16 research outputs found
เชตเชฟเชเซเชเชพเชจ เช เชจเซ เชเซเชเชจเซเชฒเซเชเชฟเชจเชพ เช เชงเชฏเชพเชชเชจ เชฎเชพเชเซ เชเชฎเซเชชเซเชฏเซเชเชฐ เชเชเชกเซเชก เชเชจเซเชธเซเชเซเชฐเชเชถเชจ (CAD) เชเชพเชฐเซเชฏเชเซเชฐเชฎ, เชตเชฐเซเชเชเชพเชฐเซเชก เช เชจเซ เชเซเชฅ เช เชงเซเชฏเชพเชชเชจ เชชเชงเซเชงเชคเชฟเชจเซ เช เชธเชฐเชเชพเชฐเชเชคเชพ
เชเชเชจเชพ เชฏเซเชเชจเซ เชฎเชพเชนเชฟเชคเซ เช
เชจเซ เชชเซเชฐเชคเซเชฏเชพเชชเชจเชจเชพ เชฏเซเชเชฅเซ เชเชณเชเชพเชฏ เชเซ. เชเซเชตเชจเชจเชพ เชคเชฎเชพเชฎ เชเซเชทเซเชคเซเชฐเซ เชชเชนเซเชฒเชพเช เชเชฐเชคเชพเช เชตเชงเซ เชฎเชพเชนเชฟเชคเซ เชชเซเชฐเชพเชชเซเชฏ เชฌเชจเซ เชเซ. เชเชจเซ เช
เชธเชฐ เชถเชฟเชเซเชทเชฃเชจเชพ เชเซเชทเซเชคเซเชฐเซ เชชเชฃ เชเซเชตเชพ เชฎเชณเซ เชเซ. เชถเชฟเชเซเชทเชฃเชจเซ เชชเซเชฐเชเซเชฐเชฟเชฏเชพเชฎเชพเช เชตเชฟเชฆเซเชฏเชพเชฐเซเชฅเซ เชเซเชเชฒเซ เชธเชเซเชฐเชฟเชฏ เชฐเชนเซ เชคเซเชเชฒเซเช เช
เชงเซเชฏเชฏเชจ เชคเซเชเชธเซเชตเซ เช
เชจเซ เช
เชธเชฐเชเชพเชฐเช เชฌเชจเซ เชเซ เช
เชจเซ เชตเชฟเชฆเซเชฏเชพเชฐเซเชฅเซเชจเซ เชเชเชคเชฐเชฟเช เชถเชเซเชคเชฟ เชตเชฟเชเชธเซ เชเซ. เชธเซเชต-เช
เชงเซเชฏเชฏเชจเชจเซ เชเซเชฆเซ-เชเซเชฆเซ เชชเซเชฐเชฏเซเชเซเชคเชฟเช เชตเชฟเชฆเซเชฏเชพเชฐเซเชฅเซเชเชฎเชพเช เชฐเชนเซเชฒเชพ เชตเซเชฏเชเซเชคเชฟเช เชคเชซเชพเชตเชคเซเชจเซ เชงเซเชฏเชพเชจเชฎเชพเช เชฐเชพเชเซเชจเซ เชธเซเชต-เชเชคเชฟเช เชเชเชณ เชตเชงเชตเชพเชจเซ เชชเซเชฐเซเชฐเชฃเชพ เชชเซเชฐเซ เชชเชพเชกเซ เชเซ. เชตเชฟเชเซเชเชพเชจ เช
เชจเซ เชเซเชเชจเซเชฒเซเชเชฟ เชเชตเซ เชตเชฟเชทเชฏ เชเซ เชเซ เชเซเชฎเชพเช เชถเชฟเชเซเชทเชฃเชจเซ เชตเชงเซ เชฐเชธเชชเซเชฐเชฆ เชฌเชจเชพเชตเชตเชพ เชฎเชพเชเซ เชตเชฟเชตเชฟเชง เชถเซเชเซเชทเชฃเชฟเช เชธเชพเชงเชจเซ เช
เชจเซ เชชเชงเซเชงเชคเชฟเชเชจเซ เชเชชเชฏเซเช เชฅเช เชถเชเซ เชเซ. เชชเซเชฐเชฏเซเชเช เชชเซเชฐเชพเชฃเซเชถเชพเชธเซเชคเซเชฐเชจเชพ เช
เชจเซเชธเซเชจเชพเชคเช เชนเซเชตเชพเชฅเซ เช เชตเชฟเชทเชฏ เชชเซเชฐเชคเซเชฏเซ เชตเชงเซ เชฒเชเชพเชต เชนเซเชฏ เช เชธเซเชตเชพเชญเชพเชตเชฟเช เชเซ. เชถเชฟเชเซเชทเชฃเชจเซ เชตเชงเซ เชฐเชธเชชเซเชฐเชฆ เชฌเชจเชพเชตเชตเชพ เชคเซเชฎเช เชตเชฟเชฆเซเชฏเชพเชฐเซเชฅเซเช เชธเซเชต-เชเชคเชฟเช เชเชเชณ เชตเชงเซ เช เชฎเชพเชเซ เชเชฎเซเชชเซเชฏเซเชเชฐ เชเชเชกเซเชก เชเชจเซเชธเซเชเซเชฐเชเชถเชจ (CAD) เชเชพเชฐเซเชฏเชเซเชฐเชฎ, เชตเชฐเซเชเชเชพเชฐเซเชก เช
เชจเซ เชเซเชฅ เช
เชงเซเชฏเชพเชชเชจเชจเซ เช
เชธเชฐเชเชพเชฐเชเชคเชพ เชถเซเชเซเชทเชฃเชฟเช เชธเชฟเชงเซเชงเชฟเชจเชพ เชธเชเชฆเชฐเซเชญเชฎเชพเช เชเชเชพเชธเชตเชพ เชชเซเชฐเชธเซเชคเซเชค เช
เชญเซเชฏเชพเชธ เชนเชพเชฅ เชงเชฐเซเชฏเซ เชนเชคเซ
PCA based components selection criteria for computationally efficient Physical Layer Key Generation (PLKG) system
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
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
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
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
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
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