| Title | Optimizing System-on-Chip Performance Using AI and SDN: Approaches and Challenges |
| Publication Type | Conference Paper |
| Year of Publication | 2022 |
| Authors | Alja'afreh, Mohammad, Obaidat, Muath, Karime, Ali, Alouneh, Sahel |
| Conference Name | 2022 Ninth International Conference on Software Defined Systems (SDS) |
| Date Published | dec |
| Keywords | artificial intelligence, Artificial Intelligence (AI), Computer architecture, deep learning (dl), Design Space Optimization (DSO), Hardware, i-o systems security, I/O (Input/Output), Integrated Circuits (IC), Intellectual Property (IP) blocks, machine learning (ML), network-on-chip, Network-on-Chip (NoC) Software Defined Networks (SDN), performance evaluation, pubcrawl, Scalability, Software, Solids, System-on-Chip (SoC) |
| Abstract | The advancement of modern multimedia and data-intensive classes of applications demands the development of hardware that delivers better performance. Due to the evolution of 5G, Edge-Computing, the Internet of Things, Software-Defined networks, etc., the data produced by the devices such as sensors are increasing. A software-Defined network is a powerful paradigm that is capable of automating networking and cloud computing. Software-Defined Network has controllers, devices, and applications which produce a huge amount of data. The processing of data inside the device as well as between the devices needs a better hardware architecture with more cores to ensure speedy performance. The System-on-Chip approach alone will not be capable to handle this dense core comprised of hardware. We have to blend Network-on-Chip along with System-on-Chip to increase the potential to include more cores capable to handle more threads. Artificial Intelligence, a key enabler in next-generation devices is capable of producing a better architecture design with optimized performance. In this paper, we are discussing and endeavouring how System-on-Chip, Network-on-Chip, Software-Defined Networks, and Artificial Intelligence can be physically, logically, and contextually incorporated to deliver improved computation and networking outcomes. |
| DOI | 10.1109/SDS57574.2022.10062950 |
| Citation Key | aljaafreh_optimizing_2022 |
Optimizing System-on-Chip Performance Using AI and SDN: Approaches and Challenges