MTech in Computer Science & Engineering
At the post-graduate level, the department offers 2-year degree course in Master of Technology (M.Tech.) in Computer Science & Engineering with an intake of 20 students. The objective of the programme is to provide the students with an opportunity to satiate their hunger for higher learning. The programme provides intensive training to the students at advanced level to enable them to take up research & development activities. Personal attention is paid to each student with intensive practical training. The course curriculum is so designed as to cater to the needs of the industry as well as the research & development organizations. The programme helps the students to specialize in an area of their choice, thus leading to their rise in the academic & professional societies and enabling them to carve a niche for themselves. Some of the obligatory courses are as following: Advanced Computer Networks Prerequisites: Computer Networks Introduction to basic models, TCP/IP model and its protocols in detail, IP, TCP, Addressing and subnetting. Flow and Congestion Control; Window and Rate Based Schemes, Decbit, TCP. ATM, ABR, hop-by-hop schemes, Quality of Service: in ATM, IETF integrated services model, Differentiated Services Model. Flow identification, Packet Classifiers and Filters. Scheduling. Network Management: ASN, SNMP, CMIP. Issues in the management of large networks. Multicast: IGMP, PIM, DVMRP, Mobility: Mobile IP. And TCP. The architecture of High-Performance Computer Systems Prerequisites: Operating System Concepts. Contents: Classification of parallel computing structures; Instruction level parallelism - static and dynamic pipelining, improving branch performance, superscalar and VLIW processors; High-performance memory system; Shared memory multiprocessors and cache coherence; Multiprocessor interconnection networks; Performance modelling; Issues in programming multiprocessors; Data-parallel architectures. Modeling & Simulation Pre-requisites: None Contents. Introduction of modelling, Basics and Classification of simulation models; The simulation process; System investigation, model formulation, validation and translation; Time flow mechanisms; Design of computer simulation experiments; Simulation of complex discrete-event systems with applications in industrial and service organizations. Tactical planning and management aspects, Random variable generation and analysis.
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Last updated January 30, 2018