Advances in modelling and simulation for big‐data applications (AMSBA)

Since the Internet introduction, we witness an explosive growth in the volume, velocity, and variety of the data created on a daily basis. This data is originated from numerous sources including mobile devices, sensors, individual archives, Internet of Things, government data holdings, software logs, public profiles in social networks, commercial datasets, etc. The issue so-called the Big Data problem requires the continuous increase of the processing speeds of the servers and of the whole network infrastructure. The Big Data era poses a critically difficult challenge and striking development opportunities to data intensive (DI) and high-performance computing (HPC): how to efficiently turn massively large data into valuable information and meaningful knowledge. Computational-effective DI and HPC are required in a fast-increasing number of data-intensive domains. Modelling and Simulation (MS) has often offered suitable abstractions to manage the complexity of the analysis of large data in various scientific and engineering domains. Unfortunately, Big Data problems are not always easily amenable to efficient MS over DI and HPC because of the complexity of the systems and of the lack of a simple way in which the analysis can be parallelized. Also, MS communities may lack the detailed expertise required to exploit the full potential of HPC solutions, and HPC architects may not be fully aware of specific MS requirements. The main research areas targeted by this special issue are algorithms and applications for Big Data, network architectures to support Big Data analytics, network and resource provisioning approaches, Big Data visualization techniques, Big Data storage and management in the cloud, many-cloud and fog systems, security and trust in Big Data management, energy-awareness in Big Data management, high-performance computing models, Big Data middleware, and data-intensive applications. This special issue primarily encompasses practical approaches that advance research in all aspects of modelling and simulation for Big Data applications. The main scope of this special issue is to highlight advances topics in modeling and simulation for Big Data Applications. The main role of simulation techniques in this domain is to crate the suitable framework for applications modeling, development, and testing before deployment in the real world. The Special Issue focuses on topics covering algorithms, architectures, management models, high-performance computing techniques, and large-scale distributed systems. The contributions accepted range from advanced technologies, applications, and innovative solutions to global optimization problems in scalable large-scale computing systems to development of methods, conceptual and theoretical models related to Big Data applications and massive data storage and processing.