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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
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

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Final year project list for the year 2012

  • 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