16 research outputs found

    เชตเชฟเชœเซเชžเชพเชจ เช…เชจเซ‡ เชŸเซ‡เช•เชจเซ‹เชฒเซ‹เชœเชฟเชจเชพ เช…เชงเชฏเชพเชชเชจ เชฎเชพเชŸเซ‡ เช•เชฎเซเชชเซเชฏเซ‚เชŸเชฐ เชเชˆเชกเซ‡เชก เช‡เชจเซเชธเซเชŸเซเชฐเช•เชถเชจ (CAD) เช•เชพเชฐเซเชฏเช•เซเชฐเชฎ, เชตเชฐเซเช•เช•เชพเชฐเซเชก เช…เชจเซ‡ เชœเซ‚เชฅ เช…เชงเซเชฏเชพเชชเชจ เชชเชงเซเชงเชคเชฟเชจเซ€ เช…เชธเชฐเช•เชพเชฐเช•เชคเชพ

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    เช†เชœเชจเชพ เชฏเซเช—เชจเซ‡ เชฎเชพเชนเชฟเชคเซ€ เช…เชจเซ‡ เชชเซเชฐเชคเซเชฏเชพเชชเชจเชจเชพ เชฏเซเช—เชฅเซ€ เช“เชณเช–เชพเชฏ เช›เซ‡. เชœเซ€เชตเชจเชจเชพ เชคเชฎเชพเชฎ เช•เซเชทเซ‡เชคเซเชฐเซ‡ เชชเชนเซ‡เชฒเชพเช‚ เช•เชฐเชคเชพเช‚ เชตเชงเซ เชฎเชพเชนเชฟเชคเซ€ เชชเซเชฐเชพเชชเซเชฏ เชฌเชจเซ€ เช›เซ‡. เช†เชจเซ€ เช…เชธเชฐ เชถเชฟเช•เซเชทเชฃเชจเชพ เช•เซเชทเซ‡เชคเซเชฐเซ‡ เชชเชฃ เชœเซ‹เชตเชพ เชฎเชณเซ‡ เช›เซ‡. เชถเชฟเช•เซเชทเชฃเชจเซ€ เชชเซเชฐเช•เซเชฐเชฟเชฏเชพเชฎเชพเช‚ เชตเชฟเชฆเซเชฏเชพเชฐเซเชฅเซ€ เชœเซ‡เชŸเชฒเซ‹ เชธเช•เซเชฐเชฟเชฏ เชฐเชนเซ‡ เชคเซ‡เชŸเชฒเซเช‚ เช…เชงเซเชฏเชฏเชจ เชคเซ‡เชœเชธเซเชตเซ€ เช…เชจเซ‡ เช…เชธเชฐเช•เชพเชฐเช• เชฌเชจเซ‡ เช›เซ‡ เช…เชจเซ‡ เชตเชฟเชฆเซเชฏเชพเชฐเซเชฅเซ€เชจเซ€ เช†เช‚เชคเชฐเชฟเช• เชถเช•เซเชคเชฟ เชตเชฟเช•เชธเซ‡ เช›เซ‡. เชธเซเชต-เช…เชงเซเชฏเชฏเชจเชจเซ€ เชœเซเชฆเซ€-เชœเซเชฆเซ€ เชชเซเชฐเชฏเซเช•เซเชคเชฟเช“ เชตเชฟเชฆเซเชฏเชพเชฐเซเชฅเซ€เช“เชฎเชพเช‚ เชฐเชนเซ‡เชฒเชพ เชตเซˆเชฏเช•เซเชคเชฟเช• เชคเชซเชพเชตเชคเซ‹เชจเซ‡ เชงเซเชฏเชพเชจเชฎเชพเช‚ เชฐเชพเช–เซ€เชจเซ‡ เชธเซเชต-เช—เชคเชฟเช เช†เช—เชณ เชตเชงเชตเชพเชจเซ€ เชชเซเชฐเซ‡เชฐเชฃเชพ เชชเซ‚เชฐเซ€ เชชเชพเชกเซ‡ เช›เซ‡. เชตเชฟเชœเซเชžเชพเชจ เช…เชจเซ‡ เชŸเซ‡เช•เชจเซ‹เชฒเซ‹เชœเชฟ เชเชตเซ‹ เชตเชฟเชทเชฏ เช›เซ‡ เช•เซ‡ เชœเซ‡เชฎเชพเช‚ เชถเชฟเช•เซเชทเชฃเชจเซ‡ เชตเชงเซ เชฐเชธเชชเซเชฐเชฆ เชฌเชจเชพเชตเชตเชพ เชฎเชพเชŸเซ‡ เชตเชฟเชตเชฟเชง เชถเซˆเช•เซเชทเชฃเชฟเช• เชธเชพเชงเชจเซ‹ เช…เชจเซ‡ เชชเชงเซเชงเชคเชฟเช“เชจเซ‹ เช‰เชชเชฏเซ‹เช— เชฅเชˆ เชถเช•เซ‡ เช›เซ‡. เชชเซเชฐเชฏเซ‹เชœเช• เชชเซเชฐเชพเชฃเซ€เชถเชพเชธเซเชคเซเชฐเชจเชพ เช…เชจเซเชธเซเชจเชพเชคเช• เชนเซ‹เชตเชพเชฅเซ€ เช† เชตเชฟเชทเชฏ เชชเซเชฐเชคเซเชฏเซ‡ เชตเชงเซ เชฒเช—เชพเชต เชนเซ‹เชฏ เช เชธเซเชตเชพเชญเชพเชตเชฟเช• เช›เซ‡. เชถเชฟเช•เซเชทเชฃเชจเซ‡ เชตเชงเซ เชฐเชธเชชเซเชฐเชฆ เชฌเชจเชพเชตเชตเชพ เชคเซ‡เชฎเชœ เชตเชฟเชฆเซเชฏเชพเชฐเซเชฅเซ€เช“ เชธเซเชต-เช—เชคเชฟเช เช†เช—เชณ เชตเชงเซ‡ เช เชฎเชพเชŸเซ‡ เช•เชฎเซเชชเซเชฏเซ‚เชŸเชฐ เชเชˆเชกเซ‡เชก เช‡เชจเซเชธเซเชŸเซเชฐเช•เชถเชจ (CAD) เช•เชพเชฐเซเชฏเช•เซเชฐเชฎ, เชตเชฐเซเช•เช•เชพเชฐเซเชก เช…เชจเซ‡ เชœเซ‚เชฅ เช…เชงเซเชฏเชพเชชเชจเชจเซ€ เช…เชธเชฐเช•เชพเชฐเช•เชคเชพ เชถเซˆเช•เซเชทเชฃเชฟเช• เชธเชฟเชงเซเชงเชฟเชจเชพ เชธเช‚เชฆเชฐเซเชญเชฎเชพเช‚ เชšเช•เชพเชธเชตเชพ เชชเซเชฐเชธเซเชคเซเชค เช…เชญเซเชฏเชพเชธ เชนเชพเชฅ เชงเชฐเซเชฏเซ‹ เชนเชคเซ‹

    PCA based components selection criteria for computationally efficient Physical Layer Key Generation (PLKG) system

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    Data security is one of the prime concerns in wireless networks. PLKG has been emerging as an attractive alternative to traditional cryptographic techniques. PLKG is more computationally efficient than cryptography. Moreover, PLKG using Principal component analysis (PCA) as pre-processing may further save computations. This paper proposes three mechanisms to select components of PCA which are based on Information content, Mean and Histfit. Bit Disagreement Rate (BDR) is compared for each mechanism. Histfit based method is found to be best. Since only two components are supposed to be processed for key generation, it is computationally efficient/ power efficient too

    PCA Based Components Selection Criteria for Computationally Efficient Physical Layer Key Generation (PLKG) System

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    Data security is one of the prime concerns in wireless networks. PLKG has been emerging as an attractive alternative to traditional cryptographic techniques. PLKG is more computationally efficient than cryptography. Moreover, PLKG using Principal component analysis (PCA) as pre-processing may further save computations. This paper proposes three mechanisms to select components of PCA which are based on Information content, Mean and Histfit. Bit Disagreement Rate (BDR) is compared for each mechanism. Histfit based method is found to be best. Since only two components are supposed to be processed for key generation, it is computationally efficient/ power efficient too

    Collision Resolution Schemes with Nonoverlapped Contention Slots for Heterogeneous and Homogeneous WLANs

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    CSMA/CA-based DCF of 802.11 MAC layer employs a best-effort delivery model, in which stations compete for channel access with the same priority. In a heterogeneous network, providing different priorities to different applications for required quality of service is a challenging task, since heterogeneous conditions result in unfairness among stations and degradation in the throughput. This paper proposes a class of collision resolution schemes for 802.11 having contention window control with nonoverlapped contention slots. In the first scheme, window ranges of two consecutive stages are nonoverlapped, and it is called nonoverlapped contention slots (NOCS) scheme. In the other scheme, termed as NOCS-offset, an offset is introduced between window ranges of two stages. Selection of a random value by a station for its contention with discontinuous distribution results in reduced probability of collision. Analytical and simulation results show that the proposed scheme exhibits higher throughput and fairness with reduced delay and collision probability in homogeneous and heterogeneous networks. Performance of the proposed scheme is evaluated for mix traffic and high data rate environment with advanced back-off management techniques to meet the requirements of the present applications

    Collision Resolution Schemes with Nonoverlapped Contention Slots for Heterogeneous and Homogeneous WLANs

    No full text
    CSMA/CA-based DCF of 802.11 MAC layer employs a best-effort delivery model, in which stations compete for channel access with the same priority. In a heterogeneous network, providing different priorities to different applications for required quality of service is a challenging task, since heterogeneous conditions result in unfairness among stations and degradation in the throughput. This paper proposes a class of collision resolution schemes for 802.11 having contention window control with nonoverlapped contention slots. In the first scheme, window ranges of two consecutive stages are nonoverlapped, and it is called nonoverlapped contention slots (NOCS) scheme. In the other scheme, termed as NOCS-offset, an offset is introduced between window ranges of two stages. Selection of a random value by a station for its contention with discontinuous distribution results in reduced probability of collision. Analytical and simulation results show that the proposed scheme exhibits higher throughput and fairness with reduced delay and collision probability in homogeneous and heterogeneous networks. Performance of the proposed scheme is evaluated for mix traffic and high data rate environment with advanced back-off management techniques to meet the requirements of the present applications

    Energy Efficient Rate Adaptation Algorithm for FiWi Access Network

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    Abstract Similar to any telecommunication network, energy efficiency is a desirable feature for fiber wireless (FiWi) access networks. These networks have optical back end and wireless front end. Both ends may contribute for energy efficiency. This work focuses on front end of FiWi access network, which is IEEE 802.11a wireless local area network (WLAN). For energy saving WLAN uses power saving mode (PSM), in which sleeping opportunity of a station is increased. During sleep time, station remains switched off and results in reduction in energy required. However, it is also observed that during active period of transmission considerable energy is consumed, which is the function of rate of data transmission. More data rate results in more active energy consumption but less transmission delay and vice versa. In order to reduce active and hence total energy consumption, we tried to transmit the data at lower data rate, while maintaining transmission delay in tolerable limit. This paper presents an Energy Efficient Rate Adaptation Algorithm (EERAA) for the front end of fiber wireless access networks. Simulation results compare the energy efficiency and transmission delay of EERAA and various existing fixed data rate schemes. Proposed scheme offers good trade-off between energy efficiency and transmission delay

    Computation of Various QoS Parameters for FiWi Access Network

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    AbstractFiber wireless (FiWi) access network is one of the broad band access networks used to support multimedia applications and interactive services. However minimum QoS needs to be maintained by the network. In this paper a method has been proposed to compute the various network parameters such as packet delivery ratio (PDR), average delay and network throughput for a FiWi network, to ensure minimum QoS. This approach may be proved very useful in computing these parameters comprehensively for any algorithm related with research issues of FiWi network like ONU placement, survivability, energy efficient algorithms etc
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