Allocating resources is crucial in large-scale distributed computing, as networks of
computers tackle difficult optimization problems. Within the scope of this discussion, the …

In many domains, the previous decade was characterized by increasing data volumes and
growing complexity of data analyses, creating new demands for batch processing on …

In a cloud environment, uncertainty and resource dispersion lead to problems with resource
allocation due, for instance, to heterogeneity, dynamism, and failures. Unfortunately, existing …

In this paper we propose a novel reservation plan adaptation system based on machine
learning. In the context of cloud auto-scaling, an important issue is the ability to define and …

In this work, we investigate the problem of inter-application interference in a shared Burst
Buffer (BB) system. A BB is a new storage technology for HPC architectures that acts as an …

Various application classes are being deployed to the cloud these days making use of a pay-
as-you-go policy. However, existing cloud technologies are still at an early stage of maturity …

The mechanism design theory can be applied not only in the economy but also in many
fields, such as politics and military affairs, which has important practical and strategic …

In the ever-evolving landscape of computational grid systems, the meticulous selection of
resources tailored to specific tasks is a formidable challenge. This paper introduces an …

In this paper, we present the development of a decentralized mechanism for the resources
control in a distributed computer system based on a network-centric approach. Intially, the …

The MapReduce framework has become the de facto standard for big data processing due
to its attractive features and abilities. One is that it automatically parallelizes a job into …