An End to End Real Time Architecture for Analyzing and Clustering Time Series Data: Case of an Energy Management System
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[1] Zahir Tari,et al. A Survey of Clustering Algorithms for Big Data: Taxonomy and Empirical Analysis , 2014, IEEE Transactions on Emerging Topics in Computing.
[2] Yingjie Tian,et al. A Comprehensive Survey of Clustering Algorithms , 2015, Annals of Data Science.
[3] Guangchi Liu,et al. Big data machine learning using apache spark MLlib , 2017, 2017 IEEE International Conference on Big Data (Big Data).
[4] Mahmoud Elkhodr,et al. A Middleware for the Internet of Things , 2016, ArXiv.
[5] Claude Tadonki,et al. Performance comparison between Hadoop and Spark frameworks using HiBench benchmarks , 2018, Concurr. Comput. Pract. Exp..
[6] Sergei Vassilvitskii,et al. Scalable K-Means++ , 2012, Proc. VLDB Endow..
[7] António Pereira,et al. Big Data Analytics in IOT: Challenges, Open Research Issues and Tools , 2018, WorldCIST.
[8] Abdulsalam Yassine,et al. Big Data Mining of Energy Time Series for Behavioral Analytics and Energy Consumption Forecasting , 2018 .
[9] Xia Liu,et al. A Survey of Distributed Message Broker Queues , 2017, ArXiv.
[10] T. Mohana Priya,et al. An Optimized repartitioned K-means Cluster algorithm using MapReduce Techniques for Big Data analysis-IJAERD , 2017 .
[11] Jay Kreps,et al. Kafka : a Distributed Messaging System for Log Processing , 2011 .
[12] Mohamed Essaaidi,et al. Smart campus microgrid: Advantages and the main architectural components , 2015, 2015 3rd International Renewable and Sustainable Energy Conference (IRSEC).
[13] Mohammed Essaaidi,et al. Smart campus energy management system: advantages, architectures, and the impact of using cloud computing , 2017, ICSDE.
[14] Partha Pratim Ray,et al. A survey of IoT cloud platforms , 2016 .
[15] Qiang Fu,et al. YADING: Fast Clustering of Large-Scale Time Series Data , 2015, Proc. VLDB Endow..
[16] José Cristóbal Riquelme Santos,et al. An approach to validity indices for clustering techniques in Big Data , 2018, Progress in Artificial Intelligence.
[17] José Antonio Lozano,et al. An efficient approximation to the K-means clustering for massive data , 2017, Knowl. Based Syst..