Multi-Agent Reinforcement Learning (MARL) algorithms suffer from slow convergence and even divergence, especially in largescale systems. In this work, we develop an organization-b...
Chongjie Zhang, Sherief Abdallah, Victor R. Lesser
In this study, we consider an environment composed of a heterogeneous cluster of multicore-based machines used to analyze satellite images. The workload involves large data sets, a...
Luis D. Briceo, Jay Smith, Howard Jay Siegel, Anth...
Abstract—A premier goal of resource allocators in virtualization environments is to control the relative resource consumption of the different virtual machines, and moreover, to ...
Grid computing platforms require automated and distributed resource allocation with controllable quality-of-service (QoS). Market-based allocation these features using the compleme...
Efficient discovery and resource allocation is one of the challenges of current Peer-to-Peer systems. In centralized approaches, the user requests can be matched to the fastest, ch...
Oscar Ardaiz, Pau Artigas, Torsten Eymann, Felix F...