Call For Papers |
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Big data is an emerging paradigm applied to datasets whose size is beyond the ability of commonly used software tools to capture, manage, and process the data within a tolerable elapsed time. Such datasets are often from various sources (Variety) yet unstructured such as social media, sensors, scientific applications, surveillance, video and image archives, Internet texts and documents, Internet search indexing, medical records, business transactions and web logs; and are of large size (Volume) with fast data in/out (Velocity). More importantly, big data has to be of high value (Value) and establish trust in it for business decision making (Veracity). Various technologies are being discussed to support the handling of big data such as massively parallel processing databases, scalable storage systems, cloud/stream computing platforms, and high performance/parallel computing platforms.
•Novel theories, computational models, and algorithms of Big Data •Big Data standards •Big Data search and mining •Big Data learning and analytics •Big Data infrastructure, high performance/parallel computing platforms •Big Data visualization •Big Data curation and management •Big Data semantics, scientific discovery and intelligence •Big Data performance analysis and large-scale deployment •Security, privacy, trust, and legal issues about Big Data •Big Data vs Big Business and Big Industry •Large data stream processing •Large incremental datasets •Distributed and federated datasets •NoSQL data stores and Big Data compression •Big Data placement, scheduling, and optimization •Distributed file systems for Big Data •MapReduce for Big Data processing, resource scheduling and SLA •Performance characterization, evaluation and optimization •Simulation and debugging systems and tools for MapReduce and Big Data •Volume, Velocity, Variety, Value and Veracity of Big Data •Multi-source Big Data processing and integration •Storage and computation management of Big Data •Large-scale Big Data workflow management •Big Data sensing and crowdsourcing •Sensor network, social network and Big Data •Big Data ecosystem •Foundation models and Big Data •Big Data applications PAPER SUMBMISSION All papers need to be submitted electronically through the conference submission website https://edas.info/N32630 with PDF format. The materials presented in the papers should not be published or under submission elsewhere. Each paper is limited to 8 pages (or 12 pages with over length charge) including figures and references using IEEE Computer Society Proceedings Manuscripts style (two columns, single-spaced, 10 fonts). Manuscript Templates for Conference Proceedings can be found at: https://www.ieee.org/conferences_events/conferences/publishing/templates.html Once accepted, at least one of the authors of any accepted paper is requested to register the paper at the conference. |
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