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Re: Ph D Entrance Exam in RGPV
The syllabus for Doctor of Philosophy (Ph.D.) Programme Entrance Exam offered by RGPV or Rajiv Gandhi Proudyogiki Vishwavidyalaya is as follows: Common for CSE/IT/CA Algorithms: Algorithms and complexity; Combinatorics and graph theory; Geometric Algorithms, Parallel and Distributed Algorithms, Randomized Algorithms, Algorithms for Biometric Based Identification, Computational Biology, Bioinformatics and streaming data. Computer Architecture : Embedded systems , Parallel and Distributed Computation, Embedded Computing Design ,Parallel Computing Structures , Parallel Algorithm for Array processors , Scheduling and load balancing in multiprocessor Systems , Multiprocessing control and algorithm, Real time and fault Tolerant Computing. Computer Networks: Performance modeling, Routers and routing, analysis and design of wired and wireless networks, MAC sub layer, Wireless sensor networks: Implementation and verification of network security protocols, data management, communication and energy efficiency issues in Sensor Networks, Design of content distribution networks for data dissemination, Network algorithms, Quality of service protocols, Mobile Computing, Voice Routing, Voice over IP, RFID networks, Enterprise networks, Access and Broadband networks, Hyper media. Protocols, Network performance and analysis, IPv6, Internet Technologies, Cryptography, Biometrics ,Intrusion Detection System and Firewalls. Software Engineering : Object oriented software development; Component architectures. Reengineering of software; systems analysis and design; MIS systems; Project management; Decision Support System , Quality assurance , Software Testing , Metrics and Models for Software Architecture, Software Fault Tolerance ,Quantitative approaches to project-and process management, Design Methodologies, Formal Specification . Database Management Systems : Object oriented, temporal and parallel databases; Query optimization and transaction management; Real time databases systems, indexing multidimensional data, distributed database systems; data dissemination systems; data warehousing and mining . Integrated mining with relational DBMS, Temporal mining, Integrating mining with OLAP. |
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