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CARDAP: a scalable energy-efficient context aware distributed mobile data analytics platform for the fog
conference contribution
posted on 2014-01-01, 00:00 authored by P P Jayaraman, J B Gomes, H L Nguyen, Z S Abdallah, S Krishnaswamy, Arkady ZaslavskyArkady ZaslavskyDistributed online data analytics has attracted significant research interest in recent years with the advent of Fog and Cloud computing. The popularity of novel distributed applications such as crowdsourcing and crowdsensing have fostered the need for scalable energy-efficient platforms that can enable distributed data analytics. In this paper, we propose CARDAP, a (C)ontext (A)ware (R)eal-time (D)ata (A)nalytics (P)latform. CARDAP is a generic, flexible and extensible, componentbased platformthat can be deployed in complex distributed mobile analytics applications e.g. sensing activity of citizens in smart cities. CARDAP incorporates a number of energy efficient data delivery strategies using real-time mobile data stream mining for data reduction and thus less data transmission. Extensive experimental evaluations indicate the CARDAP platform can deliver significant benefits in energy efficiency over naive approaches. Lessons learnt and future work conclude the paper.
History
Event
Advances in Databases and Information Systems. Conferences (18th : 2014 : Ohrid, Republic of Macedonia)Volume
8716Series
Advances in Databases and Information Systems ConferencesPagination
192 - 206Publisher
SpringerLocation
Ohrid, Republic of MacedoniaPlace of publication
Cham, SwitzerlandPublisher DOI
Start date
2014-09-07End date
2014-09-10ISSN
0302-9743eISSN
1611-3349Language
engPublication classification
E1.1 Full written paper - refereedCopyright notice
2014, Springer International Publishing SwitzerlandEditor/Contributor(s)
Y Manolopoulos, G Trajcevski, M Kon-PopovskaTitle of proceedings
ADBIS 2014 : Proceedings of the 18th East European Conference on Advances in Databases and Information Systems 2014Usage metrics
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