An efficient mechanism for resource management of fog-based IoMT applications

نوع: Type: thesis

مقطع: Segment: masters

عنوان: Title: An efficient mechanism for resource management of fog-based IoMT applications

ارائه دهنده: Provider: Maryam Eslami

اساتید راهنما: Supervisors: Dr. Mehdi Sakhaei-nia

اساتید مشاور: Advisory Professors:

اساتید ممتحن یا داور: Examining professors or referees: Dr. Muharram Mansoorizadeh and Dr. Reza Mohammadi

زمان و تاریخ ارائه: Time and date of presentation: 15:00 ,22/12/2021

مکان ارائه: Place of presentation: Virtual

چکیده: Abstract: Over the past years, various research efforts have been founded to propose distributed computation models to overcome the problems with the central nature of cloud computing. Amongst all, fog computing with the vision of extending cloud services to the edge of the network can effectively meet the requirements of new applications such as the Internet of Medical Things (IoMT), such as low latency, energy efficiency, etc. Deployment of applications in fog computing differs from the cloud. Since fog resources are much more limited than cloud data centers, heterogeneous, and distributed, the deployment of applications should be done in a distributed manner in this model. In this regard, fog service deployment is a challenge and research topic in this field. In this thesis, the Fog Service Deployment Problem (FSDP) is studied specifically for the IoMT applications. In this way, first, the requirements of such applications are identified. Then a novel problem formulation is presented for FSDP optimization. It must be mentioned that in the proposed methodology, the quality requirements of these applications including availability and security are considered along with the quantitative indicators such as energy consumption and response time of applications. Due to the NP-Hard nature of FSDP, three reputed multi-objective evolutionary algorithms, namely Speed-constrained Multi-objective Particle Swarm Optimization (SMPSO), Non-dominated Sorting Genetic Algorithm-II (NSGA-II), and lastly MultiObjective Evolutionary Algorithm based on Decomposition (MOEA/D) are used to solve the FSDP optimization. The simulation results in the iFogSim simulator demonstrate a generally better behavior of SMPSO algorithms compared to the other two methods