This special issue addresses core topics on the design, the use and the evaluation of Big Data enabling technologies to build next-generation context-aware applications and computing systems for future intelligent environments. Disruptive paradigm shifts such as the Internet of Things (IoT) and Cyber-Physical Systems (CPS) will create a wealth of streaming context information. Large-scale context-awareness combining IoT and Big Data will drive to creation of smarter application ecosystems in diverse vertical domains, including smart health, finance, smart grids and cities, transportation, Industry 4.0, etc. However, effectively tapping into growing amounts of disparate contextual information streams remains a challenge, especially for large-scale application and service providers that need timely and relevant information to support adequate decision-making.

A deeper understanding is necessary on the strengths and weaknesses of state-of-the-art big data processing and analytics systems (Hadoop, Spark, Storm, Samza, Flume, Kafka, Kudu, etc.) to realize large-scale contextawareness and build Big Context architectures. In particular, the key question is how one can help identify relevant context information, ascertain the quality of the context information, extract semantic meaning from heterogeneous distributed information sources, and do this data processing effectively for many concurrent context-aware applications with different requirements for adequate decision-making.

At the same time, fundamental research is necessary to understand how context information about these large-scale distributed data processing infrastructures itself can offer the intelligence to selfadapt the configuration of these systems to optimize resource usage, such as the networking, data storage, and computation required to process context data. The particular focus of this special issue is on Big Context solutions covering the modeling, designing, implementation, assessment and systematic evaluation of large-scale context-aware applications and intelligent Big Data systems.

We are soliciting high-quality, original research papers and encourage submissions that cover the broad range of research topics combining Big Data and context-aware applications or intelligent environments, including practical applications and case studies, application design methodologies, empirical evaluation of systems and metrics, underpinning theories, and more technical/scientific research topics.

The possible topics include but are not limited to:

• Big Data architectures for large-scale context-aware applications
• Context models and query languages for heterogeneous data streams
• Distributed context reasoning with Big Data technologies
• Machine learning and prediction of situational awareness with Big Data
• Effective data collection and processing for concurrent context-aware applications
• Modeling of Quality of Service constraints and enforcing of Service Level Agreements
• Context-aware dynamic decision making on streaming Big Data
• Context-driven monitoring, adaptation and optimization of Big Data systems
• Large-scale Quality of Context management
• Systematic comparison of Big Data technologies for context-aware applications
• Big Context solutions for finance, health, smart cities, industry 4.0, etc.
• Security, privacy, scalability, and sustainability concerns Big Context systems

Submissions that use experimental data derived from real or simulated test-beds of smart applications and intelligent environments are especially encouraged.

To download detailed information of the call, please click here.

Important Dates

Guest Editors