Bio-Inspired Fault-Tolerant Algorithms for Network-on-Chip

Informationen zum Autor Dr. Muhammad Athar Javed Sethi is an Assistant Professor at the Department of Computer Systems Engineering, University of Engineering and Technology (UET), Peshawar, Pakistan. He received the Bachelor of Sciences in Computer Information Systems Engineering (honors) from the UET Peshawar, Pakistan in 2004. He had done Master of Sciences in Computer Systems Engineering from the same university in 2008. He completed his Ph.D. at Universiti Teknologi PETRONAS (UTP), Malaysia in Department of Electrical & Electronic Engineering in 2016. He was able to get different scholarships to pursue and continue his studies. Dr. Sethi got IEEE student best paper award in the year 2013 and a most downloaded paper award from Elsevier in consecutive two years 2016-2017 for two different papers. His research interests include network on chip (NoC), interconnection networks, computer architecture, and embedded systems. Dr. Sethi, has published numerous manuscripts in reputable Journals, Conferences and Books. Currently, he is also actively involved in technical program committees of various international conferences. He is serving as Associate Editor at EAI Endorsed Transactions on Context-aware Systems & Applications and at EAI Endorsed Transactions on Ambient Systems. Klappentext This book exclusively presents in-depth information regarding bio-inspired algorithms solving real world problems focussing on fault-tolerant algorithms inspired by the biological brain and implemented on NoC. It further documents the bio-inspired algorithms in general and more specifically, in the design of NoC. Zusammenfassung This book exclusively presents in-depth information regarding bio-inspired algorithms solving real world problems focussing on fault-tolerant algorithms inspired by the biological brain and implemented on NoC. It further documents the bio-inspired algorithms in general and more specifically, in the design of NoC. Inhaltsverzeichnis 1. Introduction. 2. In-depth Review of Network on Chip. 3. Bio-inspired algorithms and implementation. 4. Bio-inspired NoC fault-tolerant algorithms. 5. Analysis of bio-inspired NoC fault-tolerant algorithms. 6. Conclusion and future work....

Auteur

Dr. Muhammad Athar Javed Sethi is an Assistant Professor at the Department of Computer Systems Engineering, University of Engineering and Technology (UET), Peshawar, Pakistan. He received the Bachelor of Sciences in Computer Information Systems Engineering (honors) from the UET Peshawar, Pakistan in 2004. He had done Master of Sciences in Computer Systems Engineering from the same university in 2008. He completed his Ph.D. at Universiti Teknologi PETRONAS (UTP), Malaysia in Department of Electrical & Electronic Engineering in 2016. He was able to get different scholarships to pursue and continue his studies. Dr. Sethi got IEEE student best paper award in the year 2013 and a most downloaded paper award from Elsevier in consecutive two years 2016-2017 for two different papers. His research interests include network on chip (NoC), interconnection networks, computer architecture, and embedded systems. Dr. Sethi, has published numerous manuscripts in reputable Journals, Conferences and Books. Currently, he is also actively involved in technical program committees of various international conferences. He is serving as Associate Editor at EAI Endorsed Transactions on Context-aware Systems & Applications and at EAI Endorsed Transactions on Ambient Systems.

Texte du rabat

This book exclusively presents in-depth information regarding bio-inspired algorithms solving real world problems focussing on fault-tolerant algorithms inspired by the biological brain and implemented on NoC. It further documents the bio-inspired algorithms in general and more specifically, in the design of NoC.

Contenu

1. Introduction. 2. In-depth Review of Network on Chip. 3. Bio-inspired algorithms and implementation. 4. Bio-inspired NoC fault-tolerant algorithms. 5. Analysis of bio-inspired NoC fault-tolerant algorithms. 6. Conclusion and future work.