B. Rajendra Naik

Work place: Department of ECE, University College of Engineering, Osmania University, Hyderabad, Telangana, India

E-mail: rajendranaikb@gmail.com


Research Interests: Image Processing


B. Rajendra Naikreceived his Bachelor’s degree in Electronics and Communication Engineering from Nagarjuna University, Andhra Pradesh, India, and Master’s in Digital Systems from Osmania University, Hyderabad, India. He received his Ph.D. degree also from Osmania University. He is working as a Professor in the Department of Electronics and Communication Engineering at University College of Engineering, Osmania University. He has published several papers in National and International Conferences and Journals. He worked as visiting Researcher at Tokyo Metro Politan University, Japan in 2010. He is presently guiding Ph.D. students in the area of VLSI and Image Processing.

Author Articles
Prediction of Intermittent Failure by Presage Debacle Model in Network on Chip

By Sangeeta Singh J V R Ravindra B. Rajendra Naik

DOI: https://doi.org/10.5815/ijcnis.2022.04.06, Pub. Date: 8 Aug. 2022

With the emergence of deep sub-micron technology, the reliability issues in on-chip interconnect has enormously increased. This includes single event upsets, like soft errors, and hard faults which are rapidly becoming important factors to be considered. Aggressive technology scaling renders these architectures vulnerable to system performance, intermittent failure, capacitive crosstalk, and power dissipation problem. To improve the performance of the area and power consumption along with bandwidth, throughput and latency, a Buffer Potency Power Gating Technique is carried out to predict the Intermittent Failure by Presage Debacle Model in Network on Chip. In the Presage Debacle Model, the links present in the application-specific topology are provided with real application traffic to assist in prediction of the intermittent failure. By predicting the failure, the output of the model provides the power dissipated over the connection of the application link. Then the crosstalk noise in the topology is reduced by the Adaption of Simulated Annealing (SA) based Particle Swarm Optimization (PSO) congruence algorithm. The optimization congruence algorithm assigns each task in the application software to each node in the topology to determine the network's optimal output. It continuously changes the task park position in the topology system and reduces the crosstalk of the NoC. Consecutively, the area and power consumption are minimized by Buffer Potency Power Gating Technique. Buffer efficiency is increased and the power-gating is a practical way to mitigate NoC power control schemes properly and effectively without any loss in performance. Thus the prediction of intermittent failure is obtained by utilizing NoC to improve the performance of area and power consumption.

[...] Read more.
Other Articles