D
Danda B. Rawat
Researcher at Howard University
Publications - 402
Citations - 6604
Danda B. Rawat is an academic researcher from Howard University. The author has contributed to research in topics: Computer science & Cognitive radio. The author has an hindex of 33, co-authored 312 publications receiving 4286 citations. Previous affiliations of Danda B. Rawat include Old Dominion University & University of Washington.
Papers
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Journal ArticleDOI
Software Defined Networking Architecture, Security and Energy Efficiency: A Survey
Danda B. Rawat,Swetha Reddy +1 more
TL;DR: This paper presents various security threats that are resolved by SDN and new threats that arise as a result of SDN implementation, and the main ongoing research efforts, challenges, and research trends in this area are discussed.
Journal ArticleDOI
Enhancing VANET Performance by Joint Adaptation of Transmission Power and Contention Window Size
TL;DR: A new scheme for dynamic adaptation of transmission power and contention window (CW) size to enhance performance of information dissemination in Vehicular Ad-hoc Networks (VANETs) and features significantly better throughput and lower average end-to-end delay compared with a similar scheme with static parameters.
Journal ArticleDOI
Advances on Security Threats and Countermeasures for Cognitive Radio Networks: A Survey
Rajesh K. Sharma,Danda B. Rawat +1 more
TL;DR: This paper presents the recent advances on security threats/attacks and countermeasures in CRNs focusing more on the physical layer by categorizing them in terms of their types, their existence in the CR cycle, network protocol layers, and game theoretic approaches.
BookDOI
Industrial Internet of Things: Cybermanufacturing Systems
TL;DR: This book develops the core system science needed to enable the development of a complex industrial internet of things/manufacturing cyber-physical systems (IIoT/M-CPS) and gathers contributions from leading experts in the field with years of experience in advancing manufacturing.
Proceedings ArticleDOI
A Novel AI-enabled Framework to Diagnose Coronavirus COVID-19 using Smartphone Embedded Sensors: Design Study
Halgurd S. Maghded,Kayhan Zrar Ghafoor,Ali Safaa Sadiq,Kevin Curran,Danda B. Rawat,Khaled M. Rabie +5 more
TL;DR: In this article, a new framework is proposed to detect COVID-19 using built-in smartphone sensors, which provides a low-cost solution, since most of radiologists have already held smartphones for different daily-purposes.