… - and DL-based resourcemanagement mechanisms in cellular wireless … resourcemanagement in cellular IoT and low-power IoT networks, review the traditional resourcemanagement …
… , resource optimisation, and energy optimisation, among others. This paper provides a detailed review of machinelearning-based resourcemanagement … , and machinelearning use in …
… job scheduling and multi-resource scheduling. Machinelearning techniques are extensively … projects that leveraged machinelearning techniques for resourcemanagement solutions in …
… management that sliced into five different isolated categories with miscellaneous resource management necessities where we present table 1 showing major resourcemanagement …
… Abstract—Machinelearning inference … resourcemanagement in heterogeneous multi-core systems and show how they can be applied to optimise the performance of machinelearning …
… of contexts to tackle resource allocation, scheduling, load … machinelearning’’ sidebar). In this article, we advocate dynamic multicore resourcemanagement based on machinelearning …
CJ Huang, YW Wang, CT Guan, HM Chen… - International Journal of …, 2013 - academia.edu
… resourcemanagement scheme for cloud computing proposed in this work. An application service resource … to record the overall utilization of system resources. Furthermore, a physical …
M Demirci - … 14th international conference on machine learning …, 2015 - ieeexplore.ieee.org
… resourcemanagement from two directions: optimizations for energy-efficient resource management, and machinelearning … topic in this work: how machinelearning has been used by …
D Wen, X Li, Q Zeng, J Ren… - … of Communications and …, 2019 - ieeexplore.ieee.org
… resourcemanagement (RRM), called data-importance aware RRM. Their designs feature the interplay of active machinelearning … data importance in active learning (eg, classification …