S
S. Sitharama Iyengar
Researcher at Indian Institute of Technology Ropar
Publications - 794
Citations - 15356
S. Sitharama Iyengar is an academic researcher from Indian Institute of Technology Ropar. The author has contributed to research in topics: Wireless sensor network & Key distribution in wireless sensor networks. The author has an hindex of 53, co-authored 776 publications receiving 13751 citations. Previous affiliations of S. Sitharama Iyengar include Jackson State University & Manipal Hospitals.
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Asynchronous production systems for real-time expert systems
TL;DR: This paper elaborates on the architectural, operational and implementational ramifications of Asynchronous Production Systems and an example of an APS-based, distributed expert system is presented to handle the task of autonomous navigation in the presence of unexpected, moving obstacles in a mobile robot.
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Concurrent maintenance of data systems for telecommunications
TL;DR: Developpement d'un code pour les processus en premier plan et en arriere-plan faisant intervenir l'approche «concurrence grossiere-concur Lawrence finie» de Dijkstra et les conditions de Jones.
Journal ArticleDOI
Index Generation and Secure Multi-user Access Control over an Encrypted Cloud Data
Raghavendra S,K. Meghana,P.A. Doddabasappa,C M Geeta,Rajkumar Buyya,K. R. Venugopal,S. Sitharama Iyengar,Lalit M. Patnaik +7 more
TL;DR: A secure multi-owner data sharing for dynamic group in the cloud with RSA Chinese Remainder Theorem (RSA-CRT) encryption technique and substring index generation method is proposed.
Modeling Memetics Using Edge Diversity.
TL;DR: This paper provides an artificial framework for studying the meme propagation patterns and proposes a meme spreading model based on the diversity of edges in the network, validated by the propagation of the Higgs boson meme on Twitter as well as many real world social networks.
Proceedings ArticleDOI
Adaptive cooperative spectrum sensing based on a novel robust detection algorithm
TL;DR: The ROC (receiver-operating characteristic) curves show that the new adaptive cooperative spectrum sensing scheme, which is based on a novel detection algorithm involving JB (Jarque-Bera) statistic, is more robust than that based on the energy-detection spectrum sensing algorithm.