Bio-Inspired Workflow Scheduling on HPC Platforms

Workflow Scheduling Techniques for Big Data Platforms

Today, almost everyone is connected to the Internet and uses different Cloud solutions to store, deliver, and process data. Cloud computing assembles large networks of virtualized services, such as hardware and software resources [1]. The use of cloud resources by end users is made in an asynchronous way and in many cases using mobile devices over different types of networks. Interoperability f...

Bidding policies for market-based HPC workflow scheduling

This paper considers the scheduling of jobs on distributed, heterogeneous High Performance Computing (HPC) clusters. Market-based approaches are known to be efficient for allocating limited resources to those that are most prepared to pay. This context is applicable to an HPC or cloud computing scenario where the platform is overloaded. In this paper, jobs are composed of dependent tasks. Each ...

A Survey on the Performance of Job Scheduling in Workflow Application on Grid Platforms

Scaling Support Vector Machines on modern HPC platforms

Support Vector Machines (SVM) have been widely used in data-mining and Big Data applications as modern commercial databases start to attach an increasing importance to the analytic capabilities. In recent years, SVM was adapted to the field of High Performance Computing for power/performance prediction, auto-tuning, and runtime scheduling. However, even at the risk of losing prediction accuracy...

IDS Based on Bio-inspired Models

Unsupervised projection approaches can support Intrusion Detection Systems for computer network security. The involved technologies assist a network manager in detecting anomalies and potential threats by an intuitive display of the progression of network traffic. Projection methods operate as smart compression tools and map raw, high-dimensional traffic data into 2-D or 3-D spaces for subseque...