Thesis Presentations Group 2

Title: insert title
Author: Lastname, Name
Supervisor(s): insert names separated by semicolons
Hosting Institution: insert name of hosting Unviersity(ies)
Abstract: Insert thesis abstract(200 words)
Paper: Insert link to thesis paper.

Title: insert title
Author: Lastname, Name
Supervisor(s): insert names separated by semicolons
Hosting Institution: insert name of hosting Unviersity(ies)
Abstract: Insert thesis abstract(200 words)
Paper: Insert link to thesis paper.

Title: insert title
Author: Lastname, Name
Supervisor(s): insert names separated by semicolons
Hosting Institution: insert name of hosting Unviersity(ies)
Abstract: Insert thesis abstract(200 words)
Paper: Insert link to thesis paper.

Title: Architecting and Designing Sustainable Smart City Services in Living Lab Environment
Author: Alam, Md Tawseef
Supervisor(s): Professor Jari Porras; Professor Ahmed Seffah
Hosting Institution: Lappeenranta University of Technology
Abstract: Insert thesis abstract(200 words)
Paper: Insert link to thesis paper.

Title: Energy - Aware Cloud Infrastructure for IoT Big Data Processing
Author: Ganesan, Madhubala
Supervisor(s): Prof. Colin Pattinson; Dr. Ah-Lian Kor
Hosting Institution: Leeds Beckett University
Abstract: Internet of Things (IoT) along with Big Data Analytics is poised to become the backbone of Smart and Sustainable Systems which bolster economic, environmental and social sustainability. Cloud-based data centers provide computing power to churn out valuable information from voluminous IoT data. Multifarious servers in the data centers turn out to be the black hole of superfluous energy burn contributing to 2% of the global carbon dioxide (CO2) emissions. IoT energy concerns are addressed by research in low-power sensors and improved Machine-to-Machine communications. However, cloud-based data centers still face energy-related challenges. Virtual Machine (VM) consolidation is an approach towards energy efficient cloud infrastructure. Although several works show convincing results of the potential of VM consolidation in simulated environments, there is inadequacy in terms of investigations on real, physical cloud infrastructure for big data workloads. This work intends to evaluate dynamic VM consolidation approaches by combining algorithms from literature. An open source VM consolidation framework, Openstack NEAT is adopted and experiments are conducted on a Multi-node Openstack Cloud with Apache Spark as Big data platform. Results on performance based on Service Level Agreement (SLA) metrics and energy usage of compute hosts are presented and the best combination of algorithms is recommended.
Paper: Insert link to thesis paper.