The document discusses computing waiting times for queueing systems using mathematical models. It introduces concepts such as average waiting time, variance of waiting time, probability distribution functions of waiting time, and models like M/M/1 queues. It provides examples of applying these concepts and models to analyze single line and multiple line queues, and compares the performance of single vs multiple server systems.
A DELAY – CONSTRAINED IN MULTICAST ROUTING USING JIA ALGORITHMIJCI JOURNAL
The Distributed multicast routing protocol under delay constraints, is one of the software, which requires simultaneous transmission of message from a source to a group of destinations within specified time delay. For example. Video Conferencing system. Multicast routing is to find a routing tree which is routed from the source and contains all the destinations. The principle goal of multicast routing is to minimize the network cost. A tree with minimal overall cost is called a Steiner tree. Finding such tree is the principle of the NP complete.
Many inexpensive heuristic algorithms have been proposed for the Steiner tree problem. However, most of the proposed algorithms are centralized in nature. Centralized algorithm requires a central node to be responsible for computing the tree and this central node must have full knowledge about the global network. But, this is not practical in large networks. Therefore, existing algorithms suffer from the drawback such as heavy communication cost, long connection setup time and poor quality of produced routing trees. So far, a little work has been done on finding delay bounded Steiner tree in a distributed manner. An effort is made in this paper to this effect. The Study reveals that the drawbacks mentioned
above has been sufficiently reduced. This paper gives complete guidelines for authors submitting papers for the AIRCC Journals.
On Demand Bandwidth Reservation for Real- Time Traffic in Cellular IP Network...IDES Editor
As real-time traffic requires more attention, it
is given priority over non-real-time traffic in Cellular IP
networks. Bandwidth reservation is often applied to serve
such traffic in order to achieve better Quality of Service
(QoS). Evolutionary Algorithms are quite useful in
solving optimization problems of such nature. This paper
employs Genetic Algorithm (GA) for bandwidth
management in Cellular IP network. It compares the
performance of the model with another model used for
optimizing Connection Dropping Probability (CDP) using
Particle Swarm Optimization (PSO). Both models, GA
based and PSO based, try to minimize the Connection
Dropping Probability for real-time users in the network
by searching the free available bandwidth in the user’s
cell or in the neighbor cells and assigning it to the realtime
users. Alternatively, if the free bandwidth is not
available, the model borrows the bandwidth from nonreal
time-users and gives it to the real-time users.
Experimental results evaluate the performance of the GA
based model. The comparative study between both the
models indicates that GA based model has an edge over
the PSO based one.
ON THE PERFORMANCE OF INTRUSION DETECTION SYSTEMS WITH HIDDEN MULTILAYER NEUR...IJCNCJournal
Deep learning applications, especially multilayer neural network models, result in network intrusion detection with high accuracy. This study proposes a model that combines a multilayer neural network with Dense Sparse Dense (DSD) multi-stage training to simultaneously improve the criteria related to the performance of intrusion detection systems on a comprehensive dataset UNSW-NB15. We conduct experiments on many neural network models such as Recurrent Neural Network (RNN), Long-Short Term Memory (LSTM), Gated Recurrent Unit (GRU), etc. to evaluate the combined efficiency with each model through many criteria such as accuracy, detection rate, false alarm rate, precision, and F1-Score.
Mean Object Size Considering Average Waiting Latency in M/BP/1 SystemIJCNCJournal
This paper deals with the web object size which affects to the service time in multiple access environments. The M/BP/1 model can be considered because packets arrival and web service are Poission and Bound Pareto (BP) distribution respectively. We find mean object size which satisfies that the average waiting latency by deterministic model equals the mean queueing delay of the M/BP/1 model. Performance evaluation shows that the mean web object size is affected by file size bounds and shape parameter of BP distribution, however, the impact of link capacity is not significant. When the system load is low, web object size converges on half the maximum segment size (MSS). Our results can be applied to find mean web object size in the economic web service design.
Application Of Extreme Value Theory To Bursts PredictionCSCJournals
Bursts and extreme events in quantities such as connection durations, file sizes, throughput, etc. may produce undesirable consequences in computer networks. Deterioration in the quality of service is a major consequence. Predicting these extreme events and burst is important. It helps in reserving the right resources for a better quality of service. We applied Extreme value theory (EVT) to predict bursts in network traffic. We took a deeper look into the application of EVT by using EVT based Exploratory Data Analysis. We found that traffic is naturally divided into two categories, Internal and external traffic. The internal traffic follows generalized extreme value (GEV) model with a negative shape parameter, which is also the same as Weibull distribution. The external traffic follows a GEV with positive shape parameter, which is Frechet distribution. These findings are of great value to the quality of service in data networks, especially when included in service level agreement as traffic descriptor parameters.
Online learning algorithmes often have to operate in the presence of concept drifts. A recent study
revealed that different diversity levels in an ensemble of learning machines are required in order to maintain high
generalization on both old and new concepts. Inspired by this study and based on a further study of diversity with
different strategies to deal with drifts, so propose a new online ensemble learning approach called Diversity for
Dealing with Drifts (DDD).DDD maintains ensembles with different diversity levels and is able to attain better
accuracy than other approaches. Furthermore, it is very robust, outperforming other drift handling approaches in
terms of accuracy when there are false positive drift detections. It is always performed at least as well as
other drift handling approaches under various conditions, with very few exceptions. Presents an analysis of low
and high diversity ensembles combined with different strategies to deal with concept drift and proposes a new
approach (DDD) to handle drifts.
A DELAY – CONSTRAINED IN MULTICAST ROUTING USING JIA ALGORITHMIJCI JOURNAL
The Distributed multicast routing protocol under delay constraints, is one of the software, which requires simultaneous transmission of message from a source to a group of destinations within specified time delay. For example. Video Conferencing system. Multicast routing is to find a routing tree which is routed from the source and contains all the destinations. The principle goal of multicast routing is to minimize the network cost. A tree with minimal overall cost is called a Steiner tree. Finding such tree is the principle of the NP complete.
Many inexpensive heuristic algorithms have been proposed for the Steiner tree problem. However, most of the proposed algorithms are centralized in nature. Centralized algorithm requires a central node to be responsible for computing the tree and this central node must have full knowledge about the global network. But, this is not practical in large networks. Therefore, existing algorithms suffer from the drawback such as heavy communication cost, long connection setup time and poor quality of produced routing trees. So far, a little work has been done on finding delay bounded Steiner tree in a distributed manner. An effort is made in this paper to this effect. The Study reveals that the drawbacks mentioned
above has been sufficiently reduced. This paper gives complete guidelines for authors submitting papers for the AIRCC Journals.
On Demand Bandwidth Reservation for Real- Time Traffic in Cellular IP Network...IDES Editor
As real-time traffic requires more attention, it
is given priority over non-real-time traffic in Cellular IP
networks. Bandwidth reservation is often applied to serve
such traffic in order to achieve better Quality of Service
(QoS). Evolutionary Algorithms are quite useful in
solving optimization problems of such nature. This paper
employs Genetic Algorithm (GA) for bandwidth
management in Cellular IP network. It compares the
performance of the model with another model used for
optimizing Connection Dropping Probability (CDP) using
Particle Swarm Optimization (PSO). Both models, GA
based and PSO based, try to minimize the Connection
Dropping Probability for real-time users in the network
by searching the free available bandwidth in the user’s
cell or in the neighbor cells and assigning it to the realtime
users. Alternatively, if the free bandwidth is not
available, the model borrows the bandwidth from nonreal
time-users and gives it to the real-time users.
Experimental results evaluate the performance of the GA
based model. The comparative study between both the
models indicates that GA based model has an edge over
the PSO based one.
ON THE PERFORMANCE OF INTRUSION DETECTION SYSTEMS WITH HIDDEN MULTILAYER NEUR...IJCNCJournal
Deep learning applications, especially multilayer neural network models, result in network intrusion detection with high accuracy. This study proposes a model that combines a multilayer neural network with Dense Sparse Dense (DSD) multi-stage training to simultaneously improve the criteria related to the performance of intrusion detection systems on a comprehensive dataset UNSW-NB15. We conduct experiments on many neural network models such as Recurrent Neural Network (RNN), Long-Short Term Memory (LSTM), Gated Recurrent Unit (GRU), etc. to evaluate the combined efficiency with each model through many criteria such as accuracy, detection rate, false alarm rate, precision, and F1-Score.
Mean Object Size Considering Average Waiting Latency in M/BP/1 SystemIJCNCJournal
This paper deals with the web object size which affects to the service time in multiple access environments. The M/BP/1 model can be considered because packets arrival and web service are Poission and Bound Pareto (BP) distribution respectively. We find mean object size which satisfies that the average waiting latency by deterministic model equals the mean queueing delay of the M/BP/1 model. Performance evaluation shows that the mean web object size is affected by file size bounds and shape parameter of BP distribution, however, the impact of link capacity is not significant. When the system load is low, web object size converges on half the maximum segment size (MSS). Our results can be applied to find mean web object size in the economic web service design.
Application Of Extreme Value Theory To Bursts PredictionCSCJournals
Bursts and extreme events in quantities such as connection durations, file sizes, throughput, etc. may produce undesirable consequences in computer networks. Deterioration in the quality of service is a major consequence. Predicting these extreme events and burst is important. It helps in reserving the right resources for a better quality of service. We applied Extreme value theory (EVT) to predict bursts in network traffic. We took a deeper look into the application of EVT by using EVT based Exploratory Data Analysis. We found that traffic is naturally divided into two categories, Internal and external traffic. The internal traffic follows generalized extreme value (GEV) model with a negative shape parameter, which is also the same as Weibull distribution. The external traffic follows a GEV with positive shape parameter, which is Frechet distribution. These findings are of great value to the quality of service in data networks, especially when included in service level agreement as traffic descriptor parameters.
Online learning algorithmes often have to operate in the presence of concept drifts. A recent study
revealed that different diversity levels in an ensemble of learning machines are required in order to maintain high
generalization on both old and new concepts. Inspired by this study and based on a further study of diversity with
different strategies to deal with drifts, so propose a new online ensemble learning approach called Diversity for
Dealing with Drifts (DDD).DDD maintains ensembles with different diversity levels and is able to attain better
accuracy than other approaches. Furthermore, it is very robust, outperforming other drift handling approaches in
terms of accuracy when there are false positive drift detections. It is always performed at least as well as
other drift handling approaches under various conditions, with very few exceptions. Presents an analysis of low
and high diversity ensembles combined with different strategies to deal with concept drift and proposes a new
approach (DDD) to handle drifts.
IDENTIFICATION AND INVESTIGATION OF THE USER SESSION FOR LAN CONNECTIVITY VIA...ijcseit
This paper mainly presents some technical discussions on the identification and analyze of “LAN usersessions”.
The identification of a user-session is non trivial. Classical methods approaches rely on
threshold based mechanisms. Threshold based techniques are very sensitive to the value chosen for the
threshold, which may be difficult to set correctly. Clustering techniques are used to define a novel
methodology to identify LAN user-sessions without requiring an a priori definition of threshold values. We
have defined a clustering based approach in detail, and also we discussed positive and negative of this
approach, and we apply it to real traffic traces. The proposed methodology is applied to artificially
generated traces to evaluate its benefits against traditional threshold based approaches. We also analyzed
the characteristics of user-sessions extracted by the clustering methodology from real traces and study
their statistical properties.
Parallel WaveGAN, Yamamoto, Ryuichi, Eunwoo Song, and Jae-Min Kim. "Parallel WaveGAN: A fast waveform generation model based on generative adversarial networks with multi-resolution spectrogram." ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2020. review by June-Woo Kim
Selective Green Device Discovery for Device to Device CommunicationTELKOMNIKA JOURNAL
The D2D communication is expected to improve devices’ energy-efficiency, which has become a
major requirement of the future wireless network. Before the D2D communication can be performed, the
device discovery between devices must be done. The previous works usually only assumed one mode of
device discovery, i.e. either use network-assisted (with network supervision) or independent (without
network supervision) device. Therefore, we propose a selective device discovery for device-to-device
(D2D) communication that can utilize both device discovery modes and maintain devices’ energyefficiency.
Different from previous works, our proposed method selects the best device discovery mode to
get the best energy-efficiency. Moreover, to further improve the energy-efficiency, our proposed method
also deployed in D2D cluster with multiple cluster heads. The proposed method selects the most suitable
mode using thresholds (cluster energy consumption and new device acceptance) and cluster energy
expectation. Our experiment result indicates that the proposed method provides lowest energy
consumption per new accepted device while compared with schemes with full network-assisted and
independent device discovery in low numbers of new device arrival (for the number of new devices
arrival = 1 ~ 3).
PERCEPTUAL COPYRIGHT PROTECTION USING MULTIRESOLUTION WAVELET-BASED WATERMARK...gerogepatton
In this paper, an efficiently DWT-based watermarking technique is proposed to embed signatures in images to attest the owner identification and discourage the unauthorized copying. This paper deals with a fuzzy inference filter to choose the larger entropy of coefficients to embed watermarks. Unlike most previous watermarking frameworks which embedded watermarks in the larger coefficients of inner coarser subbands, the proposed technique is based on utilizing a context model and fuzzy inference filter by embedding watermarks in the larger-entropy coefficients of coarser DWT subbands. The proposed approaches allow us to embed adaptive casting degree of watermarks for transparency and robustness to the general image-processing attacks such as smoothing, sharpening, and JPEG compression. The approach has no need the original host image to extract watermarks. Our schemes have been shown to provide very good results in both image transparency and robustness.
Conformer, Gulati, Anmol, et al. "Conformer: Convolution-augmented Transformer for Speech Recognition." arXiv preprint arXiv:2005.08100 (2020). review by June-Woo Kim
Machine learning in Dynamic Adaptive Streaming over HTTP (DASH)Eswar Publications
Recently machine learning has been introduced into the area of adaptive video streaming. This paper explores a novel taxonomy that includes six state of the art techniques of machine learning that have been applied to Dynamic Adaptive Streaming over HTTP (DASH): (1) Q-learning, (2) Reinforcement learning, (3) Regression, (4) Classification, (5) Decision Tree learning, and (6) Neural networks.
Packet Loss Rate Differentiation in slotted Optical Packet Switching OCDM/WDMTELKOMNIKA JOURNAL
We propose a multi-class mechanism for Optical Code Division Multiplexing (OCDM), Wavelength
Division Multiplexing (WDM) Optical Packet Switch (OPS) architecture capable of supporting Quality of Service
(QoS) transmission. OCDM/WDM has been proposed as a competitive hybrid switching technology to
support the next generation optical Internet. This paper addresses performance issues in the slotted OPS
networks and proposed four differentiation schemes to support Quality of Service. In addition, we present a
comparison between the proposed schemes as well as, a simulation scheduler design which can be suitable
for the core switch node in OPS networks. Using software simulations the performance of our algorithm in
terms of losing probability, the packet delay, and scalability is evaluated.
Data collection scheme for wireless sensor network with mobile collectorijwmn
In this paper, we investigate the problem of designing the minimum number of required mobile elements
tours such that each sensor node is either on the tour or one hop away from the tour, and the length of the
tour to be bounded by pre-determined value L. To address this problem, we propose heuristic-based
solution. This solution works by directing the mobile element tour towards the highly dense area in the
network. The experiment results show that our scheme outperform the benchmark scheme by 10% in most
scenarios.
Performance Analysis of Bfsk Multi-Hop Communication Systems Over K-μ Fading ...ijwmn
Multi-hop communication systems gained popularity in wireless communications; they can be used to
extend the coverage of the network and reduce the transmitted power. The transmission of data from the
source node to the destination node in multi-hop communications undergoes through intermediate relay
nodes. In this paper, we study the performance of multi-hop communication systems, in terms of average bit
error rate (BER) with Binary frequency shift keying assuming the κ-µ fading channel model. Due to the
difficulty in finding the probability density function (PDF) of the end-to-end signal to noise ratio (SNR) and
hence for the performance metrics, we use Gaussian Mixture (GM) approximation technique to
approximate the PDF of the end to end SNR assuming the κ-µ fading models as weighted sums of Gaussian
distributions. Numerical results are provided for the BER of binary frequency shift keying (BFSK) of
amplify and forward (AF) multi-hop communication systems assuming different values for the fading
parameters (, ) and for different number of hops. Numerical results are validated by comparing them
with simulation results.
Monotonic Multihead Attention, Ma, Xutai, et al. "Monotonic Multihead Attention." International Conference on Learning Representations. 2020. review by June-Woo Kim
A Novel Technique for Image Steganography Based on DWT and Huffman EncodingCSCJournals
Image steganography is the art of hiding information into a cover image. This paper presents a novel technique for Image steganography based on DWT, where DWT is used to transform original image (cover image) from spatial domain to frequency domain. Firstly two dimensional Discrete Wavelet Transform (2-D DWT) is performed on a gray level cover image of size M × N and Huffman encoding is performed on the secret messages/image before embedding. Then each bit of Huffman code of secret message/image is embedded in the high frequency coefficients resulted from Discrete Wavelet Transform. Image quality is to be improved by preserving the wavelet coefficients in the low frequency sub-band. The experimental results show that the algorithm has a high capacity and a good invisibility. Moreover PSNR of cover image with stego-image shows the better results in comparison with other existing steganography approaches. Furthermore, satisfactory security is maintained since the secret message/image cannot be extracted without knowing decoding rules and Huffman table.
FAST DETECTION OF DDOS ATTACKS USING NON-ADAPTIVE GROUP TESTINGIJNSA Journal
Network security has become more important role today to personal users and organizations. Denial-of-
Service (DoS) and Distributed Denial-of-Service (DDoS) attacks are serious problem in network. The
major challenges in design of an efficient algorithm in data stream are one-pass over the input, poly-log
space, poly-log update time and poly-log reporting time. In this paper, we use strongly explicit construction
d-disjunct matrices in Non-adaptive group testing (NAGT) to adapt these requirements and propose a
solution for fast detecting DoS and DDoS attacks based on NAGT approach
Sector based multicast routing algorithm for mobile ad hoc networksijwmn
Multicast routing algorithms for mobile ad-hoc networks have been extensively researched in the recent
past. In this paper, we present two algorithms for dealing with multicast routing problem using the notion
of virtual forces. We look at the effective force exerted on a packet and determine whether a node could be
considered as a Steiner node. The nodes' location information is used to generate virtual circuits
corresponding to the multicast route. QoS parameters are taken into consideration in the form of virtual
dampening force. The first algorithm produces relatively minimal multicast trees under the set of
constraints. We improve upon the first algorithm and present a second algorithm that provides
improvement in average residual energy in the network as well as effective cost per data packet
transmitted. In this paper, the virtual-force technique has been applied for multicast routing for the first
time in mobile ad-hoc networks.
Cellular wireless systems like GSM suffer from congestion resulting in overall system degradation and poor service delivery. When the traffic demand in a geographical area is high, the input traffic rate will exceed thecapacity of the output lines. This work focused on homogenous wireless network (the network traffic and resource dimensioning that are statistically identical) such that the network performance
evaluation can be reduced to a system with single cell and a single traffic type. Such system can employa queuing model to evaluate the performance metric of a cell in terms of blocking probability.
Five congestion control models were compared in the work to ascertain their peculiarities, they are Erlang B, Erlang C, Engset (cleared), Engset (buffered), and Bernoulli. To analyze the system, an aggregate onedimensional Markov chain wasderived, such that it describes a call arrival process under the assumption
that it is Poisson distributed. The models were simulated and their results show varying performances, however the Bernoulli model (Pb5) tends to show a situation that allows more users access to the system and the congestion level remain unaffected despite increase in the number of users and the offered traffic into the system.
IDENTIFICATION AND INVESTIGATION OF THE USER SESSION FOR LAN CONNECTIVITY VIA...ijcseit
This paper mainly presents some technical discussions on the identification and analyze of “LAN usersessions”.
The identification of a user-session is non trivial. Classical methods approaches rely on
threshold based mechanisms. Threshold based techniques are very sensitive to the value chosen for the
threshold, which may be difficult to set correctly. Clustering techniques are used to define a novel
methodology to identify LAN user-sessions without requiring an a priori definition of threshold values. We
have defined a clustering based approach in detail, and also we discussed positive and negative of this
approach, and we apply it to real traffic traces. The proposed methodology is applied to artificially
generated traces to evaluate its benefits against traditional threshold based approaches. We also analyzed
the characteristics of user-sessions extracted by the clustering methodology from real traces and study
their statistical properties.
Parallel WaveGAN, Yamamoto, Ryuichi, Eunwoo Song, and Jae-Min Kim. "Parallel WaveGAN: A fast waveform generation model based on generative adversarial networks with multi-resolution spectrogram." ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2020. review by June-Woo Kim
Selective Green Device Discovery for Device to Device CommunicationTELKOMNIKA JOURNAL
The D2D communication is expected to improve devices’ energy-efficiency, which has become a
major requirement of the future wireless network. Before the D2D communication can be performed, the
device discovery between devices must be done. The previous works usually only assumed one mode of
device discovery, i.e. either use network-assisted (with network supervision) or independent (without
network supervision) device. Therefore, we propose a selective device discovery for device-to-device
(D2D) communication that can utilize both device discovery modes and maintain devices’ energyefficiency.
Different from previous works, our proposed method selects the best device discovery mode to
get the best energy-efficiency. Moreover, to further improve the energy-efficiency, our proposed method
also deployed in D2D cluster with multiple cluster heads. The proposed method selects the most suitable
mode using thresholds (cluster energy consumption and new device acceptance) and cluster energy
expectation. Our experiment result indicates that the proposed method provides lowest energy
consumption per new accepted device while compared with schemes with full network-assisted and
independent device discovery in low numbers of new device arrival (for the number of new devices
arrival = 1 ~ 3).
PERCEPTUAL COPYRIGHT PROTECTION USING MULTIRESOLUTION WAVELET-BASED WATERMARK...gerogepatton
In this paper, an efficiently DWT-based watermarking technique is proposed to embed signatures in images to attest the owner identification and discourage the unauthorized copying. This paper deals with a fuzzy inference filter to choose the larger entropy of coefficients to embed watermarks. Unlike most previous watermarking frameworks which embedded watermarks in the larger coefficients of inner coarser subbands, the proposed technique is based on utilizing a context model and fuzzy inference filter by embedding watermarks in the larger-entropy coefficients of coarser DWT subbands. The proposed approaches allow us to embed adaptive casting degree of watermarks for transparency and robustness to the general image-processing attacks such as smoothing, sharpening, and JPEG compression. The approach has no need the original host image to extract watermarks. Our schemes have been shown to provide very good results in both image transparency and robustness.
Conformer, Gulati, Anmol, et al. "Conformer: Convolution-augmented Transformer for Speech Recognition." arXiv preprint arXiv:2005.08100 (2020). review by June-Woo Kim
Machine learning in Dynamic Adaptive Streaming over HTTP (DASH)Eswar Publications
Recently machine learning has been introduced into the area of adaptive video streaming. This paper explores a novel taxonomy that includes six state of the art techniques of machine learning that have been applied to Dynamic Adaptive Streaming over HTTP (DASH): (1) Q-learning, (2) Reinforcement learning, (3) Regression, (4) Classification, (5) Decision Tree learning, and (6) Neural networks.
Packet Loss Rate Differentiation in slotted Optical Packet Switching OCDM/WDMTELKOMNIKA JOURNAL
We propose a multi-class mechanism for Optical Code Division Multiplexing (OCDM), Wavelength
Division Multiplexing (WDM) Optical Packet Switch (OPS) architecture capable of supporting Quality of Service
(QoS) transmission. OCDM/WDM has been proposed as a competitive hybrid switching technology to
support the next generation optical Internet. This paper addresses performance issues in the slotted OPS
networks and proposed four differentiation schemes to support Quality of Service. In addition, we present a
comparison between the proposed schemes as well as, a simulation scheduler design which can be suitable
for the core switch node in OPS networks. Using software simulations the performance of our algorithm in
terms of losing probability, the packet delay, and scalability is evaluated.
Data collection scheme for wireless sensor network with mobile collectorijwmn
In this paper, we investigate the problem of designing the minimum number of required mobile elements
tours such that each sensor node is either on the tour or one hop away from the tour, and the length of the
tour to be bounded by pre-determined value L. To address this problem, we propose heuristic-based
solution. This solution works by directing the mobile element tour towards the highly dense area in the
network. The experiment results show that our scheme outperform the benchmark scheme by 10% in most
scenarios.
Performance Analysis of Bfsk Multi-Hop Communication Systems Over K-μ Fading ...ijwmn
Multi-hop communication systems gained popularity in wireless communications; they can be used to
extend the coverage of the network and reduce the transmitted power. The transmission of data from the
source node to the destination node in multi-hop communications undergoes through intermediate relay
nodes. In this paper, we study the performance of multi-hop communication systems, in terms of average bit
error rate (BER) with Binary frequency shift keying assuming the κ-µ fading channel model. Due to the
difficulty in finding the probability density function (PDF) of the end-to-end signal to noise ratio (SNR) and
hence for the performance metrics, we use Gaussian Mixture (GM) approximation technique to
approximate the PDF of the end to end SNR assuming the κ-µ fading models as weighted sums of Gaussian
distributions. Numerical results are provided for the BER of binary frequency shift keying (BFSK) of
amplify and forward (AF) multi-hop communication systems assuming different values for the fading
parameters (, ) and for different number of hops. Numerical results are validated by comparing them
with simulation results.
Monotonic Multihead Attention, Ma, Xutai, et al. "Monotonic Multihead Attention." International Conference on Learning Representations. 2020. review by June-Woo Kim
A Novel Technique for Image Steganography Based on DWT and Huffman EncodingCSCJournals
Image steganography is the art of hiding information into a cover image. This paper presents a novel technique for Image steganography based on DWT, where DWT is used to transform original image (cover image) from spatial domain to frequency domain. Firstly two dimensional Discrete Wavelet Transform (2-D DWT) is performed on a gray level cover image of size M × N and Huffman encoding is performed on the secret messages/image before embedding. Then each bit of Huffman code of secret message/image is embedded in the high frequency coefficients resulted from Discrete Wavelet Transform. Image quality is to be improved by preserving the wavelet coefficients in the low frequency sub-band. The experimental results show that the algorithm has a high capacity and a good invisibility. Moreover PSNR of cover image with stego-image shows the better results in comparison with other existing steganography approaches. Furthermore, satisfactory security is maintained since the secret message/image cannot be extracted without knowing decoding rules and Huffman table.
FAST DETECTION OF DDOS ATTACKS USING NON-ADAPTIVE GROUP TESTINGIJNSA Journal
Network security has become more important role today to personal users and organizations. Denial-of-
Service (DoS) and Distributed Denial-of-Service (DDoS) attacks are serious problem in network. The
major challenges in design of an efficient algorithm in data stream are one-pass over the input, poly-log
space, poly-log update time and poly-log reporting time. In this paper, we use strongly explicit construction
d-disjunct matrices in Non-adaptive group testing (NAGT) to adapt these requirements and propose a
solution for fast detecting DoS and DDoS attacks based on NAGT approach
Sector based multicast routing algorithm for mobile ad hoc networksijwmn
Multicast routing algorithms for mobile ad-hoc networks have been extensively researched in the recent
past. In this paper, we present two algorithms for dealing with multicast routing problem using the notion
of virtual forces. We look at the effective force exerted on a packet and determine whether a node could be
considered as a Steiner node. The nodes' location information is used to generate virtual circuits
corresponding to the multicast route. QoS parameters are taken into consideration in the form of virtual
dampening force. The first algorithm produces relatively minimal multicast trees under the set of
constraints. We improve upon the first algorithm and present a second algorithm that provides
improvement in average residual energy in the network as well as effective cost per data packet
transmitted. In this paper, the virtual-force technique has been applied for multicast routing for the first
time in mobile ad-hoc networks.
Cellular wireless systems like GSM suffer from congestion resulting in overall system degradation and poor service delivery. When the traffic demand in a geographical area is high, the input traffic rate will exceed thecapacity of the output lines. This work focused on homogenous wireless network (the network traffic and resource dimensioning that are statistically identical) such that the network performance
evaluation can be reduced to a system with single cell and a single traffic type. Such system can employa queuing model to evaluate the performance metric of a cell in terms of blocking probability.
Five congestion control models were compared in the work to ascertain their peculiarities, they are Erlang B, Erlang C, Engset (cleared), Engset (buffered), and Bernoulli. To analyze the system, an aggregate onedimensional Markov chain wasderived, such that it describes a call arrival process under the assumption
that it is Poisson distributed. The models were simulated and their results show varying performances, however the Bernoulli model (Pb5) tends to show a situation that allows more users access to the system and the congestion level remain unaffected despite increase in the number of users and the offered traffic into the system.
Dynamic bandwidth allocation scheme in lr pon with performance modelling and ...IJCNCJournal
We consider models of telecommunication systems that incorporate probability, dense real-time and data.
We present a new formal abstraction method for computing minimum and maximum reachability
probabilities for such models. Our approach uses strictly local formal abstract steps to reduce both the size
of abstract specifications generated and the complexity of operations needed, in comparison to previous
approaches of this kind. A selection of large case studies are implemented the techniques and evaluate,
which include some infinite-state probabilistic real time models, demonstrating improvements over existing
tools in several cases. The capacity of metro and access networks are extended the reach and split ratio of
the conventional Long - Reach Passive Optical Networks (LR-PONs). The efficient solutions of LR-PONs
are appeared in feeder distances around 100km and high split ratios up to 1000-way . Among many
existing approaches, one of the most effective options to improve network performance in LR-PONs are the
multi-thread based dynamic bandwidth allocation (DBA) scheme where several bandwidth allocation
processes are performed in parallel is considered. Without proper intercommunication between the
overlapped threads, multi-thread DBA may lose efficiency and even perform worse than the conventional
single thread algorithm. Real Time Probabilistic Systems are used to evaluate a typical PON systems
performance. This approach is more convenient, flexible, and lower cost than the former simulation method,
which do not need develop special hardware and software tools. Moreover, how changes in performance
depend on changes in the particular modes can be easily analysis by supplying ranges for parameter values.
The proposed algorithm with traditional DBA is compared, and shows its advantage on average packet
delay. The key parameters of the algorithm are analysed and optimized, such as initiating and tuning
multiple threads, inter -thread scheduling, and fairness among users. The algorithms advantage in
numerical results are decreased the average packet delay and improve network throughput under varying
offered loads.
Resource Allocation in MIMO – OFDM Communication System under Signal Strength...Kumar Goud
Abstract: - Multiple Inputs and Multiple Output (MIMO) and Orthogonal Frequency Division Multiplexing (OFDM) system have the potential to attain high capability on the propagation setting. The aim of this paper is that the adaptive resource allocation in MIMO-OFDM system uses the water filling formula. Water filling answer is enforced for allocating the ability so as to extend the data rate. The overall system capability is maximised subject to the constraints on total power, signal to noise quantitative relation, and proportionality. Channel is assumed as a flat attenuation channel and therefore the comparison is created for various 2×2, 2×3, 3×2 and 4×4 MIMO-OFDM systems and water filling formula with allotted power. Supported the capability contribution from the relaying terminal, a brand new parameter referred to as cooperation constant is introduced as an operate of the relaying sub channel. This parameter is employed to switch the target parameter of the subcarrier allocation procedure. Fairness-oriented [Fading Channel] and throughput-oriented [Near finish Channel] algorithms square measure elite from the literature to check the planned technique. Each algorithms square measure changed to use the mean of cooperation constant within the objective parameter of the subcarrier allocation procedure and shown to own a much better total turnout with none sacrifice.
Keywords - MIMO-OFDM; Water filling Algorithm; Subcarrier Resource Allocation
Jamming aware traffic allocation for multiple-path routing using portfolio se...Saad Bare
Multiple-path source routing protocols allow a data source node to distribute the total traffic among available paths. we consider the problem of jamming-aware source routing in which the source node performs traffic allocation based on empirical jamming statistics at individual network nodes. We formulate this traffic allocation as a lossy network flow optimization problem using portfolio selection theory from financial statistics. We show that in multisource networks, this centralized optimization problem can be solved using a distributed algorithm based on decomposition in network utility maximization (NUM). We demonstrate the network's ability to estimate the impact of jamming and incorporate these estimates into the traffic allocation problem. Finally, we simulate the achievable throughput using our proposed traffic allocation method in several scenarios.
Performance Simulation and Analysis for LTESystem Using Human Behavior Queue ...ijwmn
Understanding the nature of traffic has been a key concern of the researchers particularly over the last
two decades and it has been noticed through extensive high quality studies that traffic found in different
kinds of IP/wireless IP networks is human operators . Despite the recent findings of real time human
behavior in measured traffic from data networks, much of the current understanding of IP traffic
modeling is still based on simplistic probability distributed traffic. Unlike most existing studies that are
primarily based on simplistic probabilistic model and traditional scheduling algorithms, this research
presents an analytical performance model for real time human behavior queue systems with intelligent
task management traffic input scheduled by a novel and promising scheduling mechanism for 4G-LTE
system. Our proposed model is substantiated on human behavior queuing system that considers real time
of traffic exhibiting homogeneous tasks characteristics. We analyze the model on the basis of newly
proposed scheduling scheme for 4G-LTE system. We present closed form expressions of expected
response times for real time traffic classes. We develop a discrete event simulator to understand the
behavior of real time of arriving tasks traffic under this newly proposed scheduling mechanism for 4GLTE system . The results indicate that our proposed scheduling algorithm provides preferential treatment
to real-time applications such as voice and video but not to that extent that data applications are starving
for bandwidth and outperforms all other scheduling schemes that are available in the market.
Optimize the Network Coding Paths to Enhance the Coding Protection in Wireles...IJCNCJournal
Efficient protection techniques for multimedia data transfer over Wireless Sensor Network (WSN) are very essential issues. In noisy Wireless Multimedia Sensor Networks (WMSN) Quality of Service (QoS) is a challenging task due to bandwidth and limited energy, and unpredictable channel conditions. Therefore, Forward Error Correction (FEC), a class of channel coding has been widely used in WSN. Nevertheless, the bulky size of multimedia data makes it more difficult to be transported over the noisy multi-hop wireless network. Moreover, the efficiency of FEC drops as the number of hops increases. In this paper, an optimized protection technique based on network coding and rateless code has been proposed to enhance the throughput and reduce overhead during data transfer in WMSN. The performance of NCP-OPR is enhanced via Optimal Network Path Model (ONPM) where the best available paths are optimally selected using Particle Swarm Optimization (PSO). In conjunction with the proposed protection scheme, the proposed ONPM is intended for limited power WSN by optimally distributing the power usage among the network paths so that the throughput can be improved.
Optimize the Network Coding Paths to Enhance the Coding Protection in Wireles...IJCNCJournal
Efficient protection techniques for multimedia data transfer over Wireless Sensor Network (WSN) are very essential issues. In noisy Wireless Multimedia Sensor Networks (WMSN) Quality of Service (QoS) is a challenging task due to bandwidth and limited energy, and unpredictable channel conditions. Therefore, Forward Error Correction (FEC), a class of channel coding has been widely used in WSN. Nevertheless, the bulky size of multimedia data makes it more difficult to be transported over the noisy multi-hop wireless network. Moreover, the efficiency of FEC drops as the number of hops increases. In this paper, an optimized protection technique based on network coding and rateless code has been proposed to enhance the throughput and reduce overhead during data transfer in WMSN. The performance of NCP-OPR is enhanced via Optimal Network Path Model (ONPM) where the best available paths are optimally selected using Particle Swarm Optimization (PSO). In conjunction with the proposed protection scheme, the proposed ONPM is intended for limited power WSN by optimally distributing the power usage among the network paths so that the throughput can be improved.
RESPONSE SURFACE METHODOLOGY FOR PERFORMANCE ANALYSIS AND MODELING OF MANET R...IJCNCJournal
Numerous studies have analyzed the performances of routing protocols in mobile Ad-hoc networks (MANETs); most of these studies vary at most one or two parameters in experiments and do not study the interactions among these parameters. Furthermore, efficient mathematical modeling of the performances has not been investigated; such models can be useful for performance analysis, optimization, and prediction. This study aims to show the effectiveness of the response surface methodology (RSM) on the performance analysis of routing protocols in MANETs and establish a relationship between the influential parameters and these performances through mathematical modeling. Given that routing performances usually do not follow a linear pattern according to the parameters; mathematical models of factorial designs are not suitable for establishing a valid and reliable relationship between performances and parameters. Therefore, a Box–Behnken design, which is an RSM technique and provides quadratic mathematical models, is used in this study to establish a relationship. The obtained models are statistically analyzed; the models show that the studied performances accurately follow a quadratic evolution. These models provide invaluable information and can be useful in analyzing, optimizing, and predicting performances for mobile Ad-hoc routing protocols.
An efficient ant optimized multipath routing in wireless sensor networkEditor Jacotech
Today, the Wireless Sensor Network is increasingly gaining popularity and importance. It is the more interesting and stimulating area of research. Now, the WSN is applied in object tracking and environmental monitoring applications. This paper presents the self-optimized model of multipath routing algorithm for WSN which considers definite parameters like delay, throughput level and loss and generates the outcomes that maximizes data throughput rate and minimizes delay and loss. This algorithm is based on ANT optimization technique that will bring out an optimal and organized route for WSN and is also to avoid congestion in WSN, the algorithm incorporate multipath capability..
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
40. An optimization model Minimize Penalty made by unsatisfied traffic aggregates Subject to Fixed resource (Limited Short Path bandwidth) Traffic aggregate QDF budget must be satisfied Allocate resource to traffic aggregates Trading off QDF with bandwidth in each Short Path 最佳化模型
72. No interac- tion allowed 2 1 Individual sampling model (ISM): Simulated patient-level Markov model (SPLMM) (variations as in quadrant below for patient level models with interaction) Simulated Markov model (SMM) Markov model (evaluated deterministically) Timed Individual sampling model (ISM): Simulated patient-level decision tree (SPLDT) Simulated decision tree (SDT) Decision tree rollback Untimed Non-Markovian, discrete-state, individuals Markovian, discrete state, individuals Markovian, discrete state, stochastic Expected value, continuous state, deterministic Individual level Cohort/aggregate level/counts D C B A
73. Discrete event simulation (CT, DES) Discrete individual simulation (DT, DES) Interaction allowed 4 3 Continuous time Individual event history model (CT, IEH) Continuous time Markov chain model (CTMC) System dynamics (ordinary differential equations, ODE) Continu-ous time Discrete-time individual event history model (DT, IEH) Discrete time Markov chain model (DTMC) System dynamics (finite difference equations, FDE) Discrete time Non-Markovian, discrete-state, individuals Markovian, discrete state, individuals Markovian, discrete state, stochastic Expected value, continuous state, deterministic Individual level Cohort/aggregate level/counts D C B A