Welcome to a predoc seminar on IoT and edge computing! Ramin Firouzi, PhD student at DSV, is the respondent.
Invitation to PhD student Ramin Firouzi’s predoc seminar at the Department for Computer and Systems Sciences (DSV), Stockholm University. He will present his ongoing work on “Distributed Intelligence for IoT System Using Edge Computing”.
Respondent: Ramin Firouzi, DSV Opponent: Anders Lindgren, RISE Main supervisor: Rahim Rahmani, DSV Supervisor: Thashmee Karunaratne, DSV Professor closest to the subject: Panagiotis Papapetrou, DSV
Abstract
Over the past decade, the Internet of Things (IoT) has undergone a paradigm shift away from centralized cloud computing to edge computing. Hundreds of billions of things are estimated to be deployed in the rapidly advancing IoT paradigm, resulting in an enormous amount of data. Sending all the data to the cloud has recently proven to be a performance bottleneck as it causes many network issues, including latency, power consumption, security, privacy, etc.
However, the existing paradigms do not use edge devices for decision-making. Distributed intelligence could strengthen the IoT in several ways by distributing decision-making tasks among edge devices within the network instead of sending all data to a central server. All computational tasks and data are shared among edge devices.
Edge computing offers many advantages, including distributed processing, low latency, fault tolerance, better scalability, better security, and data protection. These advantages are helpful for critical applications that require higher reliability, real-time processing, mobility support, and context awareness. This thesis investigated the application of different types of intelligence (e.g., rule-based, machine learning, etc.) and network challenges for implementing distributed intelligence at the edge of the network.
The focus of this PhD thesis project is on distributed intelligence in the Internet of Things (IoT), edge computing, and distributed computing. Currently, we are investigating how to optimize the architecture of the network at the edge of IoT to provide more efficient distributed intelligence.
Technological advances allow both humans and things to be more connected and exchange information. Our research focuses on how we can participate in real and virtual societies, with regards to application areas such as culture, transport, intelligent vehicles and e-health.
