6th IEEE International Conference on Big Data and Cloud Computing, Atlanta, Vereinigte Staaten

Abbrevation

BDCloud

Link

http://grid.cs.gsu.edu/~bdcloud/

City

Atlanta

Country

United States

Deadline Paper

2016-05-01

Start Date

2016-10-08

End Date

2016-10-10

Abstract

Big data is a term applied to many data sets with sizes going beyond the ability of commonly used software tools to capture, manage, process and analyze the data within a tolerable time period. Such datasets are usually characterized by having high VARIETY due to the data coming from various sources or having highly unstructured character (examples include data from social media, sensor networks, scientific applications, video and image formats, websites and documents, Internet search indexes, medical records, business transactions, web logs, etc.); and large VOLUMES that are needed to be processed with high data VELOCITY (I/O–intensive systems). Moreover, big data need to be high VALUE and VERACITY for decision makers to effectively take action and trust the results and rationale. Cloud computing is an increasingly popular approach for delivering information infrastructures and resources as computing services. A broad range of customers (both enterprises and individuals) can usually provision and deploy Cloud services via pay–as–you–go pricing models, which let them save significant capital investments in their own computing infrastructures. As estimated by IDC, by 2020, about 40% data globally will be touched with Cloud Computing. Cloud Computing can provide significant storage, computation, and distribution capabilities in support of solving multiple Big Data challenges. The BDCloud (Big Data and Cloud Computing) conference was created to provide a prime international forum for researchers, industry practitioners, and domain experts to exchange the latest advances in Big Data and Cloud Computing as well as support synergy of both fields. Topics Topics of particular interest include, but are not limited to: Fundamentals of cloud computing Architectural cloud models Programming cloud models Provisioning/pricing cloud models Data storage and computation in cloud computing Resource and large–scale job scheduling in cloud computing Security, privacy, trust, risk in cloud and big data Fault tolerance and reliability in cloud computing Access control to cloud computing Resource virtualisation Monitoring and auditing in cloud Scalable and elastic cloud services Social computing and impacts on the cloud Innovative HCI and touch–screen models and technologies to cloud Mobile commerce, handheld commerce and e–markets on cloud Intelligent/agent–based cloud computing Migration of business applications to cloud Energy efficient cloud architecture Energy aware data storage and computation in cloud computing Energy aware scheduling, monitoring, auditing in cloud Green Cloud Cloud use case studies Big Data theory, applications and challenges Big Data mining and analytics on Cloud Big Data Infrastructure, MapReduce and Cloud Computing Big Data visualization Large data stream, incremental datasets on cloud Distributed and federated datasets NoSQL data stores and DB scalability Big Data sharing, security, privacy and trust Big Data placement, scheduling, and optimization Distributed file systems for Big Data Big Data processing, resource scheduling and SLA on Cloud Performance characterization, evaluation and optimization Simulation and debugging of Big Data systems Volume, Velocity, Variety, Value and Veracity of Big Data Storage and computation management of Big Data Large–scale workflow management in Big Data Data management and distributed data systems Big data applications