Bachelor and Master Theses

Cloud computing has captured significant attention from different sectors due to its innovative characteristics and services. Cloud services provide access to a wide range of infrastructures hosted on cloud data centers. Recently, the number of Internet of Things (IoT) devices (e.g., smartphones, cameras, and smart vehicles) has increased dramatically. Serving the applications of those devices, and processing/storing the massive amount of data they generate have become a critical issue.

Some of such applications need powerful computing and network resources as they are real-time and latency-sensitive. Cloud computing has a massive pool of resources, but the architecture of traditional cloud computing (centralized fashion) did not design the generated massive data, as moving all data of the applications from the network edge to the cloud data centers for processing and storage adds latency and outstrips the network bandwidth capacity. So, the best place to process/store the generated data can be near the IoT devices. This is called edge computing, which aims to move operations as close to the data sources as possible and acts as an intermediate layer between IoT devices and cloud data centers.

IoT-Edge-Cloud is forming what is called The Computing Continuum, which is a unified environment to run and serve the applications. To provide stable services, this environment needs to be considered as an integrated unit while deciding on an exact layer (IoT, Edge, or Cloud) to serve the applications.

The aim of this work is to manage serving latency-sensitive applications such that some QoS metrics (e.g., deadline) must be ensured. This issue can be tackled by designing a latency-aware model for application placement of IoT devices to minimize their execution time in the computing continuum.

References:

- Al-Dulaimy A, et al. "The computing continuum: From IoT to the cloud." Internet of Things 27 (2024): 101272.

- Salaht FA, Desprez F, Lebre A. "An overview of service placement problem in fog and edge computing". ACM Computing Surveys (CSUR). 2020 12;53(3):1-35.

- Taneja M, Davy A. "Resource aware placement of IoT application modules in Fog-Cloud Computing Paradigm". In 2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM) 2017 (pp. 1222-1228).

- Good background in computing systems, and in solving optimization problems.

- Advanced programming skills.