Autonomic Computing is a concept that brings together many fields of computing with the
purpose of creating computing systems that self-manage. In its early days it was criticised as …

In the framework of fully cooperative multi-agent systems, independent (non-communicative)
agents that learn by reinforcement must overcome several difficulties to manage to …

This paper investigates the accuracy of predictive auto-scaling systems in the Infrastructure
as a Service (IaaS) layer of cloud computing. The hypothesis in this research is that …

This article describes Distributed W-Learning (DWL), a reinforcement learning-based
algorithm for collaborative agent-based optimization of pervasive systems. DWL supports …

Web applications have stringent performance requirements that are sometimes violated
during periods of high demand due to lack of resources. Infrastructure as a Service (IaaS) …

The high growth rate of vehicles per capita now poses a real challenge to efficient urban
traffic control (UTC). An efficient solution to UTC must be adaptive in order to deal with the …

One of the challenges of cloud computing is effective resource management due to its auto-
scaling feature. Prediction techniques have been proposed for cloud computing to improve …

This paper introduces a novel routing protocol in Delay Tolerant Networks (DTNs), aiming to
solve the online distributed routing problem. By manipulating a collaborative reinforcement …

This paper addresses the challenge of assigning virtual networks, through network
virtualisation, to the underlying physical network in a distributed and efficient manner. The …

Self-adaptation in embedded self-organizing real-time systems pose stringent expectations
on the performance of their system architecture. The flexibility required for self-adaptation …