NS2 IEEE Projects
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NS2 IEEE Projects for Final Year Engineering Students
I. NS2 based MANET
- PROVEST: Provenance-based Trust Model for Delay Tolerant Networks. (IEEE 2018)
- An Evolutionary Self-Cooperative Trust Scheme against Routing Disruptions in MANETs. (IEEE 2018)
- A Unified Framework of Clustering Approach in Vehicular Ad Hoc Networks. (IEEE 2018)
- Bandwidth-Satisfied and Coding-Aware Multicast Protocol in MANETs. (IEEE 2018)
- An Online Mechanism for Detection of Gray-Hole Attacks on PMU Data. (IEEE 2018)
II. NS2 based WSN
- Distributed Clustering-Task Scheduling for Wireless Sensor Networks Using Dynamic Hyper Round Policy (IEEE 2018).
- Denial of Service (DoS) Defence for Resource Availability in Wireless Sensor Networks. (IEEE 2018)
- Centralized Trust Based Secure Routing in Wireless Networks. (IEEE 2018)
III. NS2 based NETWORK SECURITY
- Zero MAC Latency Sensor Networking for Cyber-Physical Systems. (IEEE 2018)
- A Survey of Physical Layer Security Techniques for 5G Wireless Networks and Challenges Ahead. (IEEE 2018)
- Forward Collision Vehicular Radar with IEEE 802.11: Feasibility Demonstration through Measurements. (IEEE 2018)
- Using Bayesian Networks for Probabilistic Identification of Zero-day Attack Paths. (IEEE 2018)
IV. NS2 based SDN
- An Effective Approach to Controller Placement in Software-Defined Wide Area Networks. (IEEE 2018)
- Privacy-Preserving DDoS Attack Detection Using Cross-Domain Traffic in Software Defined Networks. (IEEE 2018)
- Towards Bayesian-based Trust Management for Insider Attacks in Healthcare Software- Defined Networks. (IEEE 2018)
V. NS2 based VANET
- Key Distribution Based on Phase FluctuationBetween Polarization Modes in Optical Channel. (IEEE 2018)
- Distributed Social Welfare Maximization in Urban Vehicular Participatory Sensing Systems. (IEEE 2018)
- A Secure and Efficient Authentication Technique for Vehicular Ad-Hoc Network. (IEEE 2018)
- Reliable Cooperative Authentication for Vehicular Networks (IEEE 2018)
- Distributed Privacy-Preserving Collaborative Intrusion Detection Systems For VANETs. (IEEE 2018)
- Data Uploading in Hybrid V2V/V2I Vehicular Networks: Modeling and Cooperative Strategy. (IEEE 2018)
- A Novel Infrastructure-Based Worm Spreading Countermeasure for Vehicular Networks. (IEEE 2018)
VI. NS2 based BODY AREA NETWORK
- Energy-efficient and Distributed Network Management Cost Minimization in Opportunistic Wireless Body Area Network. (IEEE 2018)
- Certificateless Public Auditing Scheme for Cloud-Assisted Wireless Body Area Networks. (IEEE 2018)
VII. NS2 based PROTOCOL ANALYSIS
- Theoretical Modeling and Analysis of Magnetic Induction Communication in Wireless Body Area Networks (WBANs). (IEEE 2018)
- A Cooperative Clustering Protocol with Duty Cycling for Energy Harvesting Enabled Wireless Sensor Networks. (IEEE 2018)
VIII. NS2 based UNDERWATER SENSOR NETWORK
- Distributed acoustic sensor using broadband weak FBG array for large temperature tolerance. (IEEE 2018)
- Compressive Sampling and Reconstruction of Acoustic Signal in Underwater Wireless Sensor Networks. (IEEE 2018)
- Interference-Free Graph-Based TDMA Protocol for Underwater Acoustic Sensor Networks. (IEEE 2018)
Networks have always been the hot cake of research for several years. From wired networks to wireless networks, several researches continue to be published in IEEE Journals and Conferences every year. Surprisingly, very few advanced tools are available for networks related simulations. When it comes to networks, NS2 has always topped the simulation chart. It comes pre-packaged with several protocol implementations like AODV,AOMDV etc , so that a researcher could spend more time on what he is planning to implement.
Why NS2 at Uniq?
We suggest the best ieee 2016 ns2 projects in chennai for final year ece students. We do not stop guiding only ieee 2016 final year ns2 projects, In addition we train students in ns2 technologies and implement own ns2 project ideas also.An integral part of any NS2 simulation are the trace file and nam file it generates. Among these, the trace file is the heart of simulation as it contains the simulation events that took place every second.
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This is not a research and is merely a demo. We, in UNIQ, do an in-depth analysis of these trace files by employing code in perl and awk to mine valuable information from them. We guarantee that the code we deliver to you is of perfect quality, which no other institute strives to achieve.
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