Globally, cities are emerging into Smart Cities (SC) as a result of sustainable cities and the
adaption of recent Internet of Things (IoT) technology. It is becoming essential to involve …

Deep learning is a very computing-intensive and time-consuming task. It needs an amount
of computing resource much greater than a single machine can afford to train a …

The paper surveys the state of the art of task scheduling in Desktop Grid computing systems.
We describe the general architecture of a Desktop Grid system and the computing model …

In the pool of cloud providers that are currently available there is a lack of standardised APIs
and brokering tools to effectively distribute high throughput calculations among them …

Cloud Computing brings a lot of benefits to its consumers. Adoption of Cloud Computing
technologies to Desktop Grid-based high-throughput computing promises better usability …

We describe a scheme for subdividing long-running, variable-length analyses into short,
fixed-length boinc workunits using phylogenetic analyses as an example. Fixed-length …

The paper addresses the problem of accelerating the “tail” stage of a computational
experiment in a Desktop Grid. We provide the mathematical model of a “tail” stage, describe …

Cloud Computing promises to be more flexible, usable, available and simple than Grid,
covering also much more computational needs than the ones required to carry out …

In this paper a short survey on Desktop Grid and Cloud computing paradigms combination is
presented. There are four approaches are considered:(1) extension of a Cloud by Desktop …

Exploiting resources belonging to multiple cloud providers in an efficient way is still an open
issue for distributed computing. Scheduling algorithms based on heuristic, probabilistic …