TY - GEN
T1 - Towards integration of big data analytics in Internet of Things mashup tools
AU - Mahapatra, Tanmaya
AU - Gerostathopoulos, Ilias
AU - Prehofer, Christian
PY - 2016/11/7
Y1 - 2016/11/7
N2 - The increasing number and sensing capabilities of connected devices offer unique opportunities for developing sophisticated applications that employ data analysis as part of their business logic to make informed decisions based on sensed data. So far, mashup tools have been successful in supporting application development for Internet of Things. At the same time, Big Data analytics tools have allowed the analysis of very large and diverse data sets. The problem is that there is no consolidated development approach for integrating the two fields, IoT mashups and Big Data analytics. Such integration should go beyond merely specifying IoT mashups that only act as data providers. Mashup developers should also be able to specify Big Data analytics jobs and consume their results within a single application model. In this paper, we contribute to the direction of integrating Big Data analytics with IoT mashup tools by highlighting the need for such integration and the challenges that it entails via concrete examples. We also provide a research and development roadmap that can pave the way forward.
AB - The increasing number and sensing capabilities of connected devices offer unique opportunities for developing sophisticated applications that employ data analysis as part of their business logic to make informed decisions based on sensed data. So far, mashup tools have been successful in supporting application development for Internet of Things. At the same time, Big Data analytics tools have allowed the analysis of very large and diverse data sets. The problem is that there is no consolidated development approach for integrating the two fields, IoT mashups and Big Data analytics. Such integration should go beyond merely specifying IoT mashups that only act as data providers. Mashup developers should also be able to specify Big Data analytics jobs and consume their results within a single application model. In this paper, we contribute to the direction of integrating Big Data analytics with IoT mashup tools by highlighting the need for such integration and the challenges that it entails via concrete examples. We also provide a research and development roadmap that can pave the way forward.
KW - Big data analytics
KW - Development support
KW - Iot mashups
UR - http://www.scopus.com/inward/record.url?scp=85022081799&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85022081799&partnerID=8YFLogxK
U2 - 10.1145/3017995.3017998
DO - 10.1145/3017995.3017998
M3 - Conference contribution
AN - SCOPUS:85022081799
T3 - ACM International Conference Proceeding Series
SP - 11
EP - 16
BT - Proceedings of the 7th International Workshop on the Web of Things, WoT 2016
PB - Association for Computing Machinery
T2 - 7th International Workshop on the Web of Things, WoT 2016
Y2 - 7 November 2016
ER -