Optical network is an emerging technology for data communication
inworldwide. The information is transmitted from the source to destination
through the fiber optics. All optical network (AON) provides good
transmission transparency, good expandability, large bandwidth, lower bit
error rate (BER), and high processing speed. Link failure and node failure
haveconsistently occurred in the traditional methods. In order to overcome
the above mentioned issues, this paper proposes a robust software defined
switching enabled fault localization framework (SDSFLF) to monitor the
node and link failure in an AON. In this work, a novel faulty node
localization (FNL) algorithm is exploited to locate the faulty node. Then, the
software defined faulty link detection (SDFLD) algorithm that addresses the
problem of link failure. The failures are localized in multi traffic stream
(MTS) and multi agent system (MAS). Thus, the throughput is improved in
SDSFLF compared than other existing methods like traditional routing and
wavelength assignment (RWA), simulated annealing (SA) algorithm, attackaware RWA (A-RWA) convex, longest path first (LPF) ordering, and
biggest source-destination node degree (BND) ordering. The performance of
the proposed algorithm is evaluated in terms of network load, wavelength
utilization, packet loss rate, and burst loss rate. Hence, proposed SDSFLF
assures that high performance is achieved than other traditional techniques.
Cross Layering using Reinforcement Learning in Cognitive Radio-based Industri...IJCNCJournal
The coupling of multiple protocol layers for a Cognitive Radio-based Industrial Internet of Ad-hoc Sensor Network, enables better interaction, coordination, and joint optimization of different protocols in achieving remarkable performance improvements. In this paper, network, and medium access control (MAC) layer functionalities are cross-layered by developing the joint strategy of routing and effective spectrum sensing and Dynamic Channel Selection (DCS) using the Reinforcement Learning (RL) algorithm. In an industrial ad-hoc scenario, the network layer utilizes the sensed spectrum and selected channel by MAC layer for next-hop routing. MAC layer utilizes the lowest known transmission delay of a channel for a single hop as computed by the network layer, which improves the MAC channel selection operation. The applied RLbased technique (Q learning) enables the CR Secondary Users (SUs) to sense, learn, and make the optimal decision on their environment of operations. The proposed RLCLD schemes improve the SU network performance up to 30% as compared to conventional methods.
CROSS LAYERING USING REINFORCEMENT LEARNING IN COGNITIVE RADIO-BASED INDUSTRI...IJCNCJournal
The coupling of multiple protocol layers for a Cognitive Radio-based Industrial Internet of Ad-hoc Sensor
Network, enables better interaction, coordination, and joint optimization of different protocols in achieving
remarkable performance improvements. In this paper, network, and medium access control (MAC) layer
functionalities are cross-layered by developing the joint strategy of routing and effective spectrum sensing
and Dynamic Channel Selection (DCS) using the Reinforcement Learning (RL) algorithm. In an industrial
ad-hoc scenario, the network layer utilizes the sensed spectrum and selected channel by MAC layer for
next-hop routing. MAC layer utilizes the lowest known transmission delay of a channel for a single hop as
computed by the network layer, which improves the MAC channel selection operation. The applied RLbased technique (Q learning) enables the CR Secondary Users (SUs) to sense, learn, and make the optimal
decision on their environment of operations. The proposed RLCLD schemes improve the SU network
performance up to 30% as compared to conventional methods.
An effective transmit packet coding with trust-based relay nodes in VANETsjournalBEEI
Vehicular ad-hoc networks (VANETs) are characterized by limited network resources such as limited bandwidth and battery capacity. Hence, it is necessary that unnecessary use of network resources (such as unnecessary packet transfers) is reduced in such networks so that the available power can be conserved for efficient multicast communications. In this paper, we have presented a Transmit Packet Coding (TPC) Network Coding in VANET to ensure reliable and efficient multicasting. With network coding, the number of transmitted packets over the network can be reduced, ensuring efficient utilization of network devices and resources. Here, the trust-based graph optimization is performed using Cuckoo search algorithm to select the secure relay nodes. The experimental results showed the superiority of the presented approach compared to the existing techniques in terms of throughput, latency, hop delay, packet delivery ratio, network decoder outage probability, and block error rate.
Reliable and Efficient Data Acquisition in Wireless Sensor NetworkIJMTST Journal
The sensors in the WSN sense the surrounding, collects the data and transfers the data to the sink node. It
has been observed that the sensor nodes are deactivated or damaged when exposed to certain radiations or
due to energy problems. This damage leads to the temporary isolation of the nodes from the network which
results in the formation of the holes. These holes are dynamic in nature and can grow and shrink depending
upon the factors causing the damage to the sensor nodes. So a solution has been presented in the base paper
where the dual mode i.e. Radio frequency and the Acoustic mode are considered so that the data can be
transferred easily. Based on this a survey has been done where several factors are studied so that the
performance of the system can be increased.
Optical Networks Automation Overview: A SurveySergio Cruzes
The increasing demand for data has driven the advancement of optical networks from traditional architectures to
more flexible, dynamic and efficient solutions. This includes technologies like flexgrid reconfigurable optical add-drop
multiplexers (ROADMs), variable bandwidth transponders (VBTs) providing different modulation, coding schemes
and baud rates. These advancements have brought about new challenges that concerns to the routing and spectrum
allocation (RSA), fragmented spectrum, need for rapid and efficient channel restoration, and operation and maintenance
management of optical networks. To address these challenges, a dynamic and flexible network requires a highly advanced
network operational system (OS) capable of efficiently managing and allocating network resources. It relies on network
abstraction, sensors, actuators, and software-defined networking (SDN) to enable algorithms, management, control, and
decision-making. Improving the sensing capabilities of the network is crucial. Modern hardware and sensor technology
can help forecast fiber breaks, equipment failures, and other potential issues in advance, allowing for proactive actions
to be taken. Machine learning (ML) methods have been proposed in the literature to enhance the accuracy of quality
of transmission (QoT) estimation, mitigate nonlinearities and provide decisions. This reduces the need for conservative
design margins, maximizes the capacity of optical network systems and reduces the investment in infrastructure. Failure
management is a critical aspect of optical networks. Providing early-warning and proactive protection is essential. This
includes detecting failures, localizing them, identifying the root causes, and estimating their magnitude. Quick response
to failures is vital to maintaining network reliability.
Congestion in Wireless Sensor Networks has negative impact on the Quality of Service.
Congestion effects the performance metrics, namely throughput and per-packet energy
consumption, network lifetime and packet delivery ratio. Reducing congestion allows better
utilization of the network resources and thus enhances the Quality of Service metrics of the
network. Traffic Aware Dynamic Routing to Alleviate Congestion in Wireless Sensor Networks
reduces congestion by considering one hop neighbor routing in the network. This paper
proposed an algorithm for Quality of Service Based Traffic-Aware Data forwarding for
congestion control in wireless sensor networks based on two hop neighbor information. On
detection of congestion, the algorithm forwards data packets around the congestion areas by
spreading the excessive packets through multiple paths. The path with light load or under
loaded nodes is efficiently utilized whenever congestion occurs. The main aspect of the
algorithm is to build path to the destination using two independent potential fields depth and
queue length. Queue length field solves the traffic-aware problem. Depth field creates a
backbone to forward packets to the sink. Both fields are combined to yield a hybrid potential
field to make dynamic decision for data forwarding. Network Simulator used for simulating the
algorithm is NS2. The proposed algorithm performs better.
TTACCA: TWO-HOP BASED TRAFFIC AWARE CONGESTION CONTROL ALGORITHM FOR WIRELESS...cscpconf
Congestion in Wireless Sensor Networks has negative impact on the Quality of Service.
Congestion effects the performance metrics, namely throughput and per-packet energy
consumption, network lifetime and packet delivery ratio. Reducing congestion allows better
utilization of the network resources and thus enhances the Quality of Service metrics of the
network. Traffic Aware Dynamic Routing to Alleviate Congestion in Wireless Sensor Networks
reduces congestion by considering one hop neighbor routing in the network. This paper
proposed an algorithm for Quality of Service Based Traffic-Aware Data forwarding for
congestion control in wireless sensor networks based on two hop neighbor information. On
detection of congestion, the algorithm forwards data packets around the congestion areas by
spreading the excessive packets through multiple paths. The path with light load or under
loaded nodes is efficiently utilized whenever congestion occurs. The main aspect of the
algorithm is to build path to the destination using two independent potential fields depth and
queue length. Queue length field solves the traffic-aware problem. Depth field creates a
backbone to forward packets to the sink. Both fields are combined to yield a hybrid potential
field to make dynamic decision for data forwarding. Network Simulator used for simulating the
algorithm is NS2. The proposed algorithm performs better.
Cross Layering using Reinforcement Learning in Cognitive Radio-based Industri...IJCNCJournal
The coupling of multiple protocol layers for a Cognitive Radio-based Industrial Internet of Ad-hoc Sensor Network, enables better interaction, coordination, and joint optimization of different protocols in achieving remarkable performance improvements. In this paper, network, and medium access control (MAC) layer functionalities are cross-layered by developing the joint strategy of routing and effective spectrum sensing and Dynamic Channel Selection (DCS) using the Reinforcement Learning (RL) algorithm. In an industrial ad-hoc scenario, the network layer utilizes the sensed spectrum and selected channel by MAC layer for next-hop routing. MAC layer utilizes the lowest known transmission delay of a channel for a single hop as computed by the network layer, which improves the MAC channel selection operation. The applied RLbased technique (Q learning) enables the CR Secondary Users (SUs) to sense, learn, and make the optimal decision on their environment of operations. The proposed RLCLD schemes improve the SU network performance up to 30% as compared to conventional methods.
CROSS LAYERING USING REINFORCEMENT LEARNING IN COGNITIVE RADIO-BASED INDUSTRI...IJCNCJournal
The coupling of multiple protocol layers for a Cognitive Radio-based Industrial Internet of Ad-hoc Sensor
Network, enables better interaction, coordination, and joint optimization of different protocols in achieving
remarkable performance improvements. In this paper, network, and medium access control (MAC) layer
functionalities are cross-layered by developing the joint strategy of routing and effective spectrum sensing
and Dynamic Channel Selection (DCS) using the Reinforcement Learning (RL) algorithm. In an industrial
ad-hoc scenario, the network layer utilizes the sensed spectrum and selected channel by MAC layer for
next-hop routing. MAC layer utilizes the lowest known transmission delay of a channel for a single hop as
computed by the network layer, which improves the MAC channel selection operation. The applied RLbased technique (Q learning) enables the CR Secondary Users (SUs) to sense, learn, and make the optimal
decision on their environment of operations. The proposed RLCLD schemes improve the SU network
performance up to 30% as compared to conventional methods.
An effective transmit packet coding with trust-based relay nodes in VANETsjournalBEEI
Vehicular ad-hoc networks (VANETs) are characterized by limited network resources such as limited bandwidth and battery capacity. Hence, it is necessary that unnecessary use of network resources (such as unnecessary packet transfers) is reduced in such networks so that the available power can be conserved for efficient multicast communications. In this paper, we have presented a Transmit Packet Coding (TPC) Network Coding in VANET to ensure reliable and efficient multicasting. With network coding, the number of transmitted packets over the network can be reduced, ensuring efficient utilization of network devices and resources. Here, the trust-based graph optimization is performed using Cuckoo search algorithm to select the secure relay nodes. The experimental results showed the superiority of the presented approach compared to the existing techniques in terms of throughput, latency, hop delay, packet delivery ratio, network decoder outage probability, and block error rate.
Reliable and Efficient Data Acquisition in Wireless Sensor NetworkIJMTST Journal
The sensors in the WSN sense the surrounding, collects the data and transfers the data to the sink node. It
has been observed that the sensor nodes are deactivated or damaged when exposed to certain radiations or
due to energy problems. This damage leads to the temporary isolation of the nodes from the network which
results in the formation of the holes. These holes are dynamic in nature and can grow and shrink depending
upon the factors causing the damage to the sensor nodes. So a solution has been presented in the base paper
where the dual mode i.e. Radio frequency and the Acoustic mode are considered so that the data can be
transferred easily. Based on this a survey has been done where several factors are studied so that the
performance of the system can be increased.
Optical Networks Automation Overview: A SurveySergio Cruzes
The increasing demand for data has driven the advancement of optical networks from traditional architectures to
more flexible, dynamic and efficient solutions. This includes technologies like flexgrid reconfigurable optical add-drop
multiplexers (ROADMs), variable bandwidth transponders (VBTs) providing different modulation, coding schemes
and baud rates. These advancements have brought about new challenges that concerns to the routing and spectrum
allocation (RSA), fragmented spectrum, need for rapid and efficient channel restoration, and operation and maintenance
management of optical networks. To address these challenges, a dynamic and flexible network requires a highly advanced
network operational system (OS) capable of efficiently managing and allocating network resources. It relies on network
abstraction, sensors, actuators, and software-defined networking (SDN) to enable algorithms, management, control, and
decision-making. Improving the sensing capabilities of the network is crucial. Modern hardware and sensor technology
can help forecast fiber breaks, equipment failures, and other potential issues in advance, allowing for proactive actions
to be taken. Machine learning (ML) methods have been proposed in the literature to enhance the accuracy of quality
of transmission (QoT) estimation, mitigate nonlinearities and provide decisions. This reduces the need for conservative
design margins, maximizes the capacity of optical network systems and reduces the investment in infrastructure. Failure
management is a critical aspect of optical networks. Providing early-warning and proactive protection is essential. This
includes detecting failures, localizing them, identifying the root causes, and estimating their magnitude. Quick response
to failures is vital to maintaining network reliability.
Congestion in Wireless Sensor Networks has negative impact on the Quality of Service.
Congestion effects the performance metrics, namely throughput and per-packet energy
consumption, network lifetime and packet delivery ratio. Reducing congestion allows better
utilization of the network resources and thus enhances the Quality of Service metrics of the
network. Traffic Aware Dynamic Routing to Alleviate Congestion in Wireless Sensor Networks
reduces congestion by considering one hop neighbor routing in the network. This paper
proposed an algorithm for Quality of Service Based Traffic-Aware Data forwarding for
congestion control in wireless sensor networks based on two hop neighbor information. On
detection of congestion, the algorithm forwards data packets around the congestion areas by
spreading the excessive packets through multiple paths. The path with light load or under
loaded nodes is efficiently utilized whenever congestion occurs. The main aspect of the
algorithm is to build path to the destination using two independent potential fields depth and
queue length. Queue length field solves the traffic-aware problem. Depth field creates a
backbone to forward packets to the sink. Both fields are combined to yield a hybrid potential
field to make dynamic decision for data forwarding. Network Simulator used for simulating the
algorithm is NS2. The proposed algorithm performs better.
TTACCA: TWO-HOP BASED TRAFFIC AWARE CONGESTION CONTROL ALGORITHM FOR WIRELESS...cscpconf
Congestion in Wireless Sensor Networks has negative impact on the Quality of Service.
Congestion effects the performance metrics, namely throughput and per-packet energy
consumption, network lifetime and packet delivery ratio. Reducing congestion allows better
utilization of the network resources and thus enhances the Quality of Service metrics of the
network. Traffic Aware Dynamic Routing to Alleviate Congestion in Wireless Sensor Networks
reduces congestion by considering one hop neighbor routing in the network. This paper
proposed an algorithm for Quality of Service Based Traffic-Aware Data forwarding for
congestion control in wireless sensor networks based on two hop neighbor information. On
detection of congestion, the algorithm forwards data packets around the congestion areas by
spreading the excessive packets through multiple paths. The path with light load or under
loaded nodes is efficiently utilized whenever congestion occurs. The main aspect of the
algorithm is to build path to the destination using two independent potential fields depth and
queue length. Queue length field solves the traffic-aware problem. Depth field creates a
backbone to forward packets to the sink. Both fields are combined to yield a hybrid potential
field to make dynamic decision for data forwarding. Network Simulator used for simulating the
algorithm is NS2. The proposed algorithm performs better.
Energy Proficient and Security Protocol for WSN: A Reviewtheijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
Theoretical work submitted to the Journal should be original in its motivation or modeling structure. Empirical analysis should be based on a theoretical framework and should be capable of replication. It is expected that all materials required for replication (including computer programs and data sets) should be available upon request to the authors.
The International Journal of Engineering & Science would take much care in making your article published without much delay with your kind cooperation
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
CL-SA-OFDM: cross-layer and smart antenna based OFDM system performance enha...IJECEIAES
The growing usage of wireless services is lacking in providing high-speed data communication in recent times. Hence, many of the modulation techniques are evolved to attain these communication needs. The recent researches have widely considered OFDM technology as the prominent modulation mechanism to fulfill the futuristic needs of wireless communication. The OFDM can bring effective usage of resources, bandwidth, and system performance enhancement in collaboration with the smart antenna and resource allocation mechanism (adaptive). However, the usage of adaptive beamforming with the OFDM leads to complication in the design of medium access layer and which causes a problem in adaptive resource allocation mechanism (ARAM). Hence, the proposed manuscript intends to design an OFDM system by considering different switched beam smart antenna (SBSA) along with the cross-layer adaptive resource allocation (CLARA) and hybrid adaptive array (HAA). In this, various smart antenna mechanism are considered to analyze the quality of service (QoS) and complexity reduction in the OFDM system. In this paper, various SA schemes are used as per the quality of service (QoS) requirement of the different users. The performance analysis is conducted by considering data traffic reduction, bit-rate reduction, and average delay.
Particle Swarm Optimization–Long Short-Term Memory based Channel Estimation w...IJCNCJournal
Non-Orthogonal Multiple Access (NOMA) helps to overcome various difficulties in future technology wireless communications. NOMA, when utilized with millimeter wave multiple-input multiple-output (MIMO) systems, channel estimation becomes extremely difficult. For reaping the benefits of the NOMA and mm-Wave combination, effective channel estimation is required. In this paper, we propose an enhanced particle swarm optimization based long short-term memory estimator network (PSOLSTMEstNet), which is a neural network model that can be employed to forecast the bandwidth required in the mm-Wave MIMO network. The prime advantage of the LSTM is that it has the capability of dynamically adapting to the functioning pattern of fluctuating channel state. The LSTM stage with adaptive coding and modulation enhances the BER.PSO algorithm is employed to optimize input weights of LSTM network. The modified algorithm splits the power by channel condition of every single user. Participants will be first sorted into distinct groups depending upon respective channel conditions, using a hybrid beamforming approach. The network characteristics are fine-estimated using PSO-LSTMEstNet after a rough approximation of channels parameters derived from the received data.
PARTICLE SWARM OPTIMIZATION–LONG SHORTTERM MEMORY BASED CHANNEL ESTIMATION WI...IJCNCJournal
Non-Orthogonal Multiple Access (NOMA) helps to overcome various difficulties in future technology wireless communications. NOMA, when utilized with millimeter wave multiple-input multiple-output (MIMO) systems, channel estimation becomes extremely difficult. For reaping the benefits of the NOMA and mm-Wave combination, effective channel estimation is required. In this paper, we propose an enhanced particle swarm optimization based long short-term memory estimator network (PSOLSTMEstNet), which is a neural network model that can be employed to forecast the bandwidth required in the mm-Wave MIMO network. The prime advantage of the LSTM is that it has the capability of dynamically adapting to the functioning pattern of fluctuating channel state. The LSTM stage with adaptive coding and modulation enhances the BER.PSO algorithm is employed to optimize input weights of LSTM network. The modified algorithm splits the power by channel condition of every single user. Participants will be first sorted into distinct groups depending upon respective channel conditions, using a hybrid beamforming approach. The network characteristics are fine-estimated using PSO-LSTMEstNet after a rough approximation of channels parameters derived from the received data
ENERGY EFFICIENT ROUTING IN WIRELESS SENSOR NETWORKS BASED ON QOSIAEME Publication
Energy is a serious resource parameter in Wireless Sensor Networks. Utilizing energy in an effectual manner is a challenging task in Wireless Sensor Networks. This paper presents an overview on various energy efficient routing protocols which fulfills the criteria of QoS parameters. Various energy effective and QoS based routing protocols have been compared. To improve the QoS in a network, data fusion and data accumulation is considered to be one of major energy saving technique. The routing protocols based on data aggregation, reduced cost routing and secure routing are also discussed in detail. Simulation tools like NS2, NS3, OMNET etc can be used to evaluate the network performance.
ENERGY EFFICIENT ROUTING IN WIRELESS SENSOR NETWORKS BASED ON QOSIAEME Publication
Energy is a serious resource parameter in Wireless Sensor Networks. Utilizing energy in an effectual manner is a challenging task in Wireless Sensor Networks. This paper presents an overview on various energy efficient routing protocols which fulfills the criteria of QoS parameters. Various energy effective and QoS based routing protocols have been compared. To improve the QoS in a network, data fusion and data accumulation is considered to be one of major energy saving technique. The routing protocols based on data aggregation, reduced cost routing and secure routing are also discussed in detail. Simulation tools like NS2, NS3, OMNET etc can be used to evaluate the network performance.
Advanced hybrid algorithms for precise multipath channel estimation in next-g...IJECEIAES
Multipath channels continue to present challenges in wireless communication for both 5G and 6G networks. A multipath channel is a phenomenon in wireless communications where signals traverse from the sender to the receiver along various paths. This end occurs due to the reflection, diffraction, and refraction of signals of various objects and structures in the environment. Such pathways can cause symbol interference in the transmitted signal, leading to communication issues. To this end, our paper proposes the integration of three algorithms: teaching-learning-based optimization (TLBO), particle swarm optimization (PSO), and artificial neural networks (ANN). This combination effectively analyzes and stabilizes the transmission channel, minimizing symbol interference. We have developed, simulated, and evaluated this hybrid approach for multipath fading channels. We apply it to various coding schemes, including tail-biting convolutional code, turbo codes, low-density parity-check, and polar code. Additionally, we have explored various decoding methods such as Viterbi, maximum logarithmic maximum a posteriori, minimum sum, and cyclic redundancy check soft cancellation list. Our study encompasses new channel equalization schemes and coding gains derived from simulations and mathematical analysis. Our proposed method significantly enhances channel equalization, reducing interference and improving error correction in wireless communication systems.
CONTEXT-AWARE ENERGY CONSERVING ROUTING ALGORITHM FOR INTERNET OF THINGSIJCNCJournal
Internet of Things (IoT) is the fast- growing technology, mostly used in smart mobile devices such as notebooks, tablets, personal digital assistants (PDA), smartphones, etc. Due to its dynamic nature and the limited battery power of the IoT enabled smart mobile nodes, the communication links between intermediate relay nodes may fail frequently, thus affecting the routing performance of the network and also the availability of the nodes. Existing algorithm does not concentrate about communication links and battery power/energy, but these node links are a very important factor for improving the quality of routing in IoT. In this paper, Context-aware Energy Conserving Algorithm for routing (CECA) was proposed which employs QoS routing metrics like Inter-Meeting Time and residual energy and has been applied to IoT enabled smart mobile devices using different technologies with different microcontroller which resulted in an increased network lifetime, throughput and reduced control overhead and the end to end delay. Simulation results show that, with respect to the speed of the mobile nodes from 2 to 10m/s, CECA increases the network lifetime, thereby increasing the average residual energy by 11.1% and increasing throughput there by reduces the average end to end delay by 14.1% over the Energy-Efficient Probabilistic Routing (EEPR) algorithm. With respect to the number of nodes increases from 10 to 100 nodes, CECA algorithms increase the average residual energy by16.1 % reduces the average end to end delay by 15.9% and control overhead by 23.7% over the existing EEPR
Analysing Mobile Random Early Detection for Congestion Control in Mobile Ad-h...IJECEIAES
This research paper suggests and analyse a technique for congestion control in mobile ad hoc networks. The technique is based on a new hybrid approach that uses clustering and queuing techniques. In clustering, in general cluster head transfers the data, following a queuing method based on a RED (Random Early Detection), the mobile environment makes it Mobile RED (or MRED), It majorly depends upon mobility of nodes and mobile environments leads to unpredictable queue size. To simulate this technique, the Network Simulator 2 (or NS2) is used for various scenarios. The simulated results are compared with NRED (Neighbourhood Random Early Detection) queuing technique of congestion control. It has been observed that the results are improved using MRED comparatively.
Performance and statistical analysis of ant colony route in mobile ad-hoc ne...IJECEIAES
Research on mobile ad-hoc networks (MANETs) is increasing in popularity due to its rapid, budget-friendly, and easily altered implementation, and relevance to emergencies such as forest firefighting and health care provisioning. The main concerns that ad-hoc networks face is dynamic topology, energy usage, packet drop rate, and throughput. Routing protocol selection is a critical point to surmount alterations in topology and maintain quality in MANET networks. The effectiveness of any network can be vastly enhanced with a well-designed routing protocol. In recent decades, standard MANET protocols have not been able to keep pace with growing demands for MANET applications. The current study investigates and contrasts ant colony optimization (ACO) with various routing protocols. This paper compares ad-hoc on-demand multi-path distance vector (AOMDV), dynamic source routing protocol (DSR), ad-hoc on-demand distance vector routing (AODV), and AntHocNet protocols regarding the quality of service (QoS) and statistical analysis. The current research aims to study the behavior of the state-of-the-art MANET protocols with the ACO technique. The ACO technique is a hybrid technique, integrating a reactive route maintaining technique with a proactive method. The reason and motivation for including the ACO algorithm in the current study is to improve by using optimization algorithms proved in other domains. The ACO algorithm appears to have substantial use in large-scale MANET simulation.
IoT Resource Allocation and Optimization Using Improved Reptile Search AlgorithmIJCNCJournal
The Internet of Things (IoT) is a dispersed network system that connects the world through the Internet. The architecture of IoT consists of more gateways and resources which cannot be allocated in a manual process. The allocation of resources in IoT is a challenging process due to the higher consumption of energy and high latency rate. To overcome the challenges in existing works, this research introduced an Improved Reptile Search Algorithm (IRSA) to solve the optimization problem which occurs during the time of allocation resources among IoT networks. IRSA employs the methodology of levy flight and cross-over to update the candidate position and enhance the search speed in a single iteration. The proposed method consumes less energy and has low latency during data transmission from User equipment (UE) to the base station.IRSA has been compared with the existing Scalable Resource Allocation Framework (SRAF) and Improved Chaotic Firefly Algorithm (ICFA). The obtained experimental results show that the proposed IRSA attained better performance with an allocation rate of 96.40% which is comparatively higher than SRAF and ICFA with 92.40% and 91.67% respectively.
Because of the rapid growth in technology breakthroughs, including
multimedia and cell phones, Telugu character recognition (TCR) has recently
become a popular study area. It is still necessary to construct automated and
intelligent online TCR models, even if many studies have focused on offline
TCR models. The Telugu character dataset construction and validation using
an Inception and ResNet-based model are presented. The collection of 645
letters in the dataset includes 18 Achus, 38 Hallus, 35 Othulu, 34×16
Guninthamulu, and 10 Ankelu. The proposed technique aims to efficiently
recognize and identify distinctive Telugu characters online. This model's main
pre-processing steps to achieve its goals include normalization, smoothing,
and interpolation. Improved recognition performance can be attained by using
stochastic gradient descent (SGD) to optimize the model's hyperparameters.
Scientific workload execution on a distributed computing platform such as a
cloud environment is time-consuming and expensive. The scientific workload
has task dependencies with different service level agreement (SLA)
prerequisites at different levels. Existing workload scheduling (WS) designs
are not efficient in assuring SLA at the task level. Alongside, induces higher
costs as the majority of scheduling mechanisms reduce either time or energy.
In reducing, cost both energy and makespan must be optimized together for
allocating resources. No prior work has considered optimizing energy and
processing time together in meeting task level SLA requirements. This paper
presents task level energy and performance assurance-workload scheduling
(TLEPA-WS) algorithm for the distributed computing environment. The
TLEPA-WS guarantees energy minimization with the performance
requirement of the parallel application under a distributed computational
environment. Experiment results show a significant reduction in using energy
and makespan; thereby reducing the cost of workload execution in comparison
with various standard workload execution models.
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Energy Proficient and Security Protocol for WSN: A Reviewtheijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
Theoretical work submitted to the Journal should be original in its motivation or modeling structure. Empirical analysis should be based on a theoretical framework and should be capable of replication. It is expected that all materials required for replication (including computer programs and data sets) should be available upon request to the authors.
The International Journal of Engineering & Science would take much care in making your article published without much delay with your kind cooperation
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
CL-SA-OFDM: cross-layer and smart antenna based OFDM system performance enha...IJECEIAES
The growing usage of wireless services is lacking in providing high-speed data communication in recent times. Hence, many of the modulation techniques are evolved to attain these communication needs. The recent researches have widely considered OFDM technology as the prominent modulation mechanism to fulfill the futuristic needs of wireless communication. The OFDM can bring effective usage of resources, bandwidth, and system performance enhancement in collaboration with the smart antenna and resource allocation mechanism (adaptive). However, the usage of adaptive beamforming with the OFDM leads to complication in the design of medium access layer and which causes a problem in adaptive resource allocation mechanism (ARAM). Hence, the proposed manuscript intends to design an OFDM system by considering different switched beam smart antenna (SBSA) along with the cross-layer adaptive resource allocation (CLARA) and hybrid adaptive array (HAA). In this, various smart antenna mechanism are considered to analyze the quality of service (QoS) and complexity reduction in the OFDM system. In this paper, various SA schemes are used as per the quality of service (QoS) requirement of the different users. The performance analysis is conducted by considering data traffic reduction, bit-rate reduction, and average delay.
Particle Swarm Optimization–Long Short-Term Memory based Channel Estimation w...IJCNCJournal
Non-Orthogonal Multiple Access (NOMA) helps to overcome various difficulties in future technology wireless communications. NOMA, when utilized with millimeter wave multiple-input multiple-output (MIMO) systems, channel estimation becomes extremely difficult. For reaping the benefits of the NOMA and mm-Wave combination, effective channel estimation is required. In this paper, we propose an enhanced particle swarm optimization based long short-term memory estimator network (PSOLSTMEstNet), which is a neural network model that can be employed to forecast the bandwidth required in the mm-Wave MIMO network. The prime advantage of the LSTM is that it has the capability of dynamically adapting to the functioning pattern of fluctuating channel state. The LSTM stage with adaptive coding and modulation enhances the BER.PSO algorithm is employed to optimize input weights of LSTM network. The modified algorithm splits the power by channel condition of every single user. Participants will be first sorted into distinct groups depending upon respective channel conditions, using a hybrid beamforming approach. The network characteristics are fine-estimated using PSO-LSTMEstNet after a rough approximation of channels parameters derived from the received data.
PARTICLE SWARM OPTIMIZATION–LONG SHORTTERM MEMORY BASED CHANNEL ESTIMATION WI...IJCNCJournal
Non-Orthogonal Multiple Access (NOMA) helps to overcome various difficulties in future technology wireless communications. NOMA, when utilized with millimeter wave multiple-input multiple-output (MIMO) systems, channel estimation becomes extremely difficult. For reaping the benefits of the NOMA and mm-Wave combination, effective channel estimation is required. In this paper, we propose an enhanced particle swarm optimization based long short-term memory estimator network (PSOLSTMEstNet), which is a neural network model that can be employed to forecast the bandwidth required in the mm-Wave MIMO network. The prime advantage of the LSTM is that it has the capability of dynamically adapting to the functioning pattern of fluctuating channel state. The LSTM stage with adaptive coding and modulation enhances the BER.PSO algorithm is employed to optimize input weights of LSTM network. The modified algorithm splits the power by channel condition of every single user. Participants will be first sorted into distinct groups depending upon respective channel conditions, using a hybrid beamforming approach. The network characteristics are fine-estimated using PSO-LSTMEstNet after a rough approximation of channels parameters derived from the received data
ENERGY EFFICIENT ROUTING IN WIRELESS SENSOR NETWORKS BASED ON QOSIAEME Publication
Energy is a serious resource parameter in Wireless Sensor Networks. Utilizing energy in an effectual manner is a challenging task in Wireless Sensor Networks. This paper presents an overview on various energy efficient routing protocols which fulfills the criteria of QoS parameters. Various energy effective and QoS based routing protocols have been compared. To improve the QoS in a network, data fusion and data accumulation is considered to be one of major energy saving technique. The routing protocols based on data aggregation, reduced cost routing and secure routing are also discussed in detail. Simulation tools like NS2, NS3, OMNET etc can be used to evaluate the network performance.
ENERGY EFFICIENT ROUTING IN WIRELESS SENSOR NETWORKS BASED ON QOSIAEME Publication
Energy is a serious resource parameter in Wireless Sensor Networks. Utilizing energy in an effectual manner is a challenging task in Wireless Sensor Networks. This paper presents an overview on various energy efficient routing protocols which fulfills the criteria of QoS parameters. Various energy effective and QoS based routing protocols have been compared. To improve the QoS in a network, data fusion and data accumulation is considered to be one of major energy saving technique. The routing protocols based on data aggregation, reduced cost routing and secure routing are also discussed in detail. Simulation tools like NS2, NS3, OMNET etc can be used to evaluate the network performance.
Advanced hybrid algorithms for precise multipath channel estimation in next-g...IJECEIAES
Multipath channels continue to present challenges in wireless communication for both 5G and 6G networks. A multipath channel is a phenomenon in wireless communications where signals traverse from the sender to the receiver along various paths. This end occurs due to the reflection, diffraction, and refraction of signals of various objects and structures in the environment. Such pathways can cause symbol interference in the transmitted signal, leading to communication issues. To this end, our paper proposes the integration of three algorithms: teaching-learning-based optimization (TLBO), particle swarm optimization (PSO), and artificial neural networks (ANN). This combination effectively analyzes and stabilizes the transmission channel, minimizing symbol interference. We have developed, simulated, and evaluated this hybrid approach for multipath fading channels. We apply it to various coding schemes, including tail-biting convolutional code, turbo codes, low-density parity-check, and polar code. Additionally, we have explored various decoding methods such as Viterbi, maximum logarithmic maximum a posteriori, minimum sum, and cyclic redundancy check soft cancellation list. Our study encompasses new channel equalization schemes and coding gains derived from simulations and mathematical analysis. Our proposed method significantly enhances channel equalization, reducing interference and improving error correction in wireless communication systems.
CONTEXT-AWARE ENERGY CONSERVING ROUTING ALGORITHM FOR INTERNET OF THINGSIJCNCJournal
Internet of Things (IoT) is the fast- growing technology, mostly used in smart mobile devices such as notebooks, tablets, personal digital assistants (PDA), smartphones, etc. Due to its dynamic nature and the limited battery power of the IoT enabled smart mobile nodes, the communication links between intermediate relay nodes may fail frequently, thus affecting the routing performance of the network and also the availability of the nodes. Existing algorithm does not concentrate about communication links and battery power/energy, but these node links are a very important factor for improving the quality of routing in IoT. In this paper, Context-aware Energy Conserving Algorithm for routing (CECA) was proposed which employs QoS routing metrics like Inter-Meeting Time and residual energy and has been applied to IoT enabled smart mobile devices using different technologies with different microcontroller which resulted in an increased network lifetime, throughput and reduced control overhead and the end to end delay. Simulation results show that, with respect to the speed of the mobile nodes from 2 to 10m/s, CECA increases the network lifetime, thereby increasing the average residual energy by 11.1% and increasing throughput there by reduces the average end to end delay by 14.1% over the Energy-Efficient Probabilistic Routing (EEPR) algorithm. With respect to the number of nodes increases from 10 to 100 nodes, CECA algorithms increase the average residual energy by16.1 % reduces the average end to end delay by 15.9% and control overhead by 23.7% over the existing EEPR
Analysing Mobile Random Early Detection for Congestion Control in Mobile Ad-h...IJECEIAES
This research paper suggests and analyse a technique for congestion control in mobile ad hoc networks. The technique is based on a new hybrid approach that uses clustering and queuing techniques. In clustering, in general cluster head transfers the data, following a queuing method based on a RED (Random Early Detection), the mobile environment makes it Mobile RED (or MRED), It majorly depends upon mobility of nodes and mobile environments leads to unpredictable queue size. To simulate this technique, the Network Simulator 2 (or NS2) is used for various scenarios. The simulated results are compared with NRED (Neighbourhood Random Early Detection) queuing technique of congestion control. It has been observed that the results are improved using MRED comparatively.
Performance and statistical analysis of ant colony route in mobile ad-hoc ne...IJECEIAES
Research on mobile ad-hoc networks (MANETs) is increasing in popularity due to its rapid, budget-friendly, and easily altered implementation, and relevance to emergencies such as forest firefighting and health care provisioning. The main concerns that ad-hoc networks face is dynamic topology, energy usage, packet drop rate, and throughput. Routing protocol selection is a critical point to surmount alterations in topology and maintain quality in MANET networks. The effectiveness of any network can be vastly enhanced with a well-designed routing protocol. In recent decades, standard MANET protocols have not been able to keep pace with growing demands for MANET applications. The current study investigates and contrasts ant colony optimization (ACO) with various routing protocols. This paper compares ad-hoc on-demand multi-path distance vector (AOMDV), dynamic source routing protocol (DSR), ad-hoc on-demand distance vector routing (AODV), and AntHocNet protocols regarding the quality of service (QoS) and statistical analysis. The current research aims to study the behavior of the state-of-the-art MANET protocols with the ACO technique. The ACO technique is a hybrid technique, integrating a reactive route maintaining technique with a proactive method. The reason and motivation for including the ACO algorithm in the current study is to improve by using optimization algorithms proved in other domains. The ACO algorithm appears to have substantial use in large-scale MANET simulation.
IoT Resource Allocation and Optimization Using Improved Reptile Search AlgorithmIJCNCJournal
The Internet of Things (IoT) is a dispersed network system that connects the world through the Internet. The architecture of IoT consists of more gateways and resources which cannot be allocated in a manual process. The allocation of resources in IoT is a challenging process due to the higher consumption of energy and high latency rate. To overcome the challenges in existing works, this research introduced an Improved Reptile Search Algorithm (IRSA) to solve the optimization problem which occurs during the time of allocation resources among IoT networks. IRSA employs the methodology of levy flight and cross-over to update the candidate position and enhance the search speed in a single iteration. The proposed method consumes less energy and has low latency during data transmission from User equipment (UE) to the base station.IRSA has been compared with the existing Scalable Resource Allocation Framework (SRAF) and Improved Chaotic Firefly Algorithm (ICFA). The obtained experimental results show that the proposed IRSA attained better performance with an allocation rate of 96.40% which is comparatively higher than SRAF and ICFA with 92.40% and 91.67% respectively.
Similar to SDSFLF: fault localization framework for optical communication using software digital switching network (20)
Because of the rapid growth in technology breakthroughs, including
multimedia and cell phones, Telugu character recognition (TCR) has recently
become a popular study area. It is still necessary to construct automated and
intelligent online TCR models, even if many studies have focused on offline
TCR models. The Telugu character dataset construction and validation using
an Inception and ResNet-based model are presented. The collection of 645
letters in the dataset includes 18 Achus, 38 Hallus, 35 Othulu, 34×16
Guninthamulu, and 10 Ankelu. The proposed technique aims to efficiently
recognize and identify distinctive Telugu characters online. This model's main
pre-processing steps to achieve its goals include normalization, smoothing,
and interpolation. Improved recognition performance can be attained by using
stochastic gradient descent (SGD) to optimize the model's hyperparameters.
Scientific workload execution on a distributed computing platform such as a
cloud environment is time-consuming and expensive. The scientific workload
has task dependencies with different service level agreement (SLA)
prerequisites at different levels. Existing workload scheduling (WS) designs
are not efficient in assuring SLA at the task level. Alongside, induces higher
costs as the majority of scheduling mechanisms reduce either time or energy.
In reducing, cost both energy and makespan must be optimized together for
allocating resources. No prior work has considered optimizing energy and
processing time together in meeting task level SLA requirements. This paper
presents task level energy and performance assurance-workload scheduling
(TLEPA-WS) algorithm for the distributed computing environment. The
TLEPA-WS guarantees energy minimization with the performance
requirement of the parallel application under a distributed computational
environment. Experiment results show a significant reduction in using energy
and makespan; thereby reducing the cost of workload execution in comparison
with various standard workload execution models.
Investigating human subjects is the goal of predicting human emotions in the
real world scenario. A significant number of psychological effects require
(feelings) to be produced, directly releasing human emotions. The
development of effect theory leads one to believe that one must be aware of
one's sentiments and emotions to forecast one's behavior. The proposed line
of inquiry focuses on developing a reliable model incorporating
neurophysiological data into actual feelings. Any change in emotional affect
will directly elicit a response in the body's physiological systems. This
approach is named after the notion of Gaussian mixture models (GMM). The
statistical reaction following data processing, quantitative findings on emotion
labels, and coincidental responses with training samples all directly impact the
outcomes that are accomplished. In terms of statistical parameters such as
population mean and standard deviation, the suggested method is evaluated
compared to a technique considered to be state-of-the-art. The proposed
system determines an individual's emotional state after a minimum of 6
iterative learning using the Gaussian expectation-maximization (GEM)
statistical model, in which the iterations tend to continue to zero error. Perhaps
each of these improves predictions while simultaneously increasing the
amount of value extracted.
Early diagnosis of cancers is a major requirement for patients and a
complicated job for the oncologist. If it is diagnosed early, it could have made
the patient more likely to live. For a few decades, fuzzy logic emerged as an
emphatic technique in the identification of diseases like different types of
cancers. The recognition of cancer diseases mostly operated with inexactness,
inaccuracy, and vagueness. This paper aims to design the fuzzy expert system
(FES) and its implementation for the detection of prostate cancer. Specifically,
prostate-specific antigen (PSA), prostate volume (PV), age, and percentage
free PSA (%FPSA) are used to determine prostate cancer risk (PCR), while
PCR serves as an output parameter. Mamdani fuzzy inference method is used
to calculate a range of PCR. The system provides a scale of risk of prostate
cancer and clears the path for the oncologist to determine whether their
patients need a biopsy. This system is fast as it requires minimum calculation
and hence comparatively less time which reduces mortality and morbidity and
is more reliable than other economic systems and can be frequently used by
doctors.
The biomedical profession has gained importance due to the rapid and accurate diagnosis of clinical patients using computer-aided diagnosis (CAD) tools.
The diagnosis and treatment of Alzheimer’s disease (AD) using complementary multimodalities can improve the quality of life and mental state of patients.
In this study, we integrated a lightweight custom convolutional neural network
(CNN) model and nature-inspired optimization techniques to enhance the performance, robustness, and stability of progress detection in AD. A multi-modal
fusion database approach was implemented, including positron emission tomography (PET) and magnetic resonance imaging (MRI) datasets, to create a fused
database. We compared the performance of custom and pre-trained deep learning models with and without optimization and found that employing natureinspired algorithms like the particle swarm optimization algorithm (PSO) algorithm significantly improved system performance. The proposed methodology,
which includes a fused multimodality database and optimization strategy, improved performance metrics such as training, validation, test accuracy, precision, and recall. Furthermore, PSO was found to improve the performance of
pre-trained models by 3-5% and custom models by up to 22%. Combining different medical imaging modalities improved the overall model performance by
2-5%. In conclusion, a customized lightweight CNN model and nature-inspired
optimization techniques can significantly enhance progress detection, leading to
better biomedical research and patient care.
Class imbalance is a pervasive issue in the field of disease classification from
medical images. It is necessary to balance out the class distribution while training a model. However, in the case of rare medical diseases, images from affected
patients are much harder to come by compared to images from non-affected
patients, resulting in unwanted class imbalance. Various processes of tackling
class imbalance issues have been explored so far, each having its fair share of
drawbacks. In this research, we propose an outlier detection based image classification technique which can handle even the most extreme case of class imbalance. We have utilized a dataset of malaria parasitized and uninfected cells. An
autoencoder model titled AnoMalNet is trained with only the uninfected cell images at the beginning and then used to classify both the affected and non-affected
cell images by thresholding a loss value. We have achieved an accuracy, precision, recall, and F1 score of 98.49%, 97.07%, 100%, and 98.52% respectively,
performing better than large deep learning models and other published works.
As our proposed approach can provide competitive results without needing the
disease-positive samples during training, it should prove to be useful in binary
disease classification on imbalanced datasets.
Recently, plant identification has become an active trend due to encouraging
results achieved in plant species detection and plant classification fields
among numerous available plants using deep learning methods. Therefore,
plant classification analysis is performed in this work to address the problem
of accurate plant species detection in the presence of multiple leaves together,
flowers, and noise. Thus, a convolutional neural network based deep feature
learning and classification (CNN-DFLC) model is designed to analyze
patterns of plant leaves and perform classification using generated finegrained feature weights. The proposed CNN-DFLC model precisely estimates
which the given image belongs to which plant species. Several layers and
blocks are utilized to design the proposed CNN-DFLC model. Fine-grained
feature weights are obtained using convolutional and pooling layers. The
obtained feature maps in training are utilized to predict labels and model
performance is tested on the Vietnam plant image (VPN-200) dataset. This
dataset consists of a total number of 20,000 images and testing results are
achieved in terms of classification accuracy, precision, recall, and other
performance metrics. The mean classification accuracy obtained using the
proposed CNN-DFLC model is 96.42% considering all 200 classes from the
VPN-200 dataset.
Big data as a service (BDaaS) platform is widely used by various
organizations for handling and processing the high volume of data generated
from different internet of things (IoT) devices. Data generated from these IoT
devices are kept in the form of big data with the help of cloud computing
technology. Researchers are putting efforts into providing a more secure and
protected access environment for the data available on the cloud. In order to
create a safe, distributed, and decentralised environment in the cloud,
blockchain technology has emerged as a useful tool. In this research paper, we
have proposed a system that uses blockchain technology as a tool to regulate
data access that is provided by BDaaS platforms. We are securing the access
policy of data by using a modified form of ciphertext policy-attribute based
encryption (CP-ABE) technique with the help of blockchain technology. For
secure data access in BDaaS, algorithms have been created using a mix of CPABE with blockchain technology. Proposed smart contract algorithms are
implemented using Eclipse 7.0 IDE and the cloud environment has been
simulated on CloudSim tool. Results of key generation time, encryption time,
and decryption time has been calculated and compared with access control
mechanism without blockchain technology.
Internet of things (IoT) has become one of the eminent phenomena in human
life along with its collaboration with wireless sensor networks (WSNs), due
to enormous growth in the domain; there has been a demand to address the
various issues regarding it such as energy consumption, redundancy, and
overhead. Data aggregation (DA) is considered as the basic mechanism to
minimize the energy efficiency and communication overhead; however,
security plays an important role where node security is essential due to the
volatile nature of WSN. Thus, we design and develop proximate node aware
secure data aggregation (PNA-SDA). In the PNA-SDA mechanism, additional
data is used to secure the original data, and further information is shared with
the proximate node; moreover, further security is achieved by updating the
state each time. Moreover, the node that does not have updated information is
considered as the compromised node and discarded. PNA-SDA is evaluated
considering the different parameters like average energy consumption, and
average deceased node; also, comparative analysis is carried out with the
existing model in terms of throughput and correct packet identification.
Drones provide an alternative progression in protection submissions since
they are capable of conducting autonomous seismic investigations. Recent
advancement in unmanned aerial vehicle (UAV) communication is an internet
of a drone combined with 5G networks. Because of the quick utilization of
rapidly progressed registering frameworks besides 5G officialdoms, the
information from the user is consistently refreshed and pooled. Thus, safety
or confidentiality is vital among clients, and a proficient substantiation
methodology utilizing a vigorous sanctuary key. Conventional procedures
ensure a few restrictions however taking care of the assault arrangements in
information transmission over the internet of drones (IOD) environmental
frameworks. A unique hyperelliptical curve (HEC) cryptographically based
validation system is proposed to provide protected data facilities among
drones. The proposed method has been compared with the existing methods
in terms of packet loss rate, computational cost, and delay and thereby
provides better insight into efficient and secure communication. Finally, the
simulation results show that our strategy is efficient in both computation and
communication.
Monitoring behavior, numerous actions, or any such information is considered
as surveillance and is done for information gathering, influencing, managing,
or directing purposes. Citizens employ surveillance to safeguard their
communities. Governments do this for the purposes of intelligence collection,
including espionage, crime prevention, the defense of a method, a person, a
group, or an item; or the investigation of criminal activity. Using an internet
of things (IoT) rover, the area will be secured with better secrecy and
efficiency instead of humans, will provide an additional safety step. In this
paper, there is a discussion about an IoT rover for remote surveillance based
around a Raspberry Pi microprocessor which will be able to monitor a
closed/open space. This rover will allow safer survey operations and would
help to reduce the risks involved with it.
In a world where climate change looms large the spotlight often shines on
greenhouse gases, but the shadow of man-made aerosols should not be
underestimated. These tiny particles play a pivotal role in disrupting Earth's
radiative equilibrium, yet many mysteries surround their influence on various
physical aspects of our planet. The root of these mysteries lies in the limited
data we have on aerosol sources, formation processes, conversion dynamics,
and collection methods. Aerosols, composed of particulate matter (PM),
sulfates, and nitrates, hold significant sway across the hemisphere. Accurate
measurement demands the refinement of in-situ, satellite, and ground-based
techniques. As aerosols interact intricately with the environment, their full
impact remains an enigma. Enter a groundbreaking study in Morocco that
dared to compare an internet of thing (IoT) system with satellite-based
atmospheric models, with a focus on fine particles below 10 and 2.5
micrometers in diameter. The initial results, particularly in regions abundant
with extraction pits, shed light on the IoT system's potential to decode
aerosols' role in the grand narrative of climate change. These findings inspire
hope as we confront the formidable global challenge of climate change.
The use of technology has a significant impact to reduce the consequences of
accidents. Sensors, small components that detect interactions experienced by
various components, play a crucial role in this regard. This study focuses on
how the MPU6050 sensor module can be used to detect the movement of
people who are falling, defined as the inability of the lower body, including
the hips and feet, to support the body effectively. An airbag system is
proposed to reduce the impact of a fall. The data processing method in this
study involves the use of a threshold value to identify falling motion. The
results of the study have identified a threshold value for falling motion,
including an acceleration relative (AR) value of less than or equal to 0.38 g,
an angle slope of more than or equal to 40 degrees, and an angular velocity
of more than or equal to 30 °/s. The airbag system is designed to inflate
faster than the time of impact, with a gas flow rate of 0.04876 m3
/s and an
inflating time of 0.05 s. The overall system has a specificity value of 100%,
a sensitivity of 85%, and an accuracy of 94%.
The fundamental principle of the paper is that the soil moisture sensor obtains
the moisture content level of the soil sample. The water pump is automatically
activated if the moisture content is insufficient, which causes water to flow
into the soil. The water pump is immediately turned off when the moisture
content is high enough. Smart home, smart city, smart transportation, and
smart farming are just a few of the new intelligent ideas that internet of things
(IoT) includes. The goal of this method is to increase productivity and
decrease manual labour among farmers. In this paper, we present a system for
monitoring and regulating water flow that employs a soil moisture sensor to
keep track of soil moisture content as well as the land’s water level to keep
track of and regulate the amount of water supplied to the plant. The device
also includes an automated led lighting system.
In order to provide sensing services to low-powered IoT devices, wireless sensor networks (WSNs) organize specialized transducers into networks. Energy usage is one of the most important design concerns in WSN because it is very hard to replace or recharge the batteries in sensor nodes. For an energy-constrained network, the clustering technique is crucial in preserving battery life. By strategically selecting a cluster head (CH), a network's load can be balanced, resulting in decreased energy usage and extended system life. Although clustering has been predominantly used in the literature, the concept of chain-based clustering has not yet been explored. As a result, in this paper, we employ a chain-based clustering architecture for data dissemination in the network. Furthermore, for CH selection, we employ the coati optimisation algorithm, which was recently proposed and has demonstrated significant improvement over other optimization algorithms. In this method, the parameters considered for selecting the CH are energy, node density, distance, and the network’s average energy. The simulation results show tremendous improvement over the competitive cluster-based routing algorithms in the context of network lifetime, stability period (first node dead), transmission rate, and the network's power reserves.
The construction industry is an industry that is always surrounded by
uncertainties and risks. The industry is always associated with a threatindustry which has a complex, tedious layout and techniques characterized by
unpredictable circumstances. It comprises a variety of human talents and the
coordination of different areas and activities associated with it. In this
competitive era of the construction industry, delays and cost overruns of the
project are often common in every project and the causes of that are also
common. One of the problems which we are trying to cater to is the improper
handling of materials at the construction site. In this paper, we propose
developing a system that is capable of tracking construction material on site
that would benefit the contractor and client for better control over inventory
on-site and to minimize loss of material that occurs due to theft and misplacing
of materials.
Today, health monitoring relies heavily on technological advancements. This
study proposes a low-power wide-area network (LPWAN) based, multinodal
health monitoring system to monitor vital physiological data. The suggested
system consists of two nodes, an indoor node, and an outdoor node, and the
nodes communicate via long range (LoRa) transceivers. Outdoor nodes use an
MPU6050 module, heart rate, oxygen pulse, temperature, and skin resistance
sensors and transmit sensed values to the indoor node. We transferred the data
received by the master node to the cloud using the Adafruit cloud service. The
system can operate with a coverage of 4.5 km, where the optimal distance
between outdoor sensor nodes and the indoor master node is 4 km. To further
predict fall detection, various machine learning classification techniques have
been applied. Upon comparing various classifier techniques, the decision tree
method achieved an accuracy of 0.99864 with a training and testing ratio of
70:30. By developing accurate prediction models, we can identify high-risk
individuals and implement preventative measures to reduce the likelihood of
a fall occurring. Remote monitoring of the health and physical status of elderly
people has proven to be the most beneficial application of this technology.
The effectiveness of adaptive filters are mainly dependent on the design
techniques and the algorithm of adaptation. The most common adaptation
technique used is least mean square (LMS) due its computational simplicity.
The application depends on the adaptive filter configuration used and are well
known for system identification and real time applications. In this work, a
modified delayed μ-law proportionate normalized least mean square
(DMPNLMS) algorithm has been proposed. It is the improvised version of the
µ-law proportionate normalized least mean square (MPNLMS) algorithm.
The algorithm is realized using Ladner-Fischer type of parallel prefix
logarithmic adder to reduce the silicon area. The simulation and
implementation of very large-scale integration (VLSI) architecture are done
using MATLAB, Vivado suite and complementary metal–oxide–
semiconductor (CMOS) 90 nm technology node using Cadence RTL and
Genus Compiler respectively. The DMPNLMS method exhibits a reduction
in mean square error, a higher rate of convergence, and more stability. The
synthesis results demonstrate that it is area and delay effective, making it
practical for applications where a faster operating speed is required.
The increasing demand for faster, robust, and efficient device development of enabling technology to mass production of industrial research in circuit design deals with challenges like size, efficiency, power, and scalability. This paper, presents a design and analysis of low power high speed full adder using negative capacitance field effecting transistors. A comprehensive study is performed with adiabatic logic and reversable logic. The performance of full adder is studied with metal oxide field effect transistor (MOSFET) and negative capacitance field effecting (NCFET). The NCFET based full adder offers a low power and high speed compared with conventional MOSFET. The complete design and analysis are performed using cadence virtuoso. The adiabatic logic offering low delay of 0.023 ns and reversable logic is offering low power of 7.19 mw.
The global agriculture system faces significant challenges in meeting the
growing demand for food production, particularly given projections that the
world's population will reach 70% by 2050. Hydroponic farming is an
increasingly popular technique in this field, offering a promising solution to
these challenges. This paper will present the improvement of the current
traditional hydroponic method by providing a system that can be used to
monitor and control the important element in order to help the plant grow up
smoothly. This proposed system is quite efficient and user-friendly that can
be used by anyone. This is a combination of a traditional hydroponic system,
an automatic control system and a smartphone. The primary objective is to
develop a smart system capable of monitoring and controlling potential
hydrogen (pH) levels, a key factor that affects hydroponic plant growth.
Ultimately, this paper offers an alternative approach to address the challenges
of the existing agricultural system and promote the production of clean,
disease-free, and healthy food for a better future.
More from International Journal of Reconfigurable and Embedded Systems (20)
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.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
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SDSFLF: fault localization framework for optical communication using software digital switching network
1. International Journal of Reconfigurable and Embedded Systems (IJRES)
Vol. 12, No. 1, March 2023, pp. 113~124
ISSN: 2089-4864, DOI: 10.11591/ijres.v12.i1.pp113-124 113
Journal homepage: http://ijres.iaescore.com
SDSFLF: fault localization framework for optical
communication using software digital switching network
Chitra Raju1
, Sudarmani Rajagopal1
, Kanagaraj Venusamy2
,
Kannadhasan Suriyan3
, Manjunathan Alagarsamy4
1
School of Engineering, Avinashilingam Institute for Home Science and higher Education for Women, Coimbatore, India
2
Department of Mechatronics, Rajalakshmi Engineering College, Thandalam, Chennai, India
3
Department of Electronics and Communication Engineering, Study World College of Engineering, Coimbatore, Tamilnadu, India
4
Department of Electronics and Communication Engineering, K. Ramakrishnan College of Technology, Trichy, India,
Article Info ABSTRACT
Article history:
Received Jul 12, 2022
Revised Aug 7, 2022
Accepted Oct 17, 2022
Optical network is an emerging technology for data communication
inworldwide. The information is transmitted from the source to destination
through the fiber optics. All optical network (AON) provides good
transmission transparency, good expandability, large bandwidth, lower bit
error rate (BER), and high processing speed. Link failure and node failure
haveconsistently occurred in the traditional methods. In order to overcome
the above mentioned issues, this paper proposes a robust software defined
switching enabled fault localization framework (SDSFLF) to monitor the
node and link failure in an AON. In this work, a novel faulty node
localization (FNL) algorithm is exploited to locate the faulty node. Then, the
software defined faulty link detection (SDFLD) algorithm that addresses the
problem of link failure. The failures are localized in multi traffic stream
(MTS) and multi agent system (MAS). Thus, the throughput is improved in
SDSFLF compared than other existing methods like traditional routing and
wavelength assignment (RWA), simulated annealing (SA) algorithm, attack-
aware RWA (A-RWA) convex, longest path first (LPF) ordering, and
biggest source-destination node degree (BND) ordering. The performance of
the proposed algorithm is evaluated in terms of network load, wavelength
utilization, packet loss rate, and burst loss rate. Hence, proposed SDSFLF
assures that high performance is achieved than other traditional techniques.
Keywords:
All optical network
Faulty node localization
Multi-traffic-stream
Software defined faulty link
detection
Software defined switching
enabled fault localization
framework
This is an open access article under the CC BY-SA license.
Corresponding Author:
Chitra Raju
Department of Electronics and Communication Engineering
Avinashilingam Institute for Home Science and higher Education for Women
Coimbatore, Tamil Nadu, India
Chitra_ece@avinuty.ac.in
1. INTRODUCTION
In worldwide, the communication network is the inevitable portion of human life for running an
efficient way of life. In spite of spending much more time for searching a good communication bandwidth
network for transmitting the information, an optical network is the solution to accommodate a large number
of users with available frequency and satisfied the user demands. In the optical network, there are two way
for communicating processes such as optical electrical optical (OEO) network and all optical network (AON)
conversion. The OEO network prompts from the traffic increases in accordance with it using excessive power
(optical to electrical conversion and electrical to optical conversion process takes more time and more
power). The AON takes less time for converting process while the input source is a light signal. Hence,
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114
choose an AON for communication. The optical interconnection networks in the data centers [1] are
introduced for maximizing throughput and consumptive less power. Hence, the interconnection to be
accomplished is processed via the ultra-high capacity. But in case of encountering some link failure, the
localization must be ensured in prior. The distributed attack localization algorithm of all optical network
(AON) is used to locate the attack in multichannel television sound and multi agent system [2]. By using the
communication scheme such as mail-slot and multi-thread to predict the attacks. The abnormal nodes and the
attacks are located effectively in this algorithm.
Hence, the major improvement requires detecting the abnormal state in the neighboring node.
Because it’s caused due to the attack propagation or node itself. Therefore, the estimation of node delay and
the link are the major aspects of the problem in undirected networks [3]. The end-to-end measurements are
used to estimate the delay time of transmission and to pre-specify the delay paths. The network tomography
problem and the compressive sensing are enhanced by a fast reference-based algorithm for network
tomography via compressive sensing (FRANTIC). The key issue prevailing within the network is SHO-FA
algorithm from the compressive sensing rather than drawn the unlike the matrix entries commencing from the
set of integers. Finally, the Steiner trees is accomplished by constructing the measurement operations. The
major problem in this specified approach is to fail the transmission while transmitting large scale of data
packets. Hence, the network engineering task needs the required traffic information for transformation.
The compressive sampling approach [4] is utilized for effective recovery of the missing internet
traffic information. The reconstruction of the missing traffic information is based on the six missing patterns
on the performance of the traffic matrix reconstruction algorithm, the link sensitivity is traced, and detect the
time sensitivity of the network. These are the performance done in the internet traffic monitoring system. Due
to their high transmission capacities, the optical networks play an important role in modern information
technology. Therefore, the comprehensive survey software defined optical networks (SDOPs) [5] is studied
and examined the software defined networking (SDN) paradigm in the optical network. This survey broadly
insurances the flexibility of SDN control for supporting networking applications with an underlying optical
network infrastructure. And also investigate the Software defined optical networks (SDON) related
mechanisms fornetwork virtualization, an orchestration of multilayer and multi-domain networking in the
optical networks. The novel technical contributions of the proposed approach are listed as: i) the faulty node
localization (FNL) algorithm is exploited to detect the failure nodes which minimizes the transmission delay
time and ii) the software defined faulty link detection (SDFLD) algorithm that addresses the problem of link
failure in multi agent system (MAS) and multichannel television sound (MTS) and also maximize throughput
value.
2. RELATED WORK
In this section, the review of various data dissemination, communication strategies and the security
in optical networking schemes are presented with their merits and demerits. Zhao et al. [6] viewed the inter-
data-center optical network architecture for detecting the traffic and the capacity. The Google’s network was
achieved due to traffic growth trends and the capacity demands. A proficient review of flex grid dense
wavelength-division multiplexed channel plan and the digital coherent detection was achieved by means of
both capacity and operational scaling of the proposed practical implementations such as C+L-band
transmission, packet and optical layer integration, and a software-defined networking enabled network
architecture. Even though the endorsed network was capable to concentrate on the critical areas such as data
rate mismatch between Ethernet and optical transport, real-time optical performance monitoring, and the
optical regeneration with assurance towards the cost, the energy consumption was mitigated owing to this
network.
Mello et al. [7] analyzed the variable-code-rate transceivers impact of cost, survivability of
wavelength, and the capacity through optical networks. The comprehensive operations of wavelength routing
network transmission were quantified the transmission rate and reach trade off into two hypothetical coded
such as aggressive and conservative modulation. Three representative networks were utilized to evaluate the
performance of the two modulation technologies. The power and modulation format were the major
drawbacks in this network. Ives et al. [8] adapted transmitter power and modulation format to improve the
performance of the optical network. It described a simplified Gaussian noise model approach to estimate the
signal quality. Hence, studied the benefits and strategies for the channel allocation of a wavelength routed
transparent optical mesh network and the power optimization technique.
Tornatore et al. [9] introduced the special issues on the optical network design and modelling
(ONDM). However, it was realized that the network virtualization, dynamic optical networks, spatial division
multiplexing networking, multi-layer design, and the next-generation optical access networks inferred a
traffic issue in addition to it. Saleh and Simmons [10] envisaged an evolution, benefits, challenges, and future
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115
visions within the AON through the formulation of an analytical model. The early vision of present vibrant
state was utilized to review the evolution of AON. The impervious such as relative merits, demerits, and the
numerous benefits was afforded by an optical transmission and all-optical switching technologies.
Finally, discussed the challenges and future directions of AON. Chow et al. [11] proposed the
convergent optical wired and wireless access networks and validated the feasibility of using all-optical
orthogonal frequency division multiplexing (AO-OFDM). Achieved high data rate (>100 Gb/s) and without
beating the speed limit of electronic digital-to-analog and analog-to-digital converters (DAC/ADC) due to the
AO-OFDM was depended on the all optically generated orthogonal subcarriers. Though it was capable of
realizing an AO-OFDM super-channel (SC) the proof-of-concept convergent access network was
significantly considerable. Then, established 40-100 Gb/s wired and gigabit/s 100 GHz millimeter-wave
(MMW) ROF transmissions. Lazzez [12] presented a deep analysis of the security issues of AONs. The
physical infrastructure of AONs was directly affected and that significantly differed the electro-optic and
electronic networks. Therefore, the proper functioning of the network and the infrastructure vulnerabilities
have to be analyzed.
Additionally, the service disruption or a tapping attack to be performed based on the set of
scenarios. The detailed description of the challenging issues and the security attacks were revealed in this
section. Khodashenas et al. [13] estimated the benefits through an optical traffic grooming (AOTG) from the
flexi gridsuper-channels to/ from the all optical add/drop of low rate signals. The thorough and holistic
techno-economic evaluation was achieved in this research field. The optically transparent and OTN-based
solutions in a planning scenario were the existing networks compared with the proposed AOTG technique.
Hence, the consuming cost was the major issues in this research. Jedidi et al. [14] evaluated an optical
performance monitoring and optical network management in order to omit low capacity in AON and also to
mitigate the transmission delay.
The intra-crosstalk in AON was effectively detected and localized the value by a policy monitoring
(PMI) system. Therefore, the new demand was to accept or blocked. Through the quality of service (QoS)
was proficient enough to pass a light path of PMI, it was using supervising performance degradation for
reducing the high cost and complexity of signal quality monitoring. In order to avoid the link failure, high
cost, and complex problem to provide security in AON. Xuan et al. [15] established a novel theoretical
solution framework for discovering the multi-link failure localization. A tree- decomposition based algorithm
was accomplished on employing these small dense networks. On the other hand, it was random walk based
localized algorithm on a large scale sparse networks in accordance with coping three practical constraints.
The link and node delay was the major issue in the undirected networks. Rahman and Arozullah [16] dealt
with the security attacks at the physical level to protect all optical networks were capable of accomplishing
three major steps in a light paths security.
The overall high level protocol for the establishment, management and on-the-fly restoration of
optimal secure light paths established by applying constraint-based open shortest path first (OSPF) source
routing. Then, a protocol utilized in fiber diversity between adjacent nodes to protect against attacks on fiber
links. Finally, analytical models of propagation of security attacks on optical amplifiers and switches were
presented. In case of an attack, the security indices and on-the-fly real-time restoration of components were
estimated based on these models exploited to develop the security envelopes. Mukherjee et al. [17] prepared
a review against disaster disruptions and cascading failures on the cloud services and adapt them to network.
The defense treat reduction agency (DTRA) was supported the recent project of light findings. Tapolcai et al.
[18] explored a global neighborhood failure localization (G-NFL) for sharing the protection scheme.
A novel monitoring trail (m-trail) scenario involved in G-NFL which includes failure dependent
protection (FDP). Thus, achieved ultra-fast failure restoration in all-optical networks. Jiang, et al. [19]
recovered the missing traffic data from the traffic matrix. Suggested the spatio-temporal Kronecker
compressive sensing method from the base of Kronecker compressive sensing. The sparse form of traffic
matrix constructed that exploited from the spatial and temporal properties. Hence, proposed the novel
recovery model to consider the low-rank property of the traffic matrix. The link failure, low throughput,
accuracy were considered as the major aspects to accomplish the great approval performance [20]-[26].
3. SOFTWARE DEFINED SWITCHING ENABLED FAULT LOCALIZATION FRAMEWORK
This section discusses the implementation details of the proposed software defined switching
enabled fault localization framework (SDSFLF) in the MAS and MTS for accomplishing a robust data
transformation network through the implication of optical fiber communication network. The workflow of
the proposed SDSFLF is shown in Figure 1. The proposed work formulation initially prompts for network
deployment with the nodes and link for communicating over the country by means of detecting faulty node
and faulty link in prior. Then, discover the router location for transmitting the data. During communication,
the whole data is optical and thus does not modify the data and its traveled path. Therefore, construct the
4. ISSN: 2089-4864
Int J Reconfigurable & Embedded Syst, Vol. 12, No. 1, March 2023: 113-124
116
directed graph that depends on the discovered route information. Then, each light path cost is calculated and
evaluate the routing metrics for each path. If not evaluated then process the light path cost calculation again.
Otherwise, determine the utilization cost of each path and classify the faulty node and the corresponding
links respectively. Finally, update the failure information in local route entry table for providing
uninterrupted communication service.
Formulated a network of the devised AON is organized with an inclusion of link congestion
probabilities and the faulty node. Therefore, design a well efficient network for transmitting an information.
Then, determine the best route to exchange the information without any interruption. Based on the packets
(bits per second) capacity the routes are assigned to transmit. If transmit the data packets through routers to
send a request and accept the corresponding reply. The hop occurs due to a number of packets passed to the
next network device at a particular time.
Figure 1. Proposed SDSFLF framework
If the hop count denotes the number of devices through which data must pass between source and
destination. It takes the count at least 15 to the maximum number of hops is 255. Therefore, discovered the
route which is the required source to construct the directed graph. Then, the network is represented in a
5. Int J Reconfigurable & Embedded Syst ISSN: 2089-4864
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117
directed graph structure also named as a diagraph. It shows an ordered pairs of edges and the vertices N and
E are called the endpoints of the edge. Therefore, the network designed the directed graph:
𝐺 = (𝑁, 𝐸) (1)
where,
𝑁 represents the vertices of nodes or points in a set of elements
𝐸 represent directed edges or directed links connected between the nodes in a set of ordered pair’s
let consider the number of edges or size of the graph,
𝑛 = |𝐸| (2)
randomly, select the vertex on the directed graph. If moves along the edges and marks that path for reducing
the number of repetitions. Therefore, select the source to destination path based on the same wavelength to
all of its link. If there is no variance occurs on its path, then select the minimum number of wavelengths
utilized path. A set of requests comprises in instances. Therefore, assigning the wavelength to the
corresponding request and not assigned the same wavelength for more than one path. For considering R, a set
of end-to-end measurements paths. Thus, shows the number of measurement path as,
|𝑅| = 𝑛𝑝 (3)
where, 𝑅 represents the measurement paths of the source to destination, and 𝑛𝑝 represents the number of
times to determine the correct path for transmitting the data packets.
Assume that, in each path there are no loops and the length of a path represents 𝑙𝑖 < 𝑠. The 𝑝 = {𝑝𝑖}
represents the states of paths, which is named as congested mean passes at least one congested link or else
passes all links called as non-congested. Therefore, consider directed graph G, and the measurement path Rto
construct the binary routing matrix 𝑀𝑛𝑝𝑋𝑠, where the entry 𝑀𝑖𝑗 = 1 represent the 𝑖𝑡ℎ
path pass through 𝑗𝑡ℎ
edge or
else 𝑀𝑖𝑗 = 0. An end-to-end measurement path 𝑅𝑖( 𝑅𝑖 ∈ 𝑅) represents each row of M and the link of a network
represents each column. If passes each link by at least one path without loss of generality or else link states
are independent due to the measurement.
In this work, several notations are used to derive the link failure which shows that, 𝑉 = [𝑉1𝑉2 … … . 𝑉
𝑛]𝑇
:
the states of a link represented by a random binary variable vector. Assume that 𝑉
𝑗 is independent of each
other. T represents the transposition. 𝑃 = [𝑝1 𝑝2 … … . 𝑝𝑛𝑝]
𝑇
: the state of paths represented by a random binary
variable vector. T represents the transposition state.
Then, determine the cost of each 𝑖𝑡ℎ
light path. The dissimilar probability distribution of noticeable
variables is generated based on the diverseparameter values which are equivalent to the mathematical
notation. Hence, 𝑝𝑖 is the statistical model of the established path, which shows that the model’s fundamental
parameter and dimensionprints are the surveillanceinformation. By utilizing a light path, the ending time of a
connection is determined based on the duration of a connection information and the last ending time of the
connections is used to find the lifetime of a light-path. The main objection of hop time is to use the least
possible number of new light-paths that involves a reduction in the length of the lifetime of existing light-
paths. Therefore, calculates the cost of the trained number of light-path connection that related to the light-
paths of the extended lifetime.
Then, shows the mathematical evaluation of the light-paths lifetime and the duration of the
connection. The new path identified based on some conditions which are satisfied to predict the congested
links. If founded the new path that shows as,
𝐸𝐿𝑇(𝑝𝑖) = 𝑛𝐻𝑖 × 𝑅𝑡 (4)
where, 𝐸𝐿𝑇(𝑝𝑖) represents the extension usage or the lifetime cost of 𝑖𝑡ℎ
light-path, 𝑛𝐻𝑖 represents the
number of hops in 𝑖𝑡ℎ
light-path, 𝑅𝑡 represents the request holding period, and 𝐿𝑇𝑃𝑖 represents the lifetime of
the 𝑖𝑡ℎ
light-path. Therefore, the request holding period denotes,
𝑅𝑡 − 𝐿𝑇𝑃𝑖→ ∆𝑡 (5)
where, ∆𝑡 represents adjustment constant variable. If (4) satisfies the following conditions such as,
if 𝐿𝑇𝑃𝑖 ≥ 𝑅𝑡𝑖.
Then,
6. ISSN: 2089-4864
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118
𝐸𝐿𝑇(𝑝𝑖) = 𝑛𝐻𝑖 × 𝜀 (6)
if 𝐿𝑇𝑃𝑖 < 𝑅𝑡𝑖.
Then,
𝐸𝐿𝑇(𝑝𝑖) = 𝑛𝐻𝑖 ∗ (𝜀 + ∆𝑡) (7)
where, 𝜀 represents exponential constant factor is 10−5
(a small constant factor).
Here, the extensive usage of light path lifetime satisfies the above mentioned condition. If not
satisfied, then move to (7). Therefore, calculate the light path life time which is used to determine the build
the routing matrix. This shows that the effective route path and eliminate the high traffic intensity path. If
eliminate the high traffic route based on the weight calculation which shows the maximum weighted routes.
In order to avoid, list the low traffic intensity nodes to transfer the information. The bandwidth availability
and the extension of the lifetime of the tight-paths are derived from the cost function between the known
duration. Therefore, derive the utilization cost of the established light path 𝑝𝑖 as,
𝑈𝑐(𝑝𝑖) = (𝐸𝐿𝑇(𝑝𝑖) × 𝜎) + (
𝐵𝑊(𝑝𝑖)−𝑏𝑤(𝑝𝑖)
𝐵𝑊(𝑝𝑖)
× (1 − 𝜎)) (8)
where, 𝑈𝑐(𝑝𝑖) represents the utilization cost of light path 𝑝𝑖, 𝜎 represents the weight which is applied to the
extension factor of a lifetime of the light-path, 𝑏𝑤 represents the available bandwidth in𝑝𝑖, 𝐵𝑊 represents
the total bandwidth of 𝑝𝑖, and 1 − 𝜎 represents the weight of bandwidth utilization. If 𝑝𝑖 is a new light-path
mean then satisfy the bandwidth value as,
𝐵𝑊(𝑝𝑖)−𝑏𝑤(𝑝𝑖)
𝐵𝑊(𝑝𝑖)
= 1. Then, determine the utilization cost of new light
path using (8) as,
𝑈𝑐(𝑝𝑖) = (𝐸𝐿𝑇(𝑝𝑖) × 𝜎) + (1 − 𝜎) (9)
These are the expectation condition which utilizes to maximize the throughput value. If examine
whether the links are congested or not due to one of the measurement path. The concrete Internet application
depends on the path packet loss rate threshold 𝛽 valuesimilar with an individual link. If path 𝑝𝑖 exceed the
packet loss rate 𝛽 is said to be congested. Then, determine the congested path probability that introduces a
new term of measurement snapshot. In a fixed length time slotderives the np path measurements which exist
from the snapshot. Hence, the similar 𝑛𝑝 path measurements consists in each snapshot that takes SS
snapshots as,
𝑥 = {𝑥1, 𝑥2, 𝑥3, … … … . . , 𝑥𝑠𝑠 } (10)
Consider, the random binary variable as 𝑥𝑖 thenderive the congestion path expectation can be
calculated. The congested links are recovered from the compressive sensing algorithm. To meetnecessities
adapt some more conditions which are essential for routing matrix. Usually, the term identifiable is derived
from a statistical model. Hence, the infinite number of observations obtaining from the derived model that
learn the true value. The route matrix value is updated in the local route entry. Hence, identified the failure
link which shows that the effective results. The proposed algorithm is used to locate the faulty node in a
network is listed as Algorithm 1.
Algorithm 1. Faulty node localization
Input: T single sourced Graph topology, S states of each node in T at time t
Find the each node states {St}
If each node states 𝑇[𝑖]. 𝑠 ∈ 𝑆𝑡[𝑖] is normal
𝑇[𝑖] is not a faulty node
Else
For every node states𝑇[𝑖]. 𝑠 ∈ 𝑆𝑡[𝑖] then
IF 𝑇[𝑖]. 𝑠 𝑖𝑠 normal then continue;
Send abnormal status information to downstream nodes
IF the node is the first node of the traffic stream
It’s the faulty node (suspected)
ELSE
IF receiving abnormal information from upstream nodes
It isn’t the faulty node (suspected)
ELSE
It is the faulty source
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119
Initializing the variables T, S, and t to represent the single sourced Graph topology, states of each
node, and time. The subset of each node state represents the {St}. In this novelty, performed under two states
of the network model such as faulty and not faulty node respectively. If suspect the faulty node, send the
abnormal status information to downstream nodes or else receive the abnormal information from upstream
nodes due to a not faulty node. In this way, the failure nodes are localized successively. If the variation is
possible, then go to link detection. The algorithm to detect the faulty link is listed as Algorithm 2.
Algorithm 2. Software defined faulty link detection
Input: suspected faulty node set F 𝑛[𝑖], suspected faulty link set F𝑙[𝑖],
and the set of congested faulty path set Cp
Output: The set of most possible congested links Lc
Initialize 𝐿𝑐 to the empty set and 𝑃(𝑖, 𝑗) = 𝐶𝑝, 𝑥 = 0
For all 𝑖, 𝑗 until 𝑃(𝑖, 𝑗) ≠ 0 +
Find a link 𝑙 ∈ 𝐿𝑐 that maximizes 𝑙𝑘 = 𝑙𝑜𝑔
1
𝐶𝑝
Add 𝑙𝑘 to the solution 𝐿𝑐= 𝐿𝑐 ∪ {𝑙𝑘}, 𝑠𝑒𝑡 𝑥𝑘 = 1 using (10)
𝑇𝑖 = 𝑇𝑖𝑙𝑘,
𝐹𝑛[𝑖] = 𝐹𝑛[𝑖]𝑙𝑘
𝑃(𝑖, 𝑗) = 𝑃(𝑖, 𝑗)𝐶(𝑙𝑘)
𝐶(𝑙𝑗) = 𝐶(𝑙𝑗)𝐶(𝑙𝑘)𝑓𝑜𝑟 𝑎𝑙𝑙 𝑙𝑗 ∈ 𝐹𝑙(𝑖)
End For
Initializing, the variablessuspected faulty node set F n[i], suspected faulty link set Fl[i], and the set
of a congested faulty path set Cp. Then, assign the set of the possible congested links 𝐿𝐶 to be empty
and 𝑃(𝑖, 𝑗) = 𝐶𝑝, 𝑥 = 0. After that, select the maximum value (suppose 𝑙𝑘) from 𝑇𝑖,which is equivalent to
select one suspected congested link 𝑙𝑘from 𝐶𝑝 and place it to 𝐿𝐶, meanwhile delete 𝑙𝑘(1) and the paths
combined with 𝑙𝑘(named by 𝐶(𝑙𝑗)) from 𝑇𝑖 and F𝑙[𝑖]respectively. Where k denotes the number of congested
links. Finally, identified the congested link and select the suitable link to transmit the information without
any interruption.
4. RESULTS AND DISCUSSION
This section illustrates the effectiveness of the proposed system by comparing with the existing
methods such as traditional routing and wavelength assignment (RWA), simulated annealing, attack-aware
RWA (A-RWA) convex, longest path first (LPF), and biggest source-destination node degree (BND) [20].
Proficiency is considered by analyzing various parameters given as network load, wavelength, packet loss
rate, and the burst loss. The delay variance, in-band cross talks, out-of-band cross-talks, and the burst loss
rate of the proposed system is lower than the existing method when compared the results.
4.1. Performance metrics
A number of basic challenges, including architectural ones like whether control should be
distributed or centralised and whether the control and data planes should be distinct, are brought up by the
rise of SDN. There are many unsolved difficulties in the SDN field, from implementation concerns like how
we create dispersed "logically centralised" control planes to architectural questions that are essential to how
networks extend and develop. Furthermore, there is a chance to integrate fault tracking framework more
deeply into the overall design process because SDN is still in its early stages.
The proportion of complete number of requested connections to the single number of requested
connections among all probable source-destination pairs and it represented in terms of 𝜌 as,
𝜌 = ∑
Λ𝑠𝑑
𝑁2−𝑁
(11)
where,
Λ𝑠𝑑representsquantity of requested connection for the source destination pair s-d,
𝛴Λ𝑠𝑑 represents the summation of total demanded network connections,
𝑁 represent the total number of network nodes,
𝑁2
− 𝑁 representsthe single demanded network connection among all the source-destination pairs.
4.2. Wavelength
The wavelength is the process of estimating the distance between source and destination in a path
and it is inversely proportional to frequency. The mathematical formula as,
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120
𝑊 = 𝑣
𝑓
⁄ (12)
where, 𝑣 represents the speed of the light signal, and 𝑓 represents the frequency.
If the same wavelength between the intra-channel, crosstalk generates the in-band jamming attack in
which the optical cross connects on the network that produceshigh power signal injection rate. Based on the
non-ideal isolation switching, cause the power leakage between light paths. Therefore, the high-power
jamming signal occurs due to high leakage which occurs similar wavelength on the attacking signal.
Otherwise, the out-band crosstalk attacks generate owed to high power outflow among the adjacent channels.
It is due to inter-channel crosstalk, and nonlinearities which affect the wavelengths on the same fiber. Hence,
the proposed technique reduces the attacks effectively.
4.3. Utilized wavelength
The network node topology produces the numeral of light paths which is the required source to
interact the nodes. This account is consideredinto continuity constraints and the distinct wavelength
assignment. The network load is assumed to 0.6 and 1.8 for minimizing the number of the wavelengths
usage. The proposed SDSFLF method devised that, minimize the number of wavelengths used and also
reduce the effect of light path interactions due to the in-band and out-of-band crosstalk. Figure 2 represents
the number of light paths that interact through in-band and out-of-band crosstalk versus a number of available
wavelengths for load 06 and 1.8.
Figure 2(a) illustrates that the existing RWA, A-RWA convex, and the simulated annealing
approaches, the number of interactions decreases significantly with increasing the number of available
wavelengths. Number of light paths that interact through in-band and out-of-band crosstalk for load=1.8 is
shown in Figure 2(b). Thus, the proposed SDSFLF method performance significantly reduces the jamming
attack than the existing techniques.
(a)
(b)
Figure 2. Wavelengths under the light paths in-band and out-of-band crosstalk for (a) load=0.6 and
(b) load=1.8
From the figure, shows that the existing LPF, BND, simulated annealing, and the A-RWA-convex
approaches, the number of interactions decreases significantly with increasing the number of available
0
100
200
300
400
500
24 26 28 30 32 34 36
in-band
and
out-of-band
lightpaths
interactions
Number of Wavelengths
Traditional RWA Simulated Annealing A-RWA-Convex LIFE@LP
0
50
100
150
200
250
12 14 16 18 20 22 24 26 28
in-band
and
out-of-band
lightpaths
interactions
(@load=1.8)
Number of Wavelengths
LPF BND Simulated Annealing A-RWA convex LIFE@LP
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121
wavelength. The proposed SDSFLF algorithm improves the wavelength usage than other existing algorithms.
Hence, the SDSFLF framework achieves the greatest performance over numerous collections during
execution.
The number of available wavelengths per fiber is assumed to be W=24. Figure 3 shows that load
with wavelength utilization with Figure 3(a) represent the number of light path interaction through in-band
and out-of-band crosstalk with respect to network load at constant wavelength 24 is shown in Figure 3(b).
From the figure shows, the SDSFLF framework exhibits a considerable changes in some cases. The existing
RWA, simulated annealing, and the A-RWA-convex performance are compared with the proposed algorithm.
The proposed SDSFLF is highly reduced the in-band and out-of-band crosstalk and produce the un-interrupt
communication. Hence, the proposed algorithm is expressively better than existing.
(a)
(b)
Figure 3. Load with wavelength utilization (a) in-band and out-of-band crosstalk at W=24
and (b) utilized Wavelength at W=24
Figure 3(b) represents the total number of utilized wavelength through all the light path. In general,
the proposed SDSFLF technique is the best choice for utilizing minimum wavelength and effectively using
the network resources. Therefore, the proposed algorithm achieves high network security in contradiction of
high-power jamming attackdue to increase in the number of utilized wavelength. Hence, the SDSFLF meets
the lower bound of the wavelength utilization for most of the network load.
The packet loss rate is calculated by the delay occurrs in the transmission during high traffic
intensity range. It is used to estimate the total delay variance in between source node to the destination node
of packet transmission’s rate while the packet loss rate of a good link is around zero. Figure 4 represents the
packet loss rate.
From the Figure 4, clearly shows that the packet loss rate delay variance of the link under various
intensities of cross traffic. The x-axis represents the increasing traffic intensities which are an increasing
number of flows loaded on the link and the y-axis represents the delay variances of the link. Hence, the
increased data packets transmitted at the specific time is varied randomly. The existing technique delay
variance of the link is higher than the proposed technique. Therefore, the minimum number of delay variance
is produced in this proposed SDSFLF framework.
The burst loss rate is defined as the average ratio of packets both lost packets and the discard
packets over high traffic intensity. Figure 5 represents the burst loss rate. The burst loss rate is ratio of packet
under the wavelength of the traffc intensity wity delay variance of the link.
0
100
200
300
400
500
600
700
0,1 0,2 0,3 0,4 0,5 0,6 0,7
in-band
and
out-of-band
lightpaths
interactions
Load
Traditional RWA Simulated Annealing A-RWA-Convex LIFE@LP
0
50
100
150
200
250
300
350
0,1 0,2 0,3 0,4 0,5 0,6 0,7
Total
Wavelength
Utilization
Load
Traditional RWA Simulated Annealing A-RWA-Convex LIFE@LP
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From the Figure 5, shows that the proposed SDSFLF method is compared with the traditional RWA,
simulated annealing, and the ARWA-convex methods. The proposed SDSFLF method achieves lower burst
rate such as 0.040, 0.043, 0.044, 0.250, 0.570, 0.790, 0.843, 1.001, 1.160, and 1.318 due to the high traffic
intensity range from 1 to 10 ms respectively. Hence, it’s proven, that the proposed SDSFLF assures that
minimum burst loss rate than the existing technique.
Figure 4. Packet loss rate
Figure 5. Burst loss rate
5. CONCLUSION
This paper developed a software defined switching enabled fault localization framework (SDSFLF)
for link failure localization and improves throughput in the all opticalnetwork. It will deliver good
transmission transparency, minimum bit error rate (BER), massive bandwidth, and the good expandability.
The proposed faulty node localization (FNL) and the software defined faulty link detection (SDFLD)
algorithm is to monitor and localize the faulty nodes and links in an AON. The FNL is processed for locating
the failure node which is the required source of link failure estimation and the SDFLD algorithm is used
detect the faulty link. Hence, the devised SDSFLF framework improves its throughput than other prevailing
methodologies like traditional RWA, simulated annealing, A-RWA-convex, LPF, and BND. The various
performance measures such as network load, wavelength utilization, packet loss rate and the burst loss rate
are evaluated. Therefore, the proposed SDSFLF framework is achieved high performance than the other
traditional techniques.
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BIOGRAPHIES OF AUTHORS
Mrs. Chitra Raju received the B.E (ECE)., degree in Government College of
Technology, Coimbatore in 2000. She received M.E degree in VLSI Design from the Anna
University of Technology, Coimbatore in 2010. Currently, she is working as Assistant
Professor (SS) in Department of ECE, School of Engineering, Avinashilingam Institute,
Coimbatore and she is Part time research scholar inDepartment of ECE, School of
Engineering, Avinashilingam Institute, Coimbatore, Tamil Nadu. She published 15 papers in
international journals and presented papers in international conferences. Her research
interestincludes computer networks, wireless sensor networks and internet of things. She can
be contacted at email: chitra_ece@avinuty.ac.in.
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Dr. Sudarmani Rajagopal is currently working as Associate Professor in the
Department of Electronics and Communication Engineering, School of Engineering at the
Avinashilingam Institute for Home Science and Higher Education for Women, in Tamil Nadu,
India. She received her B.E. Electronics and Communication Engineering from Bharathiar
University, Tamil Nadu, India and her M.E. (Applied Electronics) and Ph.D. in Information
and Communication Engineering from Anna University, Chennai - India. Dr. R. Sudarmani
published 74 papers in refereed Journals, conferences and chapters in books. She also
presented research papers at several national and international conferences including the
International Conference IEEE TENCON 2011 at Bali, Indonesia. Her research interest
includes wireless sensor networks, wireless communication and signal processing. She can be
contacted at email: sudarmani_ece@avinuty.ac.in.
Kanagaraj Venusamy is an Assistant Professor at Rajalakshmi Engineering
College in Chennai, Tamilnadu, India. He obtained his undergraduate degree in Electronics
and Communication Engineering (2005). He has received his Master of Business
Administration in Production Management from ManonmaniumSundaranar University in
2011. He received a Master of Engineering in Mechatronics from Anna University affiliated
College-Rajas college in 2019. His main area of awareness is robotics, drone, industrial
automation, artificial intelligence, internet of things, embedded system, entrepreneurship and
human resource development. He had a ten years of teaching experience in reputed academic
Institution in India and Sultanate of Oman. He has technically assisted in various academic
Projects, Robotics International Competition, TRC-Oman funded Projects. He acted as Course
facilitator in numerous short term course and Workshop which is organized by IEEE-UTAS-Al
mussanah. His team won GCC level and national level Robotics competition in the year of
2017,2018 and 2019. He has published journals, book chapter and Conferences in high indexed
platform. He has conducted various technical workshop in online mode in the following area
robotics, embedded system, drone and machine learning during pandemic period (2020-2021).
He can be contacted at email: kanagaraj.v@rajalakshmi.edu.in.
Dr. Kannadhasan Suriyan is working as an Assistant Professor in the department
of Electronics and Communication Engineering in Study World College of Engineering,
Coimbatore, Tamilnadu, India. He is Completed the Ph.D in the field of Smart Antenna for
Anna University in 2022. He is Twelve years of teaching and research experience. He obtained
his B.E in ECE from Sethu Institute of Technology, Kariapatti in 2009 and M.E in
Communication Systems from Velammal College of Engineering and Technology, Madurai in
2013. He obtained his M.B.A in Human Resources Management from Tamilnadu Open
University, Chennai. He has published around 45 papers in the reputed indexed international
journals indexed by SCI, Scopus, Web of science, Major indexing and more than 146 papers
presented/published in national, international journal and conferences. Besides he has
contributed a book chapter also. He also serves as a board member, reviewer, speaker, session
chair, advisory and technical committee of various colleges and conferences. He is also to
attend the various workshop, seminar, conferences, faculty development programme, STTP
and Online courses. His areas of interest are smart antennas, digital signal processing, wireless
communication, wireless networks, embedded system, network security, optical
communication, microwave antennas, electromagnetic compatability and interference, wireless
sensor networks, digital image processing, satellite communication, cognitive radio design and
soft computing techniques. He is Member of IEEE, ISTE, IEI, IETE, CSI, IAENG, SEEE,
IEAE, INSC, IARDO, ISRPM, IACSIT, ICSES, SPG, SDIWC, IJSPR and EAI Community.
He can be contacted at email: kannadhasan.ece@gmail.com.
Manjunathan Alagarsamy received the Engineer degree in Electronics and
Comunication Engineering from Dr. Navalar Nedunchezhiyan College of Engineering in
2010.He received the Master degree in Embedded System Technologies from Raja College of
Engineering and Technology, Madurai, Tamilnadu, India in 2013.He is currently working as
an Assistant Professor in the Department of Electronics and Communication Engineering at K.
Ramakrishnan College of Technology, Trichy, India. His area of interests includes embedded
systems, image processing, sensors and interfacing networks and internet of things. He has
published 13 articles in peer reviewed International journals and presented 6 papers in
International conferences. He can be contacted at email: manjunathankrct@gmail.com.