Inbjudan till predoc-seminarium på Institutionen för data- och systemvetenskap (DSV) vid Stockholms universitet. Doktoranden Ramin Firouzi presenterar sitt pågående arbete. Titeln är ”Distributed Intelligence for IoT System Using Edge Computing”.

Respondent: Ramin Firouzi, DSV
Opponent: Anders Lindgren, RISE
Huvudhandledare: Rahim Rahmani, DSV
Handledare: Thashmee Karunaratne, DSV
Närmast berörda professor: Panagiotis Papapetrou, DSV

Sammanfattning på engelska

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.