ustainability is a paradigm for thinking about the future in which environmental, societal and economic considerations are equitable in the pursuit of an improved lifestyle. Most of the economies are developing with breakneck velocities and are becoming epicenters of unsustainable global growth. Immense utilization of natural resources, waste generation and ecological irresponsibility are the reasons for such a dire situation. Big data analytics is clearly on a penetrative path across all arenas that rely on technology.
At present scientific area of chemical process engineering and natural hazards management is recognized as a method to integrate an efficient sustainability analysis and strategy. Those two engineering domains provide handful solution to manage systems by enabling the use of modeling, simulation, optimization, planning and control in order to develop a more sustainable product and process. In this context scientific simulation based on big data and collaborative work has to be developed for succeeding Computer-Aided Design/Engineering (CAD/E) of sustainable system. In scientific simulation based High Performance Computing (HPC) area, pre and post-processing technologies are the keys to make the investments valuable.
This special issue calls for high quality, up-to-date technology related to big data analytics for Sustainability and serves as a forum for researchers all over the world to discuss their works and recent advances in this field. A few best papers from IoTBDS 2017 and COMPLEXIS 2017 will be invited. In particular, the special issue is going to showcase the most recent achievements and developments in big data discovery and exploration. Both theoretical studies and state-of-the-art practical applications are welcome for submission. All submitted papers will be peer-reviewed and selected on the basis of both their quality and their relevance to the theme of this special issue.
The list of possible topics includes, but not limited to:
Geographical Big Data Analysis
Geography Big Data Mining and Exploration
Big Data for Smart Cities and Smart Homes
Large-scale Sustainable infrastructure and smart buildings
Large-scale Human Activities Data Computing
Sustainability Analysis of Energy Distributions
Internet of Things (IoT) services and applications
Internet of Vehicles (IoV) technologies
Passenger Sensing, Control and Management
Data-Driven Urban Management
Environment-Aware Application, analytics and visualization
Environment Big Data Processing and Analysis
Big Data Information Security for Sustainability
Knowledge-based systems, computing and visualization for Sustainability
Computational intelligence and algorithms for Sustainability
Cloud Computing Platform Based Big Data Mining
Energy-Consumption-Aware Ubiquitous Computing
Complex information systems for Sustainability
Environmental sensor networks, monitoring, environmental and weather studies
Energy efficient communication protocol for networks
Energy-efficient metrics and modeling for communication networks
Network traffic model and characteristics for information-centric networking
Future Generation Green ICT
Authors should prepare their manuscript according to the Guide for Authors available from the online submission page of the Future Generation Computer Systems at http://ees.elsevier.com/fgcs/. Authors should select “SI: BD Analytics Sust” when they reach the “Article Type” step in the submission process.