Wireless sensor network ns2 code
Wireless sensor network ns2 code is used to simulate the network concepts. Ns2 is based on c++ program. Design and code is two division of the ns2 tool. For design we can use the scripting languages like tcl / tk.
Wireless sensor network ns2 code
C++ is the common program language for ns2 tool. Otcl is used to connect the c++ codes into the ns2. All protocols can be develop using the c++ coding. Nam file is used to interface the Color, Link manipulation, Topology layout, Protocol state, Misc, Node manipulation.
Wireless sensor network ns2 codes
Network simulator 2 have number of features, here we list out some Multicast, Areas in wired domain, Full TCP, Applications like web-mining, LAN, Wireless domain, Emulator, Ad hoc routing, Connect simulator in real time network, Send and receive live packets, Satellite networking, Diffserv/intserv, Mobile IP, Sensor networks.
Wireless sensor networks ns2 code
There are variety of components used in ns2 like nam, ns, xgraph. Major benefit for using the network simulator 2 we can calculate any kind of the parameter results. Xgraph is provide the major support for get the accurate results.
Wireless sensor network ns2 code:
- Performance analysis of transmitting H.263 over DCCP
- Performance Evaluation and Optimization of NCOR Methods in Wireless Mesh Networks
- Optimization based queue management for opportunistic network coding
- An efficient adaptive Cross-Layer interaction mechanism for TCP traffic over heterogeneous networks
- An Energy-Efficient Broadcast Protocol in MANETs: Design and Evaluation
- Wireless sensor nodes for long range surveillance using MIMO
- Performance complexity of raptor codes in TCP/IP-based wireless networks
- Improve the Throughput of AODV Based on Network Coding Idea
- Improving decoding efficiency of opportunistic network coding via efficient data caching
- Generic Application Level Rate Control for Scalable Video Using Shadow Probing
- Distributed channel access schemes for multi-channel ALOHA cognitive radio networks
- Fine-Grained Indoor Localization Using Single Access Point With Multiple Antennas
- A classification tree-based system for multi-sensor train approach detection
- Analysis and Optimization of Random Sensing Order in Cognitive Radio Networks
- FIT: On-the-fly, in-situ training with sensor data for SNR-based rate selection
- Computer vision for green and secure cooperative augmented reality in Next Generation Converged Wireless Networks
- Dynamic active area clustering with inertial information for fingerprinting based indoor localization systems
- Implementing Intelligent Traffic Control System for Congestion Control, Ambulance Clearance, and Stolen Vehicle Detection
- A framework to support real-time applications over IEEE802.15.4 DSME
- Multiwavelength Hybrid Fiber Raman/Parametric Linear Oscillator
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