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Nirwan Ansari
Researcher at New Jersey Institute of Technology
Publications - 743
Citations - 25453
Nirwan Ansari is an academic researcher from New Jersey Institute of Technology. The author has contributed to research in topics: Quality of service & Network packet. The author has an hindex of 71, co-authored 708 publications receiving 21488 citations. Previous affiliations of Nirwan Ansari include Hebei University of Engineering & Purdue University.
Papers
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Journal ArticleDOI
Reversible data hiding
TL;DR: It is proved analytically and shown experimentally that the peak signal-to-noise ratio of the marked image generated by this method versus the original image is guaranteed to be above 48 dB, which is much higher than that of all reversible data hiding techniques reported in the literature.
Journal ArticleDOI
A genetic algorithm for multiprocessor scheduling
Edwin Hou,Nirwan Ansari,Hong Ren +2 more
TL;DR: An efficient method based on genetic algorithms is developed to solve the multiprocessor scheduling problem and results comparing the proposed genetic algorithm, the list scheduling algorithm, and the optimal schedule using random task graphs, and a robot inverse dynamics computational task graph are presented.
Book ChapterDOI
Reversible data hiding
TL;DR: A theoretical proof and numerous experiments show that the PSNR of the marked image generated by this method is always above 48 dB, which is much higher than other reversible data hiding algorithms.
Journal ArticleDOI
EdgeIoT: Mobile Edge Computing for the Internet of Things
Xiang Sun,Nirwan Ansari +1 more
TL;DR: A novel approach to mobile edge computing for the IoT architecture, edgeIoT, to handle the data streams at the mobile edge by proposing a hierarchical fog computing architecture in each fog node to provide flexible IoT services while maintaining user privacy.
Journal ArticleDOI
Dynamic Service Provisioning in Elastic Optical Networks With Hybrid Single-/Multi-Path Routing
TL;DR: The simulation results have demonstrated that the proposed HSMR schemes can effectively reduce the bandwidth blocking probability (BBP) of dynamic RMSA, as compared to two benchmark algorithms that use single-path routing and split spectrum.