumption is a fundamental issue …

In this paper, we are interested in the energy optimization of hybrid Scratchpad Memory
(SPM) which consists of SRAM and Non-Volatile Memory (NVM). We approach the energy …

Very few models have been proposed for estimating the energy consumption of mobile
robots based on fuzzy controller methods. In comparison to the classical controllers, using …

Abstract The emerging Non-Volatile Memory (NVM) attracts attentions in recent years
because of its fast reading/writing speed, high density, low idle power and persistence. With …

Energy consumption is an important issue in designing embedded systems and the
emerging Internet of Things (IoT). The use of non-volatile memories instead of SRAM in …

Adopting multicore platforms is a general trend in real-time embedded systems. However,
integrating tasks with different real-time constraints into a single platform presents new …