N. Šatkauskas “Fog computing service dynamic orchestration method” doctoral dissertation defence

Author, Institution: Nerijus Šatkauskas, Kaunas University of Technology

Science area, field of science: Technological Sciences, Informatics Engineering, T007

Scientific Supervisor: Prof. Dr. Algimantas Venčkauskas (Kaunas University of Technology, Technological Sciences, Informatics Engineering, T007)

Dissertation Defence Board of Informatics Engineering Science Field:
Prof. Dr. Rimantas Butleris (Kaunas University of Technology, Technological Sciences, Informatics Engineering, T007) – chairperson
Prof. Dr. Tomas Blažauskas (Kaunas University of Technology, Technological Sciences, Informatics Engineering, T007)
Prof. Dr. Arnas Kačeniauskas (Vilnius Gediminas Technical University, Technological Sciences, Informatics Engineering, T007)
Prof. Dr. Hab. Artūras Kaklauskas (Vilnius Gediminas Technical University, Technological Sciences, Informatics Engineering, T007)
Assoc. Prof. Dr. Anton Rassolkin (Tallinn University of Technology, Estonia, Technological Sciences, Informatics Engineering, T 007)

Dissertation defence meeting will be at Rectorate Hall of Kaunas University of Technology (K. Donelaičio 73–402, Kaunas)

The doctoral dissertation is available at the library of Kaunas University of Technology (Gedimino g. 50, Kaunas) and on the internet: N. Šatkauskas el. dissertation (PDF)

Annotation: Fog Computing conception was introduced by OpenFog Consortium which was established in 2015 by such companies as Cisco, Microsoft, Intel etc. This paradigm seeks to solve Cloud Computing issues. They are due to long transmission distances, higher data flow, data loss, latency, and energy consumption. Services have to be closer to end-users as a part of a solution. But, fog devices are known for being mobile and heterogenous. Their resources can be limited, and their availability can be constantly changing. A service placement optimization is needed to meet the QoS requirements. A service placement orchestration is proposed in this thesis, which functions as a multi-agent system. This two-step process is made of Multi-Objective Particle Swarm Optimization (IMOPSO) to generate particle sets as the first step and the Analytical Hierarchy Process (AHP) with a specific judgement matrix as the second step for service distribution priority decisions. This dynamic service orchestration method is important for its quality that it does not focus on a central control unit. It allows to make a service placement decision for any orchestrator which synchronizes its resource availabilities with other nodes within the fog network. It greatly improves scalability and resilience to fog node failures. It also supports mobility and adapts to resource availability changes.