Primary supervisor
Adel Nadjaran ToosiToday's society and its organisations are becoming ever-increasingly dependent upon Information and Communication Technology (ICT) systems mostly based in cloud data centres. These cloud data centres, serving as infrastructure for hosting ICT services, are consuming a large amount of electricity leading to (a) high operational costs and (b) high carbon footprint on the environment. In response to these concerns, renewable energy systems are shown to be extremely useful both in reducing dependence on finite fossil fuels and decreasing environmental impacts. However, powering data centres entirely with renewable energy sources such as solar or wind is challenging as they are non-dispatchable and not always available due to their fluctuating nature. Recently, container solutions such as Docker and container orchestration platforms such as Kubernetes, Docker Swarm, or Apache Mesos are gaining increasing use in cloud production environments. Containers provide a lightweight and flexible deployment environment with performance isolation and fine-grained resource sharing to run applications in clouds. This project intends to develop scheduling and auto-scaling algorithms for container orchestration within clouds based on the availability of renewable energy.
Aim/outline
This project aims to match energy consumption with the availability of renewables in the data centres by harnessing the diversity in Quality of Services (QoS) requirements of applications running on containers. We develop scheduling and auto-scaling policies within the container orchestration platform to optimise renewable energy use while QoS requirements of applications are met. As part of this project, we implement a small-scale prototype demonstrator using our micro data centre connected to microgrid (Solar panels). This project provides an excellent opportunity for the student to learn cloud backend technologies such as containers, Kubernetes/Docker Swarm, OpenStack and work within a multi-disciplinary area consisting of software engineering, science and electrical engineering.
URLs/references
Docker, https://www.docker.com Kubernetes, https://kubernetes.io/ Docker Swarm, https://docs.docker.com/engine/swarm/ . Goiri, K. Le, M. E. Haque, R. Beauchea, T. D. Nguyen, J. Guitart, J. Torres and R. Bianchini, "GreenSlot: scheduling energy consumption in green datacenters," in Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis, Seattle, Washington, 2011.
Required knowledge
Strong programming skills preferably in Java and Python. Basic knowledge of distributed systems and cloud computing. Knowledge and familiarity with Kubernetes or Docker Swarm is a plus.