1. Final Year Project List for the Year 2012
S.No Project Title Description
1 Decremental algorithm for Routing in a stochastic and dynamic (time-dependent)
adaptive routing incorporating network is a crucial transportation problem. A new variant
traveler information of adaptive routing, which assumes perfect online
information of continuous real-time link travel time, is
proposed. Driver's speed profile is taken into consideration
to realistically estimate travel times, which also involves the
stochasticity of links in a dynamic network. An adaptive
approach is suggested to tackle the continuous dynamic
shortest path problem. A decremental algorithm is
consequently developed to reduce optimization time. The
impact of the proposed adaptive routing and the
performance of the decremental approach are evaluated in
static and dynamic networks under different traffic
conditions. The proposed approach can be incorporated into
vehicle navigation systems.
2 Design a Global authentication Self-explanatory, can be discussed further
system for Distributed Wireless
Networks
3 Design an IP-IP tunnel for Self-explanatory, can be discussed further
remote authentication for
resource utilization
4 Decryptiong GSM encryption Require Radio Receiver(hardware) and GSM basic concepts
using Programmable Radio
Receivers
5 GSM Speech Coder Indirect GSM speech coder indirect identification algorithm based on
Identification Algorithm sending novel identification pilot signals through the GSM
speech channel. Each GSM subsystem disturbs identification
pilot, while speech coder uniquely changes the tempo-
spectral characteristics of the proposed pilot signal. Speech
coder identification algorithm identifies speech coder with
the usage of robust linear frequency cepstral coefficient
(LFCC) feature extraction procedure and fast artificial neural
networks. First step of speech coder identification algorithm
is the exact position detection of the identification pilot
signal using normalized cross correlation approach. Next
stage is time-domain windowing of the input signal to
convolve each frame of the input speech signal and window
spectrum. Consecutive step is a short-time Fast Fourier
Transformation to produce the magnitude spectrum of each
windowed frame. Further, a noise reduction with spectral

2. subtraction based on spectral smoothing is carried out. In
last steps we perform the frequency filtering and Discrete
Cosine Transformation to receive 24 uncorrelated cepstral
coefficients per frame as a result. Speech coder
identification is completed with fast artificial neural network
classification using the input feature vector of 24 LFCC
coefficients, giving a result of identified speech coder.
6 Distributed fault detection of Wireless Sensor Networks (WSNs) have become a new
wireless sensor networks information collection and monitoring solution for a variety
of applications. Faults occurring to sensor nodes are
common due to the sensor device itself and the harsh
environment where the sensor nodes are deployed. In order
to ensure the network quality of service it is necessary for
the WSN to be able to detect the faults and take actions to
avoid further degradation of the service.
7 Efficient code distribution in The need to re-programme a wireless sensor network may
wireless sensor networks arise from changing application requirements, bug fixes, or
during the application development cycle. Once deployed, it
will be impractical at best to reach each individual node.
Thus, a scheme is required to wirelessly re-programme the
nodes.
8 A novel agent-based user- Wireless sensor networks generally have three kinds of
network communication model objects: sensor nodes, sinks, and users that send queries and
in wireless sensor networks receive data via the sinks. In addition, the user and the sinks
are mostly connected to each other by infrastructure
networks. The users, however, should receive the data from
the sinks through multi-hop communications between
disseminating sensor nodes if such users move into the
sensor networks without infrastructure networks. To
support mobile users, previous work has studied various
user mobility models. Nevertheless, such approaches are
not compatible with the existing data-centric routing
algorithms, and it is difficult for the mobile users to gather
data efficiently from sensor nodes due to their mobility
You can also present any other idea relevant to Data Communication,
Communication Networks, Wireless Networks or Digital Communication
for further discussion