In this papr, we have minimized the effects of failures on network performace, by using suitable Routing
and Wavelenghth Assignment(RWA) method without disturbing other performance criteria such as blocking
probability(BP) and network management(NM). The computation complexity is reduced by using Kalaman
Filter(KF) techniques. The minimum reconfiguration probability routing (MRPR) algorithm must be
able to select most reliable routes and assign wavelengths to connections in a manner that utilizes the light
path(LP) established efficiently considering all possible requests.
AN MINIMUM RECONFIGURATION PROBABILITY ROUTING ALGORITHM FOR RWA IN ALL-OPTIC...sipij
In this paper, we present a detailed study of Minimum Reconfiguration Probability Routing (MRPR) algorithm, and its performance evaluation in comparison with Adaptive unconstrained routing (AUR) and Least Loaded routing (LLR) algorithms. We have minimized the effects of failures on link and router failure in the network under changing load conditions, we assess the probability of service and number of light path failures due to link or route failure on Wavelength Interchange(WI) network. The computation complexity is reduced by using Kalman Filter(KF) techniques. The minimum reconfiguration probability
routing (MRPR) algorithm selects most reliable routes and assign wavelengths to connections in a manner that utilizes the light path(LP) established efficiently considering all possible requests.
MPC-EAR : Maximal Power Conserved And Energy Aware Routing in Ad hoc Networksijsrd.com
Power preservation in wireless ad hoc networks is a decisive factor as energy resources are inadequate at the electronic devices in use. Power-aware routing strategies are fundamentally route selection strategies built on accessible ad hoc routing protocols. This paper proposed a new Maximal Power Conserved And Energy Aware Routing (MPC-EAR ) topology for mobile ad hoc networks that enhances the network life span. Simulation results prove that the projected protocol has a higher performance other minimal energy usage, energy level aware and energy conserving routing protocols such as MTPR, MMECR and CMMECR.
Abstract In optical circuit switching the high values of blocking probability is resolved by dynamic wavelength routing algorithms with wavelength conversion. The aim of this paper is to study these algorithms. Then the algorithm is selected which gives good results with and without wavelength conversion. The selected algorithm is then checked for other parameters of networking namely throughput, packet delivery ratio, and delay. A comparative study is then carried out for increasing traffic. We try to prove that these algorithms satisfy the criteria of QoS parameters by this comparative study. The results of simulation show that the parameters follow the trend of blocking probability of the selected algorithm. Keywords: optical burst switching, throughput, packet delivery ratio, delay.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
AN MINIMUM RECONFIGURATION PROBABILITY ROUTING ALGORITHM FOR RWA IN ALL-OPTIC...sipij
In this paper, we present a detailed study of Minimum Reconfiguration Probability Routing (MRPR) algorithm, and its performance evaluation in comparison with Adaptive unconstrained routing (AUR) and Least Loaded routing (LLR) algorithms. We have minimized the effects of failures on link and router failure in the network under changing load conditions, we assess the probability of service and number of light path failures due to link or route failure on Wavelength Interchange(WI) network. The computation complexity is reduced by using Kalman Filter(KF) techniques. The minimum reconfiguration probability
routing (MRPR) algorithm selects most reliable routes and assign wavelengths to connections in a manner that utilizes the light path(LP) established efficiently considering all possible requests.
MPC-EAR : Maximal Power Conserved And Energy Aware Routing in Ad hoc Networksijsrd.com
Power preservation in wireless ad hoc networks is a decisive factor as energy resources are inadequate at the electronic devices in use. Power-aware routing strategies are fundamentally route selection strategies built on accessible ad hoc routing protocols. This paper proposed a new Maximal Power Conserved And Energy Aware Routing (MPC-EAR ) topology for mobile ad hoc networks that enhances the network life span. Simulation results prove that the projected protocol has a higher performance other minimal energy usage, energy level aware and energy conserving routing protocols such as MTPR, MMECR and CMMECR.
Abstract In optical circuit switching the high values of blocking probability is resolved by dynamic wavelength routing algorithms with wavelength conversion. The aim of this paper is to study these algorithms. Then the algorithm is selected which gives good results with and without wavelength conversion. The selected algorithm is then checked for other parameters of networking namely throughput, packet delivery ratio, and delay. A comparative study is then carried out for increasing traffic. We try to prove that these algorithms satisfy the criteria of QoS parameters by this comparative study. The results of simulation show that the parameters follow the trend of blocking probability of the selected algorithm. Keywords: optical burst switching, throughput, packet delivery ratio, delay.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Performance evaluation of proactive, reactive and hybrid routing protocols wi...eSAT Journals
Abstract Our work mainly focused on the performance and effects of different mobility models like Random Waypoint, Reference Point Group, and Manhattan mobility models in different aspects to improve and analyze the behavior of Optimized Link-State Routing (OLSR), Temporally-Ordered Routing Algorithm (TORA) and Zone Routing Protocol (ZRP) routing protocols. These three routing protocols can be classified into the following three general categories, based on the timing when the routes are discovered and updated-proactive (OLSR), reactive (TORA) and hybrid (ZRP). In literature various researchers have discussed the performance issues in AODV, DSDV and DSR routing protocols in Random Waypoint mobility model on Mobile Ad hoc Networks (MANETs) is not satisfactory due to link failure and late acknowledgement. To resolve the specified issue, we have come up with other alternatives like Reference Point Group, and Manhattan mobility model and also other routing protocols like OSLR, TORA and ZRP. A simulation was carried out in NS2 and Bonnmotion for above said protocols and mobility models in Constant Bit Rate (CBR) traffic to analyzed using various metrics like packet delivery fraction, end to end delay and normalized routing load. In our simulation it was shown that few mobility model performed better in different routing protocols. In our simulation results, we got a high Normalized Routing Load for Random Waypoint compared to Reference Point Group, and Manhattan mobility model in both DRP and OSLR protocols. Index Terms: MANET, CBR, Routing protocols, Mobility models, NS2
M-EPAR to Improve the Quality of the MANETsIJERA Editor
In MANET, power aware is important challenge issue to improve the communication energy efficiency at individual nodes. We propose modified efficient power aware routing (M-EPAR), a new power aware routing protocol that increases the network lifetime of MANET. Designing a power aware routing algorithm or technique is one of the most important point considered in Mobile Ad Hoc Networks. These nodes are driven by reactive protocols where broadcasting is mandatory to form a path between two nodes. So in case of death of the node resulting out of less battery calls for re-routing. Since many existing techniques focuses on energy aware routing this paper presents combination of energy aware routing merged with link quality determined by packet drop rate. The proposed scheme has outperformed the existing technique in terms of packet delivery ratio, throughput and energy consumption.
Performance Analysis for Parallel MRA in Heterogeneous Wireless NetworksEditor IJCATR
This paper analysis a different methods to find optimal path for services and power allocation to heterogeneous wireless network. Under heterogeneous wireless networks, a user can send data through a single or multi RATs (Radio Access Technology) simultaneously. The objective of this paper is to choose the optimal path for the services and power allocation to that bandwidth (BW) distributed joint allocation algorithm using Newton and modified Newton are adopted and the total system capacity compared. The analysis is done in Matlab and simulation results are compared. The numerical result shows that compare to Newton method, modified Newton method maximize the total system capacity.
Design A Congestion Aware Routing Algorithm for Synchronous Cam Designijtsrd
The effect of process variation (PV) on delay is a major reason to decay the performance in advanced technologies. The performance of front routing algorithms is determined with or without PV for different traffic patterns. The saturation throughput and average message delay are used as performance metrics to evaluate the throughput. PV decreases the saturation throughput and increases the average message delay. Adaptive routing algorithm should be manipulated with the PV. A novel PV delay and congestion aware routing (PDCR) algorithm is presented for asynchronous network-on-chip (NOC) design. The routing algorithm performs various adaptive routing algorithms in the average delay and saturation throughput for different traffic patterns. A low-power content-addressable memory (CAM) by a new algorithm is proposed for associativity between the input tag and the corresponding address of the output data. The proposed architecture is depends on a recently developed sparse clustered network by utilizing binary connections that on-average eliminates most of the parallel comparisons performed during a search. P. Mounica | R. Umamaheswari | R. Madhavi | R. Nischala | N. Ramesh Babu"Design A Congestion Aware Routing Algorithm for Synchronous Cam Design" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-3 , April 2018, URL: http://www.ijtsrd.com/papers/ijtsrd11547.pdf http://www.ijtsrd.com/engineering/electronics-and-communication-engineering/11547/design-a-congestion-aware-routing-algorithm-for-synchronous-cam-design/p-mounica
Solving bandwidth guaranteed routing problem using routing dataIJCNCJournal
This paper introduces a traffic engineering routing algorithm that aims to accept as many routing demands
as possible on the condition that a certain amount of bandwidth resource is reserved for each accepted
demand. The novel idea is to select routes based on not only network states but also information derived
from routing data such as probabilities of the ingress egress pairs and usage frequencies of the links.
Experiments with respect to acceptance ratio and computation time have been conducted against various
test sets. Results indicate that the proposed algorithm has better performance than the existing popular algorithms including Minimum Interference Routing Algorithm (MIRA) and Random Race based Algorithm for Traffic Engineering (RRATE)
.
4 ijaems jan-2016-8-performance analysis of mixed line rate optical wdm netwo...INFOGAIN PUBLICATION
Due to heterogeneous traffic in next generation Mixed Line Rate (MLR) networks are capable of delivering different bandwidth in a flexible manner. In this paper a simple routing algorithm is proposed to study the case of any link failure in MLR WDM networks. Here Poisson random traffic is used as a dynamic traffic for 24-hour duration. The proposed work can be achieved by deleting the failed link and then finding the new best possible shortest path between source and destination node. According to the traffic load light paths adjustments employ the addition of light paths under congestion and deletion of lightpaths which are not being used at a particular time. Simulation result shows the total number of lightpaths used, total number of addition and deletion of light paths under link safe and link failure case in mixed line rate (MLR) and single line rate (SLR) optical WDM networks.
MMINIMUM RESOURCE CONSUMPTIONS ROUTING FOR OPTICAL NETWORKSprj_publication
The problem of determining primary and backup paths for survivable optical WDM
networks is considered. Results of various available routing techniques that try to minimize
the combined cost of primary and the backup path are analyzed for the effects on network
parameters such as mean load, variance of the load on route, number of converters required
by the route and the length of the route. The route cost is modelled such a way that it is
extensible to include any new parameter and vary their relative importance. The efficiency of
such wavelength routed networks has been proved to improve for certain parameters, such as
reduction in blocking probability and number of converters required for desired performance.
The routing is enhanced to analyse effect on network parameters for all node full range
converters, limited number full converters, reserved primary and back up wavelengths and
with no such reservation.
A CRITICAL REVIEW OF THE ROUTING PROTOCOLS FOR COGNITIVE RADIO NETWORKS AND A...cscpconf
We present a critical review and analysis of different categories of routing protocols for cognitive radio networks. We first classify the available solutions to two broad categories: those
based on full spectrum knowledge (typically used to establish performance benchmarks) and those based on local spectrum knowledge (used for real-time implementation). The full spectrum knowledge based routing solutions are analyzed from a graph-theoretic point of view, and we review the layered graph, edge coloring and conflict graph models. We classify the various local spectrum knowledge based routing protocols into the following five categories: Minimum power, Minimum delay, Maximum throughput, Geographic and Class-based routing. A total of 25 routing protocols proposed for cognitive radio networks have been reviewed. We discuss the working principle and analyze the pros and cons of the routing protocols. Finally, we propose an idea of a load balancing-based local spectrum knowledge-based routing protocol for cognitive radio ad hoc networks.
Throughput Maximization of Cognitive Radio Multi Relay Network with Interfere...IJECEIAES
In this paper, an Orthogonal Frequency Division Multiplexing (OFDM) based cognitive multi relay network is investigated to maximize the transmission rate of the cognitive radio (CR) with enhanced fairness among CR users with interference to the primary users (PUs) being managed below a certain threshold level. In order to improve the transmission rate of the CR, optimization of the subcarrier pairing and power allocation is to be carried out simultaneously. Firstly joint optimization problem is formulated and Composite Genetic and Ordered Subcarrier Pairing (CGOSP) algorithm is proposed to solve the problem. The motivation behind merging genetic and OSP algorithm is to reduce the complexity of Genetic Algorithm (GA). Further, to have a fair allocation of resources among CR users, the Round Robin allocation method is adopted so as to allocate subcarrier pairs to relays efficiently. The degree of fairness of the system is calculated using Jain‟s Fairness Index (JFI). Simulation results demonstrate the significant improvement in transmission rate of the CR, low computational complexity and enhanced fairness.
Quadrant Based DIR in CWin Adaptation Mechanism for Multihop Wireless NetworkIJCI JOURNAL
In Multihop Wireless Networks, traffic forwarding capability of each node varies according to its level of contention. Each node can yield its channel access opportunity to its neighbouring nodes, so that all the nodes can evenly share the channel and have similar forwarding capability. In this manner the wireless channel is utilized effectively, which is achieved using Contention Window Adaptation Mechanism (CWAM). This mechanism achieves a higher end-to-end throughout but consumes the network power to a higher level. So, a newly proposed algorithm Quadrant- Based Directional Routing Protocol (Q-DIR) is implemented as a cross-layer with CWAM, to reduce the total network power consumption through limited flooding and also reduce the routing overheads, which eventually increases overall network throughput. This algorithm limits the broadcast region to a quadrant where the source node and the destination nodes are located. Implementation of the algorithm is done in Linux based NS-2 simulator
Routing in Cognitive Radio Networks - A SurveyIJERA Editor
Cognitive Radio Networks (CRNs) have been emerged as a revolutionary solution to migrate the spectrum
scarcity problem in wireless networks. Due to increasing demand for additional spectrum resources, CRNs have
been receiving significant research to solve issues related with spectrum underutilization. This technology
brings efficient spectrum usage and effective interference avoidance, and also brings new challenges to routing
in multi-hop Cognitive Radio Networks. In CRN, unlicensed users or secondary users are able to use
underutilized licensed channels, but they have to leave the channel if any interference is caused to the primary or
licensed users. So CR technology allows sharing of licensed spectrum band in opportunistic and non-interfering
manner. Different routing protocols have been proposed recently based on different design goals under different
assumptions.
Adaptive resources assignment in OFDM-based cognitive radio systemsIJECEIAES
Spectrum efficiency of orthogonal frequency division multiplexing (OFDM)-based cognitive radio (CR) systems can be improved by adaptive resources allocation. In resources allocation, transmission resources such as modulation level and transmission power are adaptively assigned based on channel variations. The goal of this paper is maximize the total transmission rate of secondary user (SU). Hence, we investigate adaptive power and modulation allocation to achieve this purpose. For power allocation, we investigate optimal and conventional methods and then introduce a novel suboptimal algorithm to calculate the transmission power of each subcarrier. In addition, for adaptive modulation, we consider two kinds of modulations including multi-quadrature amplitude modulation (MQAM) and multi-phase-shift keying (MPSK). Also, simulation results are indicated the performance of our algorithm.
USING CRM SOLUTIONS TO INCREASE SALES AND RETAIN VALUABLE CUSTOMERSInsideUp
CRM is an important tool for creating business success. The better your customer relationships, the
easier it is to conduct business and generate revenue. Using available technology to improve
customer relations management simply makes good business sense.
If you need further information, or would like assistance in selecting a CRM provider, go to
http://www.insideup.com/compare/customer_relationship_management
Performance evaluation of proactive, reactive and hybrid routing protocols wi...eSAT Journals
Abstract Our work mainly focused on the performance and effects of different mobility models like Random Waypoint, Reference Point Group, and Manhattan mobility models in different aspects to improve and analyze the behavior of Optimized Link-State Routing (OLSR), Temporally-Ordered Routing Algorithm (TORA) and Zone Routing Protocol (ZRP) routing protocols. These three routing protocols can be classified into the following three general categories, based on the timing when the routes are discovered and updated-proactive (OLSR), reactive (TORA) and hybrid (ZRP). In literature various researchers have discussed the performance issues in AODV, DSDV and DSR routing protocols in Random Waypoint mobility model on Mobile Ad hoc Networks (MANETs) is not satisfactory due to link failure and late acknowledgement. To resolve the specified issue, we have come up with other alternatives like Reference Point Group, and Manhattan mobility model and also other routing protocols like OSLR, TORA and ZRP. A simulation was carried out in NS2 and Bonnmotion for above said protocols and mobility models in Constant Bit Rate (CBR) traffic to analyzed using various metrics like packet delivery fraction, end to end delay and normalized routing load. In our simulation it was shown that few mobility model performed better in different routing protocols. In our simulation results, we got a high Normalized Routing Load for Random Waypoint compared to Reference Point Group, and Manhattan mobility model in both DRP and OSLR protocols. Index Terms: MANET, CBR, Routing protocols, Mobility models, NS2
M-EPAR to Improve the Quality of the MANETsIJERA Editor
In MANET, power aware is important challenge issue to improve the communication energy efficiency at individual nodes. We propose modified efficient power aware routing (M-EPAR), a new power aware routing protocol that increases the network lifetime of MANET. Designing a power aware routing algorithm or technique is one of the most important point considered in Mobile Ad Hoc Networks. These nodes are driven by reactive protocols where broadcasting is mandatory to form a path between two nodes. So in case of death of the node resulting out of less battery calls for re-routing. Since many existing techniques focuses on energy aware routing this paper presents combination of energy aware routing merged with link quality determined by packet drop rate. The proposed scheme has outperformed the existing technique in terms of packet delivery ratio, throughput and energy consumption.
Performance Analysis for Parallel MRA in Heterogeneous Wireless NetworksEditor IJCATR
This paper analysis a different methods to find optimal path for services and power allocation to heterogeneous wireless network. Under heterogeneous wireless networks, a user can send data through a single or multi RATs (Radio Access Technology) simultaneously. The objective of this paper is to choose the optimal path for the services and power allocation to that bandwidth (BW) distributed joint allocation algorithm using Newton and modified Newton are adopted and the total system capacity compared. The analysis is done in Matlab and simulation results are compared. The numerical result shows that compare to Newton method, modified Newton method maximize the total system capacity.
Design A Congestion Aware Routing Algorithm for Synchronous Cam Designijtsrd
The effect of process variation (PV) on delay is a major reason to decay the performance in advanced technologies. The performance of front routing algorithms is determined with or without PV for different traffic patterns. The saturation throughput and average message delay are used as performance metrics to evaluate the throughput. PV decreases the saturation throughput and increases the average message delay. Adaptive routing algorithm should be manipulated with the PV. A novel PV delay and congestion aware routing (PDCR) algorithm is presented for asynchronous network-on-chip (NOC) design. The routing algorithm performs various adaptive routing algorithms in the average delay and saturation throughput for different traffic patterns. A low-power content-addressable memory (CAM) by a new algorithm is proposed for associativity between the input tag and the corresponding address of the output data. The proposed architecture is depends on a recently developed sparse clustered network by utilizing binary connections that on-average eliminates most of the parallel comparisons performed during a search. P. Mounica | R. Umamaheswari | R. Madhavi | R. Nischala | N. Ramesh Babu"Design A Congestion Aware Routing Algorithm for Synchronous Cam Design" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-3 , April 2018, URL: http://www.ijtsrd.com/papers/ijtsrd11547.pdf http://www.ijtsrd.com/engineering/electronics-and-communication-engineering/11547/design-a-congestion-aware-routing-algorithm-for-synchronous-cam-design/p-mounica
Solving bandwidth guaranteed routing problem using routing dataIJCNCJournal
This paper introduces a traffic engineering routing algorithm that aims to accept as many routing demands
as possible on the condition that a certain amount of bandwidth resource is reserved for each accepted
demand. The novel idea is to select routes based on not only network states but also information derived
from routing data such as probabilities of the ingress egress pairs and usage frequencies of the links.
Experiments with respect to acceptance ratio and computation time have been conducted against various
test sets. Results indicate that the proposed algorithm has better performance than the existing popular algorithms including Minimum Interference Routing Algorithm (MIRA) and Random Race based Algorithm for Traffic Engineering (RRATE)
.
4 ijaems jan-2016-8-performance analysis of mixed line rate optical wdm netwo...INFOGAIN PUBLICATION
Due to heterogeneous traffic in next generation Mixed Line Rate (MLR) networks are capable of delivering different bandwidth in a flexible manner. In this paper a simple routing algorithm is proposed to study the case of any link failure in MLR WDM networks. Here Poisson random traffic is used as a dynamic traffic for 24-hour duration. The proposed work can be achieved by deleting the failed link and then finding the new best possible shortest path between source and destination node. According to the traffic load light paths adjustments employ the addition of light paths under congestion and deletion of lightpaths which are not being used at a particular time. Simulation result shows the total number of lightpaths used, total number of addition and deletion of light paths under link safe and link failure case in mixed line rate (MLR) and single line rate (SLR) optical WDM networks.
MMINIMUM RESOURCE CONSUMPTIONS ROUTING FOR OPTICAL NETWORKSprj_publication
The problem of determining primary and backup paths for survivable optical WDM
networks is considered. Results of various available routing techniques that try to minimize
the combined cost of primary and the backup path are analyzed for the effects on network
parameters such as mean load, variance of the load on route, number of converters required
by the route and the length of the route. The route cost is modelled such a way that it is
extensible to include any new parameter and vary their relative importance. The efficiency of
such wavelength routed networks has been proved to improve for certain parameters, such as
reduction in blocking probability and number of converters required for desired performance.
The routing is enhanced to analyse effect on network parameters for all node full range
converters, limited number full converters, reserved primary and back up wavelengths and
with no such reservation.
A CRITICAL REVIEW OF THE ROUTING PROTOCOLS FOR COGNITIVE RADIO NETWORKS AND A...cscpconf
We present a critical review and analysis of different categories of routing protocols for cognitive radio networks. We first classify the available solutions to two broad categories: those
based on full spectrum knowledge (typically used to establish performance benchmarks) and those based on local spectrum knowledge (used for real-time implementation). The full spectrum knowledge based routing solutions are analyzed from a graph-theoretic point of view, and we review the layered graph, edge coloring and conflict graph models. We classify the various local spectrum knowledge based routing protocols into the following five categories: Minimum power, Minimum delay, Maximum throughput, Geographic and Class-based routing. A total of 25 routing protocols proposed for cognitive radio networks have been reviewed. We discuss the working principle and analyze the pros and cons of the routing protocols. Finally, we propose an idea of a load balancing-based local spectrum knowledge-based routing protocol for cognitive radio ad hoc networks.
Throughput Maximization of Cognitive Radio Multi Relay Network with Interfere...IJECEIAES
In this paper, an Orthogonal Frequency Division Multiplexing (OFDM) based cognitive multi relay network is investigated to maximize the transmission rate of the cognitive radio (CR) with enhanced fairness among CR users with interference to the primary users (PUs) being managed below a certain threshold level. In order to improve the transmission rate of the CR, optimization of the subcarrier pairing and power allocation is to be carried out simultaneously. Firstly joint optimization problem is formulated and Composite Genetic and Ordered Subcarrier Pairing (CGOSP) algorithm is proposed to solve the problem. The motivation behind merging genetic and OSP algorithm is to reduce the complexity of Genetic Algorithm (GA). Further, to have a fair allocation of resources among CR users, the Round Robin allocation method is adopted so as to allocate subcarrier pairs to relays efficiently. The degree of fairness of the system is calculated using Jain‟s Fairness Index (JFI). Simulation results demonstrate the significant improvement in transmission rate of the CR, low computational complexity and enhanced fairness.
Quadrant Based DIR in CWin Adaptation Mechanism for Multihop Wireless NetworkIJCI JOURNAL
In Multihop Wireless Networks, traffic forwarding capability of each node varies according to its level of contention. Each node can yield its channel access opportunity to its neighbouring nodes, so that all the nodes can evenly share the channel and have similar forwarding capability. In this manner the wireless channel is utilized effectively, which is achieved using Contention Window Adaptation Mechanism (CWAM). This mechanism achieves a higher end-to-end throughout but consumes the network power to a higher level. So, a newly proposed algorithm Quadrant- Based Directional Routing Protocol (Q-DIR) is implemented as a cross-layer with CWAM, to reduce the total network power consumption through limited flooding and also reduce the routing overheads, which eventually increases overall network throughput. This algorithm limits the broadcast region to a quadrant where the source node and the destination nodes are located. Implementation of the algorithm is done in Linux based NS-2 simulator
Routing in Cognitive Radio Networks - A SurveyIJERA Editor
Cognitive Radio Networks (CRNs) have been emerged as a revolutionary solution to migrate the spectrum
scarcity problem in wireless networks. Due to increasing demand for additional spectrum resources, CRNs have
been receiving significant research to solve issues related with spectrum underutilization. This technology
brings efficient spectrum usage and effective interference avoidance, and also brings new challenges to routing
in multi-hop Cognitive Radio Networks. In CRN, unlicensed users or secondary users are able to use
underutilized licensed channels, but they have to leave the channel if any interference is caused to the primary or
licensed users. So CR technology allows sharing of licensed spectrum band in opportunistic and non-interfering
manner. Different routing protocols have been proposed recently based on different design goals under different
assumptions.
Adaptive resources assignment in OFDM-based cognitive radio systemsIJECEIAES
Spectrum efficiency of orthogonal frequency division multiplexing (OFDM)-based cognitive radio (CR) systems can be improved by adaptive resources allocation. In resources allocation, transmission resources such as modulation level and transmission power are adaptively assigned based on channel variations. The goal of this paper is maximize the total transmission rate of secondary user (SU). Hence, we investigate adaptive power and modulation allocation to achieve this purpose. For power allocation, we investigate optimal and conventional methods and then introduce a novel suboptimal algorithm to calculate the transmission power of each subcarrier. In addition, for adaptive modulation, we consider two kinds of modulations including multi-quadrature amplitude modulation (MQAM) and multi-phase-shift keying (MPSK). Also, simulation results are indicated the performance of our algorithm.
USING CRM SOLUTIONS TO INCREASE SALES AND RETAIN VALUABLE CUSTOMERSInsideUp
CRM is an important tool for creating business success. The better your customer relationships, the
easier it is to conduct business and generate revenue. Using available technology to improve
customer relations management simply makes good business sense.
If you need further information, or would like assistance in selecting a CRM provider, go to
http://www.insideup.com/compare/customer_relationship_management
A modified distance regularized level set model for liver segmentation from c...sipij
Segmentation of organs from medical images is an active and interesting area of research. Liver segmentation incurs more challenges and difficulties compared with segmentation of other organs. In this paper we demonstrate a liver segmentation method for computer tomography images. We revisit the distance regularization level set (DRLS) model by deploying new balloon forces. These forces control the direction of the evolution and slow down the evolution process in regions that are associated with weak or without edges. The newly added balloon forces discourage the evolving contour from exceeding the liver
boundary or leaking at a region that is associated with a weak edge, or does not have an edge. Our
experimental results confirm that the method yields a satisfactory overall segmentation outcome. Comparing with the original DRLS model, our model is proven to be more effective in handling oversegmentation problems.
Time of arrival based localization in wireless sensor networks a non linear ...sipij
In this paper, we aim to obtain the location information of a sensor node deployed in a Wireless Sensor Network (WSN). Here, Time of Arrival based localization technique is considered. We calculate the position information of an unknown sensor node using the non- linear techniques. The performances of the techniques are compared with the Cramer Rao Lower bound (CRLB). Non-linear Least Squares and the Maximum Likelihood are the non-linear techniques that have been used to estimate the position of the unknown sensor node. Each of these non-linear techniques are iterative approaches, namely, Newton
Raphson estimate, Gauss Newton Estimate and the Steepest Descent estimate for comparison. Based on the
results of the simulation, the approaches have been compared. From the simulation study, Localization
based on Maximum Likelihood approach is having higher localization accuracy.
A divisive hierarchical clustering based method for indexing image informationsipij
In most practical applications of image retrieval, high-dimensional feature vectors are required, but current multi-dimensional indexing structures lose their efficiency with growth of dimensions. Our goal is to propose a divisive hierarchical clustering-based multi-dimensional indexing structure which is efficient in high-dimensional feature spaces. A projection pursuit method has been used for finding a component of the data, which data's projections onto it maximizes the approximation of negentropy for preparing essential information in order to partitioning of the data space. Various tests and experimental results on high-dimensional datasets indicate the performance of proposed method in comparison with others.
NIRS-BASED CORTICAL ACTIVATION ANALYSIS BY TEMPORAL CROSS CORRELATIONsipij
In this study we present a method of signal processing to determine dominant channels in near infrared spectroscopy (NIRS). To compare measuring channels and identify delays between them, cross correlation is computed. Furthermore, to find out possible dominant channels, a visual inspection was performed. The
outcomes demonstrated that the visual inspection exhibited evoked-related activations in the primary somatosensory cortex (S1) after stimulation which is consistent with comparable studies and the cross correlation study discovered dominant channels on both cerebral hemispheres. The analysis also showed a relationship between dominant channels and adjacent channels. For that reason, our results present a new
method to identify dominant regions in the cerebral cortex using near-infrared spectroscopy. These findings have also implications in the decrease of channels by eliminating irrelevant channels for the experiment.
A novel method is proposed for image segmentation based on probabilistic field theory. This model assumes that the whole pixels of an image and some unknown parameters form a field. According to this model, the pixel labels are generated by a compound function of the field. The main novelty of this model is it consider the features of the pixels and the interdependent among the pixels. The parameters are generated by a novel spatially variant mixture model and estimated by expectation-maximization (EM)-
based algorithm. Thus, we simultaneously impose the spatial smoothness on the prior knowledge. Numerical experiments are presented where the proposed method and other mixture model-based methods were tested on synthetic and real world images. These experimental results demonstrate that our algorithm achieves competitive performance compared to other methods.
The state-of-the-art Automatic Speech Recognition (ASR) systems lack the ability to identify spoken words if they have non-standard pronunciations. In this paper, we present a new classification algorithm to identify pronunciation variants. It uses Dynamic Phone Warping (DPW) technique to compute the
pronunciation-by-pronunciation phonetic distance and a threshold critical distance criterion for the classification. The proposed method consists of two steps; a training step to estimate a critical distance
parameter using transcribed data and in the second step, use this critical distance criterion to classify the input utterances into the pronunciation variants and OOV words.
The algorithm is implemented using Java language. The classifier is trained on data sets from TIMIT
speech corpus and CMU pronunciation dictionary. The confusion matrix and precision, recall and accuracy performance metrics are used for the performance evaluation. Experimental results show significant performance improvement over the existing classifiers.
ANALYSIS OF INTEREST POINTS OF CURVELET COEFFICIENTS CONTRIBUTIONS OF MICROS...sipij
This paper focuses on improved edge model based on Curvelet coefficients analysis. Curvelet transform is
a powerful tool for multiresolution representation of object with anisotropic edge. Curvelet coefficients
contributions have been analyzed using Scale Invariant Feature Transform (SIFT), commonly used to study
local structure in images. The permutation of Curvelet coefficients from original image and edges image
obtained from gradient operator is used to improve original edges. Experimental results show that this
method brings out details on edges when the decomposition scale increases.
Digital camera and mobile document image acquisition are new trends arising in the world of Optical Character Recognition and text detection. In some cases, such process integrates many distortions and produces poorly scanned text or text-photo images and natural images, leading to an unreliable OCR digitization. In this paper, we present a novel nonparametric and unsupervised method to compensate for
undesirable document image distortions aiming to optimally improve OCR accuracy. Our approach relies on a very efficient stack of document image enhancing techniques to recover deformation of the entire document image. First, we propose a local brightness and contrast adjustment method to effectively handle lighting variations and the irregular distribution of image illumination. Second, we use an optimized greyscale conversion algorithm to transform our document image to greyscale level. Third, we sharpen the
useful information in the resulting greyscale image using Un-sharp Masking method. Finally, an optimal global binarization approach is used to prepare the final document image to OCR recognition. The proposed approach can significantly improve text detection rate and optical character recognition
accuracy. To demonstrate the efficiency of our approach, an exhaustive experimentation on a standard dataset is presented.
My Best friend Izaiah Kaine Breeden....recently left this world..and he got what he wanted..he is flying with the angels.....Rest In Paradise Sweet bubbles...Buttercup loves you</3
Modeling and Simulation of Wavelength-Routed optical Networksijceronline
All-optical Wavelength Division Multiplexing (WDM) networks providing extremely large bandwidths are among the most promising solutions to the increasing need for high-speed data transport. A lightpath has a specific route and one or more wavelengths through which the information is routed from the source to the destination node. In wavelength-routed optical networks, data are transmitted solely in the optical domain along lightpaths from source to destination without being converted into the electronic form and each lightpath is allowed to use the same wavelength on all the links along its path. This restriction is known as the wavelength continuity constraint. And it leads to an issue called as blocking in networks. Optical wavelength conversion with suitable Routing and wavelength assignment (RWA) can increase the performance and capacity of optical networks by eliminating this restriction and relaxing the wavelength continuity constraint. In this research, we analyze the problem of placing a limited number of wavelength converters in a mesh network using Weighted Maximum Segment Length (WMSL) converter placement algorithm. It employs Least-Loaded Routing and First-Fit (LLR-FF) RWA algorithm. It is tested on varying number of nodes in network and its respective blocking probabilities are calculated. The proposed algorithm provides the minimum blocking probability on optimal wavelength converters placement.
SNR/RP Aware Routing Algorithm: Cross-Layer Design for MANETSijwmn
Routing in MANET is complex due to the fact that the network graph is episodically connected and nodes get only intermittently connected because of nodes mobility, terrain, weather, and jamming that change topology rapidly. In this paper, we propose cross-layer design to achieve a reliable data transmission in MANET. A key challenge is to create a mechanism that can provide good delivery performance and high quality of service in intermittent networks. The key components of our approach include a cross-layer design (CLD) to improve information sharing between different protocol layers. In order to improve the end-to-end performance of MANET, we present mechanism that allows the network layer to adjust its routing protocol dynamically based on SNR and Received Power along the end-to-end routing path for each transmission link. We evaluate our approach using one of common MANET routing protocols, DSR, to illustrate that our CLD improved the performance of DSR.
SNR/RP Aware Routing Algorithm: Cross-Layer Design for MANETSijwmn
Routing in MANET is complex due to the fact that the network graph is episodically connected and nodes get only intermittently connected because of nodes mobility, terrain, weather, and jamming that change topology rapidly. In this paper, we propose cross-layer design to achieve a reliable data transmission in MANET. A key challenge is to create a mechanism that can provide good delivery performance and high quality of service in intermittent networks. The key components of our approach include a cross-layer design (CLD) to improve information sharing between different protocol layers. In order to improve the end-to-end performance of MANET, we present mechanism that allows the network layer to adjust its routing protocol dynamically based on SNR and Received Power along the end-to-end routing path for each transmission link. We evaluate our approach using one of common MANET routing protocols, DSR, to illustrate that our CLD improved the performance of DSR
ANALYSIS AND STUDY OF MATHEMATICAL MODELS FOR RWA PROBLEM IN OPTICAL NETWORKSIJEEE
Blocking probability has been one of the key performance to solve Routing and Wavelength Assignment problem (RWA) indexes in the design of wavelength-routed all-optical WDM networks. To evaluate blocking probability different analytical model are introduced.
The Impact of Signal Strength over Routing Protocols in Wireless NetworksDr. Amarjeet Singh
In ad hoc routing protocols the source node
may need an intermediate nodes to transmit the packets into
the destination if the destination is not within transmission
range of the source. This paper studies the impact of signal
strength of nodes over ad hoc routing protocols and explains
an important effect of signal strength on ad hoc routing
protocols in four different directions including the routes and
the nodes. As a result the study give an important
improvement in ad hoc routing protocols when using signal
strength compared to other ad hoc routing protocols without
considering signal strength.
Performance analysis for Adaptive Subcarriers Allocation in Coherent Optical ...iosrjce
The constraint to satisfy the need of increased bandwidth requirement for high speed applications
with higher performance has been a motivation to work on Optical Orthogonal Frequency division multiplexing
(OOFDM) technique with coherent detection. We implement the coherent optical OFDM (CO-OOFDM)
technique and investigate the effect of the number of sub-carriers on performance over single mode fiber (SMF)
links. To explore improvement in performance adaptive subcarriers has been selected by assigning subcarriers
to user according to the conditions of channel. An adaptive subcarrier allocation has been investigated and
performance comparison for proportional and equal allocation has been carried over.
Fault Tolerant Congestion based Algorithms in OBS NetworkCSCJournals
In Optical Burst Switched networks, each light path carry huge amount of traffic, path failures may damage the user application. Hence fault-tolerance becomes an important issue on these networks. Blocking probability is a key index of quality of service in Optical Burst Switched (OBS) network. The Erlang formula has been used extensively in the traffic engineering of optical communication to calculate the blocking probability. The paper revisits burst contention resolution problems in OBS networks. When the network is overloaded, no contention resolution scheme would effectively avoid the collision and cause blocking. It is important to first decide, a good routing algorithm and then to choose a wavelength assignment scheme. In this paper we have developed two algorithms, Fault Tolerant Optimized Blocking Algorithm (FTOBA) and Fault Tolerant Least Congestion Algorithm (FTLCA) and then compare the performance of these algorithms on the basis of blocking probability. These algorithms are based upon the congestion on path in OBS network and based on the simulation results, we shows that the reliable and fault tolerant routing algorithms reduces the blocking probability.
Analysis of FSR, LANMAR and DYMO under MANETidescitation
A movable ad hoc system (MANET) is a self-configuring communications set of
connections of mobile procedure associated by wireless. Each mechanism in a MANET is
free to move independently in some way, and will therefore modify its relations to other
devices frequently [2]. The primary purpose of any ad-hoc network routing protocol is to
meet the challenges of the dynamically changing topology and establish an efficient route
connecting every two nodes. In this paper three protocols FSR, LANMAR and DYMO are
compared by using random waypoint mobility in few nodes with varying packet sizes in
CBR traffic. The parameters or metrics are used to assess the performance of protocols with
and without Black Hole attack, that are data Packet Delivery ratio and Average Jitter with
varying data traffic CBR (Constant Bit Ratio) using Qual Net 5.0.2 simulator.
Fuzzy Controller Based Stable Routes with Lifetime Prediction in MANETsCSCJournals
In ad hoc networks, the nodes are dynamically and arbitrary located in a manner that the interconnections between nodes are changing frequently. Thus, designing an effective routing protocol is a critical issue. In this paper, we propose a fuzzy based routing method that selects the most stable route (FSRS) considering the number of intermediate nodes, packet queue occupancy, and internodes distances. Also it takes the produced cost of the selected route as an input to another fuzzy controller predicts its lifetime (FRLP), the evaluation of the proposed method is performed using OMNet++4.0 simulator in terms of packet delivery ratio, average end-to-end delay and normalized routing load.
A SEMI BLIND CHANNEL ESTIMATION METHOD BASED ON HYBRID NEURAL NETWORKS FOR UP...ijwmn
The paper describes how to improve channel estimation in Single Carrier Frequency Division Multiple
Access (SC-FDMA) system, using a Hybrid Artificial Neural Networks (HANN). The 3rd Generation
Partnership Project (3GPP) standards for uplink Long Term Evolution Advanced (LTE-A) uses pilot based
channel estimation technique. This kind of channel estimation method suffers from a considerable loss
ofbitrate due to pilot insertion; all data frame sent contains reference signal. The HANN converts data
aided channel estimator to semi blind channel estimator. To increase convergence speed, HANN uses some
channel propagation Fuzzy Rules to initialize Neural Network parameters before learning instead of a
random initialization, so its learning phase ismore rapidly compared to classic ANN.HANN allows more
bandwidth efficient and less complexity. Simulation results show that HANN has better computational
efficiency than the Minimum Mean Square Error (MMSE) estimator and has faster convergence than
classic Neural Networks estimators.
IMPACT OF ENERGY AND LINK QUALITY INDICATOR WITH LINK QUALITY ESTIMATORS IN W...Fransiskeran
The Link Quality Indicator (LQI) and Residual Energy have a fundamental impact on the network
performance in Wireless Sensor Networks (WSNs) and affects as well in the life time of nodes. This paper
will provide a comparative of Link Quality Estimator, the Link Quality Estimator with Link Quality
Indicator and Link Quality Estimator with Residual Energy. In this paper we develop a Collect Tree
Protocol (CTP) and compare the performance of LQI and Residual Energy, and show their effect on the
packet delivery ratio and throughput, covering the characteristics of low-power links, and their
performance to the best of our knowledge, we believe that our efforts would have implementations on
embedded application.
Impact of energy and link quality indicator with link quality estimators in w...graphhoc
The Link Quality Indicator (LQI) and Residual Energy have a fundamental impact on the network
performance in Wireless Sensor Networks (WSNs) and affects as well in the life time of nodes. This paper
will provide a comparative of Link Quality Estimator, the Link Quality Estimator with Link Quality
Indicator and Link Quality Estimator with Residual Energy. In this paper we develop a Collect Tree
Protocol (CTP) and compare the performance of LQI and Residual Energy, and show their effect on the
packet delivery ratio and throughput, covering the characteristics of low-power links, and their
performance to the best of our knowledge, we believe that our efforts would have implementations on
embedded application.
Performance Evaluation of Consumed Energy-Type-Aware Routing (CETAR) For Wire...ijwmn
This work evaluates the performance of Consumed-Energy-Type-Aware Routing (CETAR) which incorporates the amount of energy consumed per type of operation for routing decision to extend the lifetime of the Wireless Sensor Networks (WSNs). CETAR makes routing decision using statistics of the energy consumed for each type of node activities including sensing, data processing, data transmission as a source node, and routing operations. In particular, CETAR encourages a node which seldom plays a role of source node as a routing node to preserve the energy of active source nodes to prolong the functionality of the WSNs. Extensive simulation study demonstrates that the lifetime of the Geographic and Energy Aware Routing (GEAR) can be significantly extended with CETAR. With its adaptability to deployed sensor node behaviors, the significance of CETAR to extend the lifetime of WSNs is clear.
Mobility and Propagation Models in Multi-hop Cognitive Radio Networksszhb
Cognitive radio networks allow unlicensed
(secondary) users to opportunistically utilize the idle
resource of a licensed network for communication
without affecting the quality of service being offered to
the primary or licensed users. This paper investigates
the effect of mobility on performance of multi-hop
cognitive radio network under various propagation
models. MPEG4 video; a bandwidth intensive traffic, is
tested over these network conditions for secondary
users and results are validated using NS2 simulations.
Performance metrics used for evaluation include
throughput, delay variations etc.
Similar to Routing in All-Optical Networks Using Recursive State Space Technique (20)
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Routing in All-Optical Networks Using Recursive State Space Technique
1. Signal & Image Processing : An International Journal (SIPIJ) Vol.7, No.2, April 2016
DOI : 10.5121/sipij.2016.7202 23
ROUTING IN ALL-OPTICAL NETWORKS USING
RECURSIVE STATE SPACE TECHNIQUE
Mohan Kumar S1
and Jagadeesha S N2
1
Ph.D, Research Center, Jawaharalal Nehru National College of Engineering,
shimoga, Karnataka, India.
2
Department of Computer Science and Engineering,
Jawaharalal Nehru National College of Engineering, shimoga.
ABSTRACT
In this papr, we have minimized the effects of failures on network performace, by using suitable Routing
and Wavelenghth Assignment(RWA) method without disturbing other performance criteria such as blocking
probability(BP) and network management(NM). The computation complexity is reduced by using Kalaman
Filter(KF) techniques. The minimum reconfiguration probability routing (MRPR) algorithm must be
able to select most reliable routes and assign wavelengths to connections in a manner that utilizes the light
path(LP) established efficiently considering all possible requests.
KEYWORDS
Routing Wavelength Assignment (RWA), Blocking Probability(BP) Network Management(NM), Kalaman
Filter(KF),Wavelength interchange(WI), Light Path(LP), Process Noise(PN), Least Loaded Routing(LLR),
Minimum Reconfiguration Probability Routing (MRPR), Max-Sum Routing(MR), Adaptive
Unconstrained Routing(AUR)
1. INTRODUCTION
In this paper, we have considered a suitable algorithm for Routing and Wavelength
Assignment(RWA) for wide area networks, such as Wavelength routing network (WRN) which
has scalable architecture. WRN has mesh like structure consisting of links having one or more
fibers at each input port to output port in the optical domain. The challenging problem in these
networks are RWA and controlling problems. In these problems, provision of connections, called
lightpaths in a scalable architecture usually span multiple links. Hence, light path may be
assigned to different links along the route. This process is called Routing and Wavelength
Assignment. In this process, lightpaths share one or more fibers links and different wavelengths.
To establish a lightpath, a route should be discovered between source and destination and suitable
wavelength need to be assigned to that route. Some of the commonly used performance criteria
for Routing and Wavelength Assignment are throughput and blocking probability[10]. There are
many algorithms proposed for this purpose with optimal solutions[10]. The main assumption of
these algorithms are that, traffic volume is static for a long time period and these networks are
reconfigured only to reflect changes in the long term traffic demand[1]. Although static demand
has been reasonable assumption for voice data communication, in current trends and future, data
intensive networks are rapidly changing. Therefore dynamic RWA algorithms which support
request arrivals and lightpath terminations at stochastic/randaom times are needed. Hence
predefined set of routes are searched in a predefined order to accommodate the request. Then the
2. Signal & Image Processing : An International Journal (SIPIJ) Vol.7, No.2, April 2016
24
smallest index randomly selects a wavelength available on the route. If not, request is blocked.
Usually one or more minimum hop routes are used and fixed order search is carried out without
taking into account the congestion on the link. It will not further improve blocking performance.
An adaptive RWA algorithm makes use of the network state information at the time of routing to
find the optimum path using filter approach. Least loaded routing(LLR), Max-sum routing (MR)
and Adaptive unconstrained routing(AUR) are the examples for adaptive RWA process[3].
An Optical switch has ability to minimize the effects of failures on network performance by using
a suitable routing and wavelength assignment method without disturbing other performance
criteria such as network management and blocking probability[4]. The main challenge in the
Wavelength Routing Network (WRN) is the provision of connections called lightpaths between
the users of network. This method is called Routing and Wavelength Assignment scheme
(RWA)[2][10]. Here, one of the efficient Routing Wavelength Assignment method known as
statistically predictive dynamic RWA algorithm[3] is implemented using the kalman filter. This
algorithm makes use of the network state information at the time of routing to find the optimum
path according to an objective function for the request. By choosing as much reliable router/links
as possible in the RWA process, it is possible to minimize the mean number of light paths broken
due to failure. However, considering only reliability characteristics, lightpaths may have to be
routed on longer routes and blocking performance may be deteriorated. For this reason, this
algorithm is based on the joint optimization of the probability of reconfiguration due to
router/link failures and probability of blocking for the future requests. Therefore effect of
potential router/link failures is minimized without disturbing blocking probability
performance[7]. For this purpose lightpath arrival/holding time and failure arrival statistics
collected for each link and router, as well as the network state information at the time of request
arrival are used in routing decisions. That is, the behavior of the network is predicted by current
state information and statistics of the past, to assign the most reliable path to the lightpath
requests[9].
In the following section Minimum Reconfiguration Probability Routing (MRPR) algorithm is
presented, then the cost function is derived to process RWA in WRN networks. Finally
simulations studies are presented and analyzed in section 5.0. The concluding remarks and
directions for future work are presented in section 6.0.
2. MINIMUM COST PATH FOR A LIGHTPATH
In Wavelength Interchange networks, the wavelength routers have wavelength converters at the
output ports and are able to change the wavelength of all lightpath passing through it. Hence the
blocking of requests due to wavelength conflicts can be avoided and the blocking probability can
be significantly reduced[7]. Wavelength routers can also switch the wavelength of lightpaths, the
RWA problem in WI networks reduce to the light path routing problem. The routing problem is
solved, wavelengths on the links along the route can be assigned randomly. In order to find the
route with minimum reconfiguration probability for a lightpath request, a simple auxiliary graph
G= (N,E),where nodes N represent the routers and each directed edge(i,j), E represents the link
(i,j) from router i to router j, is constructed. Then, cost of each edge(i,j) is set to:
ܥ = ൜
∞
− ln൫1 − ܨ൯ − ln൫1 − ܴ൯ − ln൫1 − ܨ൯ ,
ௗ ௧ ௨௦ௗ
௧ ௪௦
....................(1)
Where, Fij is the probability of reconfiguration due to failure and Rij is the probability of
reconfiguration due to repacking on the link from router i to router j and Fj is the probability of
reconfiguration due to failure on router j for the lightpath to be routed [3]. In equation(1), Edge
cannot be used' means that the link (i,j) has no free wavelength channel at the time of routing.
3. Signal & Image Processing : An International Journal (SIPIJ) Vol.7, No.2, April 2016
25
2.1 Reconfiguration Due to Failure
In this paper, we present an efficient routing algorithm based on Kalman Filtering techniques to
predict a future state of the router in order to determine the accurate state of router to reconfigure
due to link or route failure. we propose the usage of Kalman Filters in routing. First, Kalman
Filter is employed for estimating the system based on several unknown parameters such as
processes and measurement noises at routing device.The probability of reconfiguration due to
failure for a lightpath on a resource (link or router) can be predicted in terms of mean of inter-
arrival times on that resource and mean of holding time for the lightpaths between the source and
destination routers. Probability of configuration due to failure, F, for a lightpath on a resource is
equal to the probability of a failure on that resource during the lifetime of the lightpath[3]. F can
be found as:
ܨ = ( ݂(ݔሻ݀ݔሻℎ(ݕሻ ݀ݕ
௬
௫ୀ
∞
௬ୀ
.............................................(2)
Where x is random variable representing failure inter-arrival times on the resource, f(x) is the
probability distribution function (pdf) of random variable x, y is a random variable representing
the lightpath holding times between the source and destination routers, h(y) is the pdf of random
variable y.
To determine F, knowledge of f(x) and h(y) are required. A straightforward way to evaluate
equation(2) is to approximate distribution function with mean and variance equal to the
corresponding values obtained from the statistics. Lightpath holding times are usually
approximated by an exponential distribution function and failure inter-arrival times are usually
approximated by an exponential or a Weibull distribution function, which will closely
approximate the observed phenomena. This calculation is done using Kalman equations(11) in
order to reduce the computational complexity. In particular, if both failures inter arrival-time and
lightpath holding times are approximated by exponential distribution functions, F can be found
as:
ܨ = න (න
1
݉
݁
ି
௫
ೕ ௗ௫
ሻ
1
݉
݁
ି
௬
௧ఏ
݀ݕ =
݉
݉ + ݉
௬
௫ୀ
∞
௬ୀ
… … … … . . . . . (3ሻ
Where, mh and mf are the mean holding time and mean failure inter arrival time, respectively.
2.2 Reconfiguration Due to Repacking
The probability of reconfiguration due to repacking, R, for a lightpath on a link in the network
can be predicted in terms of the number of lightpaths currently passing through the link, arrival
rate and service time statistics for the lightpaths on the link[3]. To find R, we need to find the
probability of a call blocked due to lack of free capacity on that link during the lifetime of the
lightpath.
In order to evaluate the approximate repacking probabilities, we make following assumptions:
• Links in the network are independent of each other. That is, lightpath arrivals on each
link are independent processes and a lightpath on an ‘n’ link route behaves like ‘n’
independent lightpaths.
• Poisson arrivals and exponential holding times: lightpaths arrive on alink under
consideration according to a Poisson process with rate λ and lightpath holding times are
exponentially distributed with mean 1/µ.
4. Signal & Image Processing : An International Journal (SIPIJ) Vol.7, No.2, April 2016
26
• The repacking probability on the link ‘R’ is independent of other links. Therefore, the
repacking probability for a lightpath on route ‘r’ denoted as Rr can be found from
individual link repacking probabilities, Rl as:
ܴ = 1 − ෑ(1 − ܴሻ … … … … … . … … … … … … … … .. (4ሻ
∈ఘ
With the help of these assumptions, we can find the repacking probability ‘R’ for a lightpath
request, lp0 on a link with capacity C and having N0 lightpaths (N0<C), can be by modeling as a
Markov Process and is shown in figure1. In this process, all states except the one labeled by ‘r’
are transient states corresponding to the number of lightpaths on the link before any repacking is
experienced. On the other hand, the state labeled by ‘r’ is the trapping state, which represents the
repacking occurrence before the termination of lightpath.
́ଵ (ݐሻ = ߣଵ(ݐሻ + ߤଶ(ݐሻ…………………..…………(5)
́ଵ (ݐሻ = −(ߣ + (݊ − 1ሻߤሻ(ݐሻ + ݊ߤାଵ(ݐሻ + ߣିଵ(ݐሻ, 1 < ݊ < ܿ,………(6)
́ (ݐሻ = −(ߣ + (ܿ − 1ሻߤሻ(ݐሻ + ߣିଵ(ݐሻ…………………………….(7)
́ (ݐሻ = ߣ(ݐሻ,……………… ……(8)
(ݐሻ = ൜
1, ݊ = ݊ + 1
,ݔ ݐℎ݁݁ݏ݅ݓݎ
1 ≤ ݊ ≤ ܿ (0ሻ = 0………….(9)
Figure 1: Constructed State diagram of Markov model to determine R
Where pn(t) for n= 1,2..C are the probability of having n light paths on the link at time ‘t’ and no
repacking has occurred up to time ‘t’. The Pr(t) is the probability of experiencing a repacking on
the link up to time t, and (N0 +1) is the state of the link at time t=0,if lightpath is routed on this
link. In this process, we assume that lp0 remains in the link for t=>0, or equivalently, at least one
lightpath exists in the link for t=>0. Therefore, the number of lightpaths that may terminate at
state N equals N-1, and death rate at state N equals (N-1) µ. Finally the probability of
experiencing repacking on the link until lp0 terminates can be found by finding the expected value
of Pr (t) as:
ܴ = ܲ(ݐሻߤ݁ିఓ௧
݀ݐ
∞
……………………………………(10)
Therefore, if we assume that when repacking occurs the lightpath to be re-routed is randomly
selected lightpath in the link, we can find the probability of reconfiguration due to repacking for
a lightpath as:
ܴ =
ଵ
ܲ(ݐሻߤ݁ିఓ௧
݀ݐ
∞
……………………………….(11)
After solving the equations(10) and (11), probability of the repacking can be calculated as:
5. Signal & Image Processing : An International Journal (SIPIJ) Vol.7, No.2, April 2016
27
ܴ =
ா(,ఘሻ
∗ா(,ఘሻ
..............................................................(12)
Where ρ =λ/µ and E (n, ρ) is the Erlang Loss Formula defined as:
,݊(ܧ ߩሻ =
ρ
!ൗ
∑ ρ
!ൗ
సబ
................................................................(13)
As a result, we find the path reconfiguration probabilities in terms of router or link failure and
link repacking probabilities as:
ܥ = 1 − ෑ (1 − ܨ
(,ሻ∈ఘ
ሻ ൫1 − ܴ൯൫1 − ܨ ൯ … … … … … … … … … … … (14ሻ
Where Cij is the cost of lightpath between nodes i and j. Fij is the probability of reconfiguration
due to failure in the link between node i and j. Rij is the probability of repacking between the
nodes i and j and Fj is the pro bability of reconfiguration due to the failure in the router located
at node j [8][9].
3. KALMAN FILTER TECHNIQUE
Kalman filter can be employed as a alternative to the Markov model to estimate the arrival and
holding times in an WRN and WI networks and solve the RWA problem are to be estimated.
3.1 Estimating the Arrival Time at Nodes of Stochastic and Dynamic Networks
Using Kalman Filter Technique
To estimate the arrival times at the nodes of a stochastic and dynamic network[5][7] a step prior
to route planning. A algorithm is developed to predict the traveling times along the arcs and
estimate the arrival times at the nodes of the network in real-time. It is shown that, under fairly
mild conditions, the developed arrival time estimator is unbiased and that the error variance of the
estimator is bounded.
Given a directed graph G = (N, A), with |N| = n and |A| = m, in dynamic problems, a non-
negative travel time dij(t) is associated with each arc(i, j) with the following meaning:
if t is a feasible leaving time from node i along the arc(i, j), then t + dij(t) is the arrival time at
node j. In addition to the travel time, a time-dependent travel cost cij(t) can be associated with (i,
j), which is the cost of traveling from i to j through (i, j) starting at time t. There is the possibility
of waiting at the nodes; in this case, a (unit time) waiting cost wi (t) can be associated with node i,
which gives the cost of waiting for unit time at i at time t. Given a route in a dynamic stochastic
transportation network, we develop a methodology to estimate the arrival times at the nodes of
that route. To estimate the arrival times, first step is developing a technique to predict the
traveling times on the arcs of the network in real-time. In this technique, available historical data
are used for predicting the traveling times, and new measurements are used to correct and update
our prediction at each instant of time. More precisely, this proposed methodology consists of the
following two stages:
1. Predicting traveling times on arcs: Given the time of the day together with the
historical and real-time data of traveling times on arcs of a transportation network, we predict the
future traveling times on those arcs, recursively.
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28
2. Estimating arrival times at nodes: Given a route in the network, the departure time
from the first node of the route, and the predicted traveling times on arcs of the network (found in
stage 1), the arrival times at the nodes of the route are estimated.
In the following section, each stage is investigated and discussed in detail.
3.2 Predicting the Traveling Times on Arcs :
Let G:(N,A) be a transportation network (graph) with node set N={1...i, 1...j} and arc set A=(i,j).
A typical transportation network is shown in Figure(2).
Figure 2: A typical transportation network
In Figure(2) Solid lines represent the direct connections (arcs) between two adjacent nodes and
dashed lines are indirect connections, which consist of two or more arcs.
It is assumed that the historical data as well as the real-time information of traveling times on arcs
of the network are available. Let be the length of the planning horizon, K be an index of time in
the planning horizon, Xij(k) be the traveling time between nodes i and j at time k, Xh
ij(k) be the
historical traveling time on arc (i,j) at time k, Uij (k) be the historical change in the traveling time
on arc (i, j) from time k to k+1, Yij(k) be the measured traveling time on arc (i, j) at time k.
The dynamic behavior of the traveling time on arc (i ,j) is given by the system model equation as:
ܺ(݇ + 1ሻ = ܺ(݇ሻ + ܷ(݇ሻ + ܹ(݇ሻ … … … … … … … … … . . . (15ሻ
ܻ(݇ሻ = ܺ(݇ሻ + ܸ(݇ሻ … … … … … … … … … … . . . … (16ሻ
Where ܹ(݇ሻ is the traveling time disturbance on arc (i, j) at time k which is caused by the
addition of white Gaussian noise during switching from one wavelength to another wavelength at
each node. This noise is Known as process noise and ܸ(݇ሻ is the error in the traveling time
measurement of arc (i, j) at time k which is caused by the delay in the measurement. This delay in
measurement is known as measurement noise. ܹ(݇ሻ represents the real-time changes in the
traveling time at time k, which are not included in the historical data ܷ(݇ሻ[6].
Here ܷ(݇ሻ , ܹ(݇ሻ, ܸ(݇ሻ and ܺ(0ሻ are all mutually uncorrelated Gaussian random
variables with the following specifications:
ܧ൛ܷ (݇ሻൟ = ߬(ሻ(݇ሻ, ܧ൛ܷ (݇ሻ, ܷ(݈ሻൟ = ቐ
ߪ
ଶ(݇ሻ+= ߬
ଶ
(݇ሻ ݇ = 1
0,
݇! = 1
........(17)
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ܧ൛ܹ (݇ሻൟ = 0; ; , ܧ൛ܹ (݇ሻ, ܹ(݈ሻൟ = ൜
ߪ
ଶ(݇ሻ ݇ = 1
0 ݇! = 1
..................(18)
ܧ൛ܹ (݇ሻൟ = 0; ; , ܧ൛ܸ (݇ሻ, ܸ(݈ሻൟ = ൜
ߪ
ଶ(݇ሻ ݇ = 1
0 ݇! = 1
....................(19)
3.3 Single Stage Predictor
In the single stage predictor case, given the measured traveling time ܻ(݇ሻ on arc (i, j) at time k,
traveling time estimation ݔො(݇ +
ଵ
ሻ is done on the arc (i, j) at the time k+1. The estimator that
minimizes the mean squared error of the estimation is given as:
n ݔො ቀ݇ +
ଵ
ቁ = ܧ൛ܺ(݇ + 1ሻ| ܻ(݇ሻൟ.............................(20)
From the equation (20), ݔො(݇ +
ଵ
ሻ denotes the estimate of the travel time ܺ (݇ + 1ሻ given
measurement ܻ(݇ሻ and is called the mean-squared predicted estimator of ܺ (݇ + 1ሻ
Using designed dynamical model in equation 15, the predicted estimator ݔො(݇ +
ଵ
ሻ can be
written as:
ݔො ቀ݇ +
ଵ
ቁ = ܧ൛ܺ(݇ሻ + ܷ (݇ሻ + ܹ(݇ሻ|ܻ(݇ሻൟ...........................(21)
= ݔො(݇|݇ሻ + ߬(݇ሻ........................................................(22)
Where ݔො(݇|݇ሻ is the mean squared filtered estimator of ܺ(݇ሻ given ܻ(݇ሻ. In equation (22)
indicates that to calculate the predicted estimator ݔො ቀ݇ +
ଵ
ቁ the value of the filtered estimator
ݔො(݇|݇ሻ should be obtained. The mean and variance of the single stage predictor error of the
mean-squared predicted estimator of ݔ(݇ + 1ሻ is calculated. Finally single stage predictor is
extended to mth
stage predictor, with the measured traveling time ܻ(݇ሻ at time k on arc (i, j), to
determine an unbiased estimate of traveling time on that arc at time k +m, where m>=1. This
design part gives the traveling time estimation for the single stage between two nodes in the
network.
3.4 The Mth
Stage Predictor
Similar to the single-stage predictor, estimator that minimizes the mean-squared estimation is
given as:
ݔො ቀ݇ +
ቁ = ܧ൛ܺ(݇ + ݉ሻ|ܻ(݇ሻൟ.................................(23)
Whereݔො ቀ݇ +
ቁ is the estimate of ܺ(݇ + ݉ሻ given the measurement ܻ(݇ሻ . The mean and
error covariance of mth
stage predictor is calculated. The predicted estimate of traveling time
ܺ(݇ + ݉ሻ on arc (i, j) at time k+m, m>=1, depends on the value of the filtered estimator
ݔො(݇/݇ሻ which is estimate of traveling time ݔො(݇ሻ at time k, given the measured traveling time
ܻ(݇ሻ at time k, The predictor-corrector form of Kalman filter is used here to calculate the
filtered estimator ݔො(݇/݇ሻ as follows:
ݔො(݇/݇ሻ = ݔො(݇/݇ − 1ሻ + ܭ(݇ሻ|ܻ (݇ሻ − ݔො(݇/݇ − 1ሻ..............(24)
8. Signal & Image Processing : An International Journal (SIPIJ) Vol.7, No.2, April 2016
30
Where ܭ(݇ሻ is the Kalman gain of arc(i,j) at time k is calculated to update the previous
measurements. Therefore, at each time k and by using the mth stage predictor, the traveling time
ݔො ቀ݇ +
ቁ on each arc (i,j) at time k+m can be predicted.
In the following section, Kalman filtering corrector-predictor technique is used to estimate the
future traveling times on the arcs of graph G as shown in Figure(3).
3.5 Estimating Arrival Times at Nodes:
In the previous section, a technique based on Kalman filter to predict the traveling times on arcs
of a given transportation network is explored. In this section, predicted traveling times on arcs is
required to estimate the arrival times at the nodes of the network. Consider the graph ‘G’ as
shown in figure(3).
Figure 3 : A typical route r in the graph G
The route ‘r’ defined in graph ‘G’ as a sequence of nodes visited in the specified order. In
Figure(3) shows a typical route ‘r’, which for convenience is represented as an ordered set i.e., R
={1, 2, i, j,.., d}. Let Ar be the arc set associated with route r.
Assumption is made such that the departure time from node 1 on route r, denoted by ܼ
ଵ , is
given using the developed technique in previous Section, the predicted traveling times on arcs of
graph ‘G’ are available. Given ܼ
ଵ , the arrival times at all the other nodes on route r in Figure(3)
can be determined using the following set of equations.
ܼଶ
= ܼଵ
+ ܺଵଶ(ܼଵ
ሻ...................................................(25)
ܼଷ
= ܼଶ
+ ܺଶଷ(ܼଵଶ
ሻ.....................................................(26)
.....
.....
ܼ
= ܼ
+ ܺଵଶ(ܼ
ሻ......................................................(27)
....
....
ܼௗ
= ܼௗିଵ
+ ܺଵௗିଵ,ௗ(ܼௗିଵ
ሻ.........................................(28)
Where ܼ
is the arrival time at node i taking route r, and ܺଵଶ(ܼ
ሻ is the traveling time on arc (i,
j) at time ܼ
. Assumption is made such that the departure time from node i is equal to the arrival
time at that node. This is achieved by assuming that there is no service time associated with the
nodes of network G.
3.6 Estimating the Holding Time at Nodes of Dynamic Stochastic Networks
Given a directed graph G = (N, A), with |N| = n and |A| = m, in dynamic problems, a non-
negative travel time ݀(ݐሻ is associated with each arc (i, j) with the following meaning: if t is a
feasible leaving time from node j along the arc (i, j), then t + ݀(ݐሻ is the holding time at node
j. In addition to the travel time, a time-dependent travel cost Cij (t) can be associated with (i, j),
9. Signal & Image Processing : An International Journal (SIPIJ) Vol.7, No.2, April 2016
31
which is the cost of traveling from i to j through (i, j). Mean holding time is calculated by
estimating the traveling time between the source and destination nodes and prior knowledge of
departure time at that node. Then ijth
Kalman filter coefficients are calculated on the basis of
above design. The implementation part is described in the following section.
4. PROPASED SYSTEM TO ESTIMATE AND MEASURE NOISE
Noises are random background events which have to be dealt with in every system processing
real input signals (requests). They are not part of the ideal signal and may be caused by an effect
of neighboring sources or delay in processing the request. The characteristics of noise depend on
their source.
4.1 Implementation of Process Noise to Estimate The Unknown Parameters:
The process noise is generated because of the signals being processed on the same wavelength
channel for some random period. Process noise can be analyzed both in wavelength convertible
networks as well as networks without converters. Q (the model/input noise covariance)
contributes to the overall uncertainty of the estimate as it is added to P (the error covariance
matrix) in each time step. When Q is large the Kalman Filter large changes in the actual output
more closely. This means there is a performance trade-off between tracking and noise in the
output in the choice of Q for the Kalman Filter[6][11].
4.2 Implementation of Measurement Noise to Estimate the Unknown Parameters:
The measurement noise is added to the signal because of the delay in the measurement device. If
the measuring device fails to measure the input data at some fixed time, then there will be delay.
Data will be the lightpath request. If the lightpath request is blocked for more than its lifetime,
then it is rejected permanently.
R (the measurement noise covariance) determines how much information from the sample is
used. If R is high the Kalman Filter measurement isn't very accurate. When R is smaller the
Kalman Filter output will follow the measurements more closely and accept more information
from them.
The effect of P (the error covariance matrix) on the Kalman Filter estimate is that when P is small
the Kalman Filter incorporates a lot less of the measurement into the estimate as it is fairly certain
of its time. Ideally P gets as close to zero as possible to indicate that the model is accurate. P is
generally reduced by measurements received; as there is more confidence in the estimated state if
there is a measurement to confirm it. However the reduction of P is limited by the model/input
variable error covariance Q which is added at each time step. Both P and R are incorporated into
the Kalman Filter through the Kalman gain K. The value of K determines how much of the
innovation (the difference between the actual measurement and the model measurement) is used
to correct the estimate. K varies in proportion to the error covariance matrix P and is inversely
proportional to the measurement covariance matrix R. If the measurement noise covariance R is
large compared to the error covariance matrix P then the Kalman gain K will be small. This
means the certainty of the measurement is small relative to the certainty of the current state model
and the old model is better compared to the new measurement so that minimal adjustment to the
estimate is required. Alternatively, if P is large compared to R, K will be large and the estimate of
X is updated to look more like the measurement than the previous estimate. The innovation is
weighted more heavily.
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32
4.3 Important Routines in the Kalman Filter Implementation
In order to implement the Kalman Filter, the following steps need to be performed:
a) Model the System: A model of the system needs to be found. A knowledge of state space
representations is useful here. Modeling the system essentially means working out the
matrices Ô, B and H. Ô is the relationship between x in one time step, and x in the next,
given no inputs. B is the relationship between the inputs and the state. H is the
relationship between the measurement and the state (slightly more complicated for the
Extended Kalman Filter).
b) Noise Parameters: In theory R and Q can be calculated directly from the real world where
Q relates to model errors and input data errors, and R relates to measurement errors. In
practice these can't always be obtained accurately (or the effort involved is too great), or
the correct values don't give the required result. Tuning R too small will place too much
emphasis on the measurements making the filter varying. Tuning Q too large gives the
same result. Tuning R too large and Q too small will have the effect of making the filter
too slow, and it won't keep up with the actual changes in x. These values can be adjusted
until the filter gives the desired performance.
c) Initial Estimates: The state vector x and the error covariance matrix P need initial
estimates. Any 'guess' for x will mean that the estimate will eventually converge on the
right value, as long as P is non-zero. Given this, the best initial estimate is the 'middle' of
where x is likely to be. P needs to be chosen significantly large so that the filter is not too
slow and small enough that P doesn't remain large for too long.
d) Implement the Filter: Use the values obtained from the above steps and substitute them
into the Kalman Filter equations.
Figure 4: The Kalman Filter as a recursive linear filter.
At each cycle, the state estimate is updated by combining new measurements with the predicted
state estimate from previous measurements. Figure(5) shows the Kalman filter algorithm and its
four steps for computations are Gain computation, State estimate update, Covariance update, and
Prediction[6].
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Figure 5: The Kalman filter algorithm updation and prediction.
4.4 Reconfiguration of Lightpath Using Erlang's Formula:
Probability of configuration due to failure, F, for a lightpath on a resource is equal to the
probability of a failure on that resource during the lifetime of the lightpath. F can be found as:
From the above equation(29). Where
inter arrival time, respectively. The Probability of the repacking can be calculated as
Where ߩ ൌ ߣ/ߤ and E(n,ρ) is the Erlang’s Loss formala defined as follows
ܧ
As a result, we find the path reconfiguration probabilities in terms of (router and link
eqution(14) failure and link repacking probabilities
ܥ ൌ 1 െ ෑ
ሺ,ሻ∈ఘ
5. SIMULATION RESULTS
we studied offline state space technique using the two well known approaches, namely, M/M/1
queuing and Kalman Filter state space model
reveals that the proposed state space algorithm is suitable for large networks.
Signal & Image Processing : An International Journal (SIPIJ) Vol.7, No.2, April 2016
The Kalman filter algorithm updation and prediction.
Reconfiguration of Lightpath Using Erlang's Formula:
Probability of configuration due to failure, F, for a lightpath on a resource is equal to the
probability of a failure on that resource during the lifetime of the lightpath. F can be found as:
ܨ ൌ
ା
........................................................
Where mh and mf are the Mean holding time and mean failure
The Probability of the repacking can be calculated as
ܴ ൌ
ாሺ,ఘሻ
∗ாሺ,ఘሻ
....................................................
) is the Erlang’s Loss formala defined as follows:
ܧሺ݊, ߩሻ ൌ
ఘ
!ൗ
∑ ఘ
!ൗ
సబ
....................................................
result, we find the path reconfiguration probabilities in terms of (router and link
repacking probabilities are as follows :
ෑ ሺ1 െ ܨ
ఘ
ሻ ൫1 െ ܴ൯൫1 െ ܨ ൯ … … … … … … … …
ESULTS
we studied offline state space technique using the two well known approaches, namely, M/M/1
queuing and Kalman Filter state space model from the assumed topology. Our investigation
te space algorithm is suitable for large networks.
Figure 6: Assumed Topology
Signal & Image Processing : An International Journal (SIPIJ) Vol.7, No.2, April 2016
33
Probability of configuration due to failure, F, for a lightpath on a resource is equal to the
probability of a failure on that resource during the lifetime of the lightpath. F can be found as:
..................................................(29)
are the Mean holding time and mean failure
The Probability of the repacking can be calculated as follows:
.........................................(30)
............................................(31)
result, we find the path reconfiguration probabilities in terms of (router and link from
… . . . … . . ሺ32ሻ
we studied offline state space technique using the two well known approaches, namely, M/M/1
assumed topology. Our investigation
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34
The assumed topology consiste of 13 Links and 6 rounters from A to H shown in the Figure (6).
All the links are unidirection light paths and are established between the source ‘A’ to ‘H’ for
each request. A Light path request arrive at the time for each request as a poisson process and
lightpat holding times are considered to be exponential process. In simulation, each link in the
assumed network is composed of 3 fibers with channels on each fiber link and routers have no
converter. The MRPR algorithm used in the networks tries to route the lightpath on the route of
all the possible routes. The blocking probability performance of MRPR are kept out of the scope.
The abilities of Kalman filter based approach over the Markov model for estimation of mean
holding time, average waiting time, inter-arrival time and their corrected time, are presented using
computer simulation.
The Table(1) shows the recorded values for service begin, server idle time, service end, mean
holding time and inter arrival time for M/M/1 queue size of 10. The number of customers'
participating has been assumed to be 50.
Table 1: Shows Inter arrival time for the M/M/1 Markov model.
Clock Inter
Arraiaval
Time in µ
sec
Next
Arriaval
time in µ
sec
Service
begin in µ
sec
Service
time in µ
sec
Service
end in µ
sec
Service
idle time
in µ sec
Customer
waiting
time in µ
sec
0.06 0.02 0.09 0.06 2.04 2.10 0.06 0.00
0.09 0.20 0.29 0.06 0.06 2.10 0.06 0.00
0.29 2.64 2.93 0.06 2.04 2.10 0.06 0.20
2.10 2.64 2.93 2.10 1.22 3.33 0.00 3.63
2.93 4.62 7.55 2.10 1.22 3.33 0.00 2.64
3.33 4.62 5.55 3.33 1.09 4.42 0.00 0.80
From the Table(1) it is seen that, the total elapsed time is nothing but a interval between a service
begin and service end for total request, i.e the total amount of Elapsed Time is equal to 9.67
µsec. The Average waiting time is equal to 1.216 µsec per arrival request. The Average Server
idle time/request is equal to 0.18 µsec.
Table 2: Shows Inter arrival time for the Kalman filter model.
No. Of
iteration
Actual time in µ
sec
Measured time in µ
sec
Corrected time in µ
sec
Estimated time in
µ sec
1 2.0 2.22 2.1935 2.2451
2 2.22 2.4135 2.3846 2.4379
3 2.413 2.6404 2.5734 2.6284
4 2.6404 2.7934 2.7600 2.8167
5 2.7934 2.9800 2.9444 3.0027
The effectiveness of using Kalman filter at each node to estimate the mean holding time, inter-
arrival time and their corrected time, are shown in Table 2. As a result, it can be seen from the
Tables(1) and (2), in the case M/M/1 from Table(1) for clock recorded of beginning time 2.10
µsec, It is seen that service begins at 2.10 µsec and Service ends at 3.33 µsec, and the customer
waiting time is 3.63 µsec. However in the case of Kalman filter from the Table (2) the actual
time is 2.6404 µsec. The measured time is 2.7934 µsec, and corrected time is 2.7600 µsec, which
is for forth iteration. Hence waiting time is calucated as measured time minus actual time
0.15774 µsec, per arrival request. For all optical networks, comparing, the delay experienced in
state space technique using kalman filter approach is optimally better compared with markovian
model.
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35
Figure 7: Kalman Filter analysis
The Transition time Vs. Arrival Time results has been plotted, in Figure(7), The red colour line
shows the Actual value of the arrival time, the blue colour line indicates the measured value of
Arrival time and green colour line shows the estimated values of Arrival time at different
intervals of time when the measured noise is 0.02 and process noise is 0.01 using kalman filter
technique. Since measured noise and process noise is small, the Kalman filter technique is able to
retrieve the state of node.
Estimated arrival time ,when measurement noise=0.1 and process noise=0.1 has been considered
to plot the graph of transition time Vs Arrival time.
Figure 8: Performance in Estimating Arrival Time
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36
As a second example, Figure(8) shows the performance in estimating the arrival time with a
measurement noise is equal to 1 and process noise is equal to 0.1. It is seen that the red colour
line shows the Actual value of the arrival time, the blue colour line indicates the measured value
of Arrival time and green colour line shows the estimated values of Arrival time at different
intervals of time. Henece it is able to retrieve the state of node, from this case study, it is possible
to retrieve the state and redirect the routing direction at the node level by using filter approach
this leads optimal performace. For simuations, we used GNU OCTAVE TOOL and Ubutu
Operating system 14.01.
6. CONCLUSION
Since the statistics are used in conjunction with the present state information, it is naturally
expected that the Kalaman filter algorithm achieves better routing performance compared to
earlier adaptive RWA algorithms especially M/M/1 under non-uniform traffic conditions, namely
M/M/1. We suggest that further research in this direction is likely to find the over-head time taken
to estimate arrival time and customer waitng time in each case and their comparisons with
markov model may yield better result.
The effectiveness of the kalman filter approach for RWA problem compared to LLR and Max –
sum routing approach will be communicated.
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AUTHORS
Mohan Kumar S. received his Bachelor of Engineering in Computer Science &
Engineering and Master of .Technology, in Networking and Internet Engineering,
from Visvesvaraya Technological University, Belgaum, and Karnataka, India
respectively. He is currently working towards a Doctoral Degree from Visvesvaraya
Technological University, Belgaum, and Karnataka, India. At present he is working
as Assistant Professor, Department of Information Science and Engineering
M.S.Ramaiah Institute of Technology Bangalore. Karnataka. India (Affiliated to
Visvesvaraya Technological University Belgaum),
Dr. Jagadeesha S N received his Bachelor of Engineering., in Electronics and
Communication Engineering, from University B. D. T College of Engineering.,
Davangere affiliated to Mysore University, Karnataka, India in 1979, M.E. from
Indian Institute of Science (IISC), Bangalore, India specializing in Electrical
Communication Engineering., in 1987 and Ph.D. in Electronics and Computer
Engineering., from University of Roorkee, Roorkee, India in 1996. He is an IEEE
member. His research interest includes Array Signal Processing, Wireless Sensor
Networks and Mobile Communications. He has published and presented many papers
on Adaptive Array Signal Processing and Direction-of-Arrival estimation. Currently he is professor in the
Department of Computer Science and Engineering, Jawaharlal Nehru National College of Engineering.
(Affiliated to Visvesvaraya Technological University), Shimoga, Karnataka, India