Apache (2018). Hadoop. Online: https://hadoop.apache.org. Accessed: September 2018.
Apache (2018). Spark. Online: https://spark.apache.org.Accessed: September 2018.
Baldeschwieler, E. (2018). Yahoo! launches worlds largest hadoop production application. Online: http://yahoohadoop.tumblr.com/post/98098649696/ yahoo-launches-worlds-largest-hadoop-production. Accessed: September 2018.
Dean, J. and Ghemawat, S. (2004). Mapreduce: Simplified data processing on large clusters. In OSDI04: Sixth Symposium on Operating System Design and Implementation
Docker (2018). Online: https://docs.docker.com/. Accessed: September 2018.
El Ioini, N. and Pahl, C. (2018). A review of distributed ledger technologies. OTM Confederated International Conferences.
Femminella, M., Pergolesi, M., and Reali, G. (2016). Performance evaluation of edge cloud computing system for big data applications. In 5th IEEE International Conference on Cloud Networking (Cloudnet), pages 170-175.
Fowley, F., Pahl, C., Jamshidi, P., Fang, D., and Liu, X. (2018). A classification and comparison framework for cloud service brokerage architectures IEEE Transactions on Cloud Computing 6 (2), 358-371.
Heinrich, R., van Hoorn, A., Knoche, H., Li, F., Lwakatare, L.E., Pahl, C., Schulte, S., and Wettinger, J. (2017). Performance engineering for microservices: research challenges and directions. Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering Companion.
Jamshidi, P., Sharifloo, A., Pahl, C., Arabnejad, A., Metzger, A., and Estrada, G. (2016). Fuzzy self-learning controllers for elasticity management in dynamic cloud architectures. 12th International ACM Conference on Quality of Software Architectures (QoSA).
Jamshidi, P., Sharifloo, A., Pahl, C., Metzger, A., and Estrada, G. (2015). Self-learning cloud controllers: Fuzzy q-learning for knowledge evolution. arXiv preprint arXiv:1507.00567.
Jamshidi, P., Pahl, C., Mendonca, N.C., Lewis, J., and Tilkov, S. (2018). Microservices: The Journey So Far and Challenges Ahead. IEEE Software 35 (3), 24-35.
Jamshidi, P., Pahl, C., and Mendonca, N.C. (2016). Managing uncertainty in autonomic cloud elasticity controllers. IEEE Cloud Computing, 50-60.
Johnston, S.J., Basford, P.J., Perkins, C.S., Herry, H., Tso, F.P., Pezaros, D., Mullins, R.D., Yoneki, E., Cox, S.J., and Singer, J. (2018). Commodity single board computer clusters and their applications. Future Generation Computer Systems, 89: 201-212.
Hentschel, K., Jacob, D., Singer, J., and Chalmers, M. (2016). Supersensors: Raspberry pi devices for smart campus infrastructure. IEEE Intl Conf on Future Internet of Things and Cloud (FiCloud).
Morabito, R. (2016). A performance evaluation of container technologies on internet of things devices. In IEEE Conference on Computer Communications Workshops.
Morabito, R., Farris, I., Iera, A., and Taleb, T. (2017). Evaluating performance of containerized iot services for clustered devices at the network edge. IEEE Internet of Things Journal, 4(4):1019-1030.
Naik, N. (2017). Docker container-based big data processing system in multiple clouds for everyone. In 2017 IEEE International Systems Engineering Symposium (ISSE), pages 1-7.
Pahl, C. and Lee. B. (2015). Containers and clusters for edge cloud architectures - A technology review. IEEE Intl Conf on Future Internet of Things and Cloud.
Pahl, C., El Ioini, N., Helmer, S., and Lee, B. (2018). An architecture pattern for trusted orchestration in IoT edge clouds. Third International Conference on Fog and Mobile Edge Computing (FMEC).
Pahl, C., Jamshidi, P., and Zimmermann, O. (2018). Architectural principles for cloud software. ACM Transactions on Internet Technology (TOIT) 18 (2), 17.
Pahl, C., Helmer, S., Miori, L., Sanin, J., and Lee. B. (2016). A container-based edge cloud paas architecture based on raspberry pi clusters. IEEE International Conference on Future Internet of Things and Cloud Workshops (FiCloudW).
Renner, T., Meldau, M., and Kliem, A. (2016). Towards container-based resource management for the internet of things. In International Conference on Software Networking (ICSN).
Renner, M. (2016). Testing high availability of docker swarm on a raspberry pi cluster. Online: https://blog.hypriot.com/post/high-availability-withdocker/, 2016. Accessed: September 2018.
Renner, M. (2016). Evaluation of high availability performance of kubernetes and docker swarm on a raspberry pi cluster. Highload++ Conference.
Raspberry Pi Foundation (2018). Online: https://www.raspberrypi.org/products/raspberry-pi-2-model-b/. Accessed: September 2018.
Taibi, D., Lenarduzzi,V., and Pahl, C. (2018). Architectural patterns for microservices: a systematic mapping study. Proc. 8th Intl Conf. Cloud Computing and Services Science.
Tso, F.P., White, D.R., Jouet, S., Singer, J., and Pezaros, D.P. (2013). The glasgow raspberry pi cloud: A scale model for cloud computing infrastructures. In IEEE 33rd International Conference on Distributed Computing Systems Workshops.
Turner, V. (2014). The Digital Universe of Opportunities: Rich Data and the Increasing Value of the Internet of Things. IDC Report.
von Leon, D., Miori, L., Sanin, J., El Ioini, N., Helmer, S., and Pahl, C. (2018). A Performance Exploration of Architectural Options for a Middleware for Decen-tralised Lightweight Edge Cloud Architectures. Intl Conf on Internet of Things, Big Data and Security.
von Leon, D., Miori, L., Sanin, J., El Ioini, N., Helmer, S., and Pahl, C. (2019). A Lightweight Container Middleware for Edge Cloud Architectures. Fog and Edge Computing: Principles and Paradigms, 145-170. Wiley & Sons.
Wang, Y., Goldstone, R., Yu, W., and Wang, T. (2014). Characterization and optimization of memory-resident mapreduce on hpc systems. In IEEE 28th Intl Parallel and Distributed Processing Symposium.