Pub Date : 2023-10-01DOI: 10.22247/ijcna/2023/223422
G.S. Sapna, Shashikumar Dandinashivara Revanna
– Security is a major challenge in the Internet of Things (IoT) domain as it plays a crucial role in a safe and uninterrupted data transmission, across various hand-held devices connected to the network. Establishing a secure Routing Protocol for Low power and lossy networks (RPL) is necessary and crucial, as it is the standard RPL network in IoT that helps to remove malicious nodes from the network. The existing researches focused on developing energy-saving techniques, malicious node detection techniques, as well as security-enhancing techniques, but neglected energy efficiency, and other trust-related considerations. This resulted in reduced confidentiality and unauthorized access to user data. To overcome these limitations, a Secure Energy Efficient Firefly Optimization Algorithm in RPL (SEEFOA-RPL) is proposed in this research for establishing a reliable and energy-efficient routing path by using Destination-Oriented Directed Acyclic Graph (DODAG) architecture. The proposed algorithm improves security measures in handheld devices such as smartphones, wearable watches, digital cameras, portable media players, and tablets. Initially, a trust model for the RPL network is established to calculate the trust parameters that help in building a secure routing in the network. The SEEFOA is capable of solving complex optimization problems, and finds the best optimum solution for a secure-energy efficient routing path. The proposed SEEFOA-RPL delivers a high-level performance in terms of Detection Rate (DR), False Negative Rate (FNR), and False Positive Rate (FPR), respectively measured at 99%, 12%, and 17% in an attack interval 4, and Packet Drop Ratio (PDR) measured at 82% in an attack interval of 1.5.
{"title":"An Interoperability Framework for Enhanced Security of Handheld Devices Using IoT-Based Secure Energy Efficient Firefly Optimization Algorithm","authors":"G.S. Sapna, Shashikumar Dandinashivara Revanna","doi":"10.22247/ijcna/2023/223422","DOIUrl":"https://doi.org/10.22247/ijcna/2023/223422","url":null,"abstract":"– Security is a major challenge in the Internet of Things (IoT) domain as it plays a crucial role in a safe and uninterrupted data transmission, across various hand-held devices connected to the network. Establishing a secure Routing Protocol for Low power and lossy networks (RPL) is necessary and crucial, as it is the standard RPL network in IoT that helps to remove malicious nodes from the network. The existing researches focused on developing energy-saving techniques, malicious node detection techniques, as well as security-enhancing techniques, but neglected energy efficiency, and other trust-related considerations. This resulted in reduced confidentiality and unauthorized access to user data. To overcome these limitations, a Secure Energy Efficient Firefly Optimization Algorithm in RPL (SEEFOA-RPL) is proposed in this research for establishing a reliable and energy-efficient routing path by using Destination-Oriented Directed Acyclic Graph (DODAG) architecture. The proposed algorithm improves security measures in handheld devices such as smartphones, wearable watches, digital cameras, portable media players, and tablets. Initially, a trust model for the RPL network is established to calculate the trust parameters that help in building a secure routing in the network. The SEEFOA is capable of solving complex optimization problems, and finds the best optimum solution for a secure-energy efficient routing path. The proposed SEEFOA-RPL delivers a high-level performance in terms of Detection Rate (DR), False Negative Rate (FNR), and False Positive Rate (FPR), respectively measured at 99%, 12%, and 17% in an attack interval 4, and Packet Drop Ratio (PDR) measured at 82% in an attack interval of 1.5.","PeriodicalId":36485,"journal":{"name":"International Journal of Computer Networks and Applications","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136129569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.22247/ijcna/2023/223420
Gagandeep Kaur, Balraj Singh, Ranbir Singh Batth
– In the transformative landscape of mobile edge computing (MEC), where the convergence of computation and communication fuels the era of ubiquitous connectivity, formidable challenges loom large. The burgeoning demand for real-time, data-intensive applications places unprecedented pressure on existing infrastructure, demanding innovative solutions to address the intricate web of challenges. This paper embarks on a compelling journey through the realm of MEC, uncovering the multifaceted challenges that have hitherto impeded its seamless integration into our digital lives. As the proliferation of mobile devices and their insatiable appetite for data strain the network's capacity, latency becomes a formidable adversary, threatening the integrity of applications requiring split-second responsiveness. Furthermore, the capricious nature of mobile devices and their mobility introduces an unpredictable dynamism into the network topology, rendering traditional traffic control approaches ineffective. The consequence is a tangled web of congestion, resource underutilization, and compromised Quality of Service (QoS), all of which hinder the realization of MEC's full potential. In response to these challenges, we unveil a pioneering solution—a QoS-aware Adaptive Data Dissemination Engine (QADE) paired with Dynamic Traffic Flow Control (DTFC). This synergistic model augments the capabilities of MEC deployments by harnessing the power of content-based routing and advanced optimization techniques. QADE, with its innovative utilization of Elephant Herding Particle Swarm Optimizer (EHPSO), refines data dissemination processes with an unprecedented focus on QoS metrics. Temporal delay, energy consumption, throughput, and Packet Delivery Ratio (PDR) become our guiding stars in the quest for routing efficiency. By harnessing this wealth of information, QADE emerges as a beacon of efficiency, driving latency to its lowest ebb, magnifying bandwidth, mitigating packet loss, elevating throughput, and rationalizing operational costs. DTFC complements this endeavor by dynamically steering traffic flows by edge processing capacity, thereby circumventing congestion pitfalls and achieving resource utilization efficiency hitherto considered unattainable. In a series of exhaustive evaluations, our proposed QADE with DTFC emerges as a beacon of hope, surpassing traditional methodologies. With an 8.5% reduction in latency compared to RL, a 16.4% reduction compared to MTO SA, and an impressive 18.0% reduction compared to HFL, it ushers in a new era of real-time data dissemination. By championing QoS awareness, adaptability, and efficiency, this study catapults mobile edge computing into a future defined by resource optimization and stellar network performance, ushering in an era where challenges bow before innovation processes.
{"title":"Design of an Efficient QoS-Aware Adaptive Data Dissemination Engine with DTFC for Mobile Edge Computing Deployments","authors":"Gagandeep Kaur, Balraj Singh, Ranbir Singh Batth","doi":"10.22247/ijcna/2023/223420","DOIUrl":"https://doi.org/10.22247/ijcna/2023/223420","url":null,"abstract":"– In the transformative landscape of mobile edge computing (MEC), where the convergence of computation and communication fuels the era of ubiquitous connectivity, formidable challenges loom large. The burgeoning demand for real-time, data-intensive applications places unprecedented pressure on existing infrastructure, demanding innovative solutions to address the intricate web of challenges. This paper embarks on a compelling journey through the realm of MEC, uncovering the multifaceted challenges that have hitherto impeded its seamless integration into our digital lives. As the proliferation of mobile devices and their insatiable appetite for data strain the network's capacity, latency becomes a formidable adversary, threatening the integrity of applications requiring split-second responsiveness. Furthermore, the capricious nature of mobile devices and their mobility introduces an unpredictable dynamism into the network topology, rendering traditional traffic control approaches ineffective. The consequence is a tangled web of congestion, resource underutilization, and compromised Quality of Service (QoS), all of which hinder the realization of MEC's full potential. In response to these challenges, we unveil a pioneering solution—a QoS-aware Adaptive Data Dissemination Engine (QADE) paired with Dynamic Traffic Flow Control (DTFC). This synergistic model augments the capabilities of MEC deployments by harnessing the power of content-based routing and advanced optimization techniques. QADE, with its innovative utilization of Elephant Herding Particle Swarm Optimizer (EHPSO), refines data dissemination processes with an unprecedented focus on QoS metrics. Temporal delay, energy consumption, throughput, and Packet Delivery Ratio (PDR) become our guiding stars in the quest for routing efficiency. By harnessing this wealth of information, QADE emerges as a beacon of efficiency, driving latency to its lowest ebb, magnifying bandwidth, mitigating packet loss, elevating throughput, and rationalizing operational costs. DTFC complements this endeavor by dynamically steering traffic flows by edge processing capacity, thereby circumventing congestion pitfalls and achieving resource utilization efficiency hitherto considered unattainable. In a series of exhaustive evaluations, our proposed QADE with DTFC emerges as a beacon of hope, surpassing traditional methodologies. With an 8.5% reduction in latency compared to RL, a 16.4% reduction compared to MTO SA, and an impressive 18.0% reduction compared to HFL, it ushers in a new era of real-time data dissemination. By championing QoS awareness, adaptability, and efficiency, this study catapults mobile edge computing into a future defined by resource optimization and stellar network performance, ushering in an era where challenges bow before innovation processes.","PeriodicalId":36485,"journal":{"name":"International Journal of Computer Networks and Applications","volume":"133 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136129745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.22247/ijcna/2023/223419
G. V. Sowmya, R. Aparna
– Energy efficiency plays a crucial role in extending the operational lifespan of Wireless Sensor Networks (WSNs). It stands as the foremost objective for any routing algorithm designed for WSNs. This study centers on enhancing communication efficiency through a multihop approach guided by the Harmony Search Algorithm (HSA). The process incorporates Cluster Head (CH) selection through the utilization of the HSA and by assessing the quality of the communication channel. There are instances where a channel possesses high capacity, yet it transmits minimal data, leading to resource underutilization. Therefore, if the communication channel’s quality is pre-determined, then algorithms can be developed to establish an upper limit for channel usage, ensuring congestion free and error free maximum data transmission. In the proposed methodology, parameters such as residual energy, distance and node degree were taken into account for CH selection. Subsequently, clusters were formed based on Shannon Channel Capacity ‘C’ and path loss model. Following the CH selection and cluster formation, a communication was established using HSA. A comparative analysis was conducted on network life span, packets sent to Base Station (BS) and energy utilization for the three algorithms, Energy Efficient Harmony Search Based Routing (EEHSBR), Clustering and Routing in wireless sensor networks using Harmony Search Algorithm (CRHS), and Robust Harmony Search Algorithm based clustering protocol for wireless sensor networks (RHSA).
{"title":"Energy Efficient Cluster Formation and Multihop Routing Based on Improved Harmony Search Algorithm for Wireless Sensor Networks","authors":"G. V. Sowmya, R. Aparna","doi":"10.22247/ijcna/2023/223419","DOIUrl":"https://doi.org/10.22247/ijcna/2023/223419","url":null,"abstract":"– Energy efficiency plays a crucial role in extending the operational lifespan of Wireless Sensor Networks (WSNs). It stands as the foremost objective for any routing algorithm designed for WSNs. This study centers on enhancing communication efficiency through a multihop approach guided by the Harmony Search Algorithm (HSA). The process incorporates Cluster Head (CH) selection through the utilization of the HSA and by assessing the quality of the communication channel. There are instances where a channel possesses high capacity, yet it transmits minimal data, leading to resource underutilization. Therefore, if the communication channel’s quality is pre-determined, then algorithms can be developed to establish an upper limit for channel usage, ensuring congestion free and error free maximum data transmission. In the proposed methodology, parameters such as residual energy, distance and node degree were taken into account for CH selection. Subsequently, clusters were formed based on Shannon Channel Capacity ‘C’ and path loss model. Following the CH selection and cluster formation, a communication was established using HSA. A comparative analysis was conducted on network life span, packets sent to Base Station (BS) and energy utilization for the three algorithms, Energy Efficient Harmony Search Based Routing (EEHSBR), Clustering and Routing in wireless sensor networks using Harmony Search Algorithm (CRHS), and Robust Harmony Search Algorithm based clustering protocol for wireless sensor networks (RHSA).","PeriodicalId":36485,"journal":{"name":"International Journal of Computer Networks and Applications","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136153661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.22247/ijcna/2023/223423
Mohammed Naif Alatawi
– The proliferation of sensor networks and other Internet of Things devices has prompted growing privacy and safety concerns. These devices have very little memory, computing power, and storage space. Security for low-powered IoT devices, such as RFID tags, nodes in wireless sensor networks (WSNs), etc., has become increasingly difficult. So, enough security for these devices was achieved by the development of lightweight cryptographic algorithms. In recent years, "smart cities" have emerged to improve contemporary lifestyles and further social development. These are enabled by developments in ICT and may open up new avenues for social and economic development. However, not everything is as secure and private as we hope it will be. The effects of the Internet of Things on IoT-based data transmission networks have been the subject of extensive study over the past few decades. Due to this flaw in the authentication process, verifying the identification of such people safely is extremely difficult. The study's goal is to provide a safe authentication technique for IoT that makes use of Hybrid and Adaptive Cryptography (HAC). In this study, we focus on authentication as a potential security risk in IoT data transmission networks. The study proposes a hybrid and adaptive cryptography (HAC) approach to authentication for the Internet of Things as a means of resolving this issue. The proposed technique of cryptographic protection makes use of the exclusive-or (Ex-or) operation, a hashing function, and a hybrid encryption strategy based on the Rivest Shamir Adleman (RSA) and the Advanced Encryption Standard (AES) algorithms. The proposed solution is simple to implement while effectively overcoming the cryptographic system's constraints via a hybrid encryption mechanism. Using the Diffie-Hellman key exchange protocol, the RSA algorithm for privacy, and the SHA-1 algorithm for authenticity, this study aims to provide a unified security architecture for modern networks.
{"title":"A Hybrid Cryptographic Cipher Solution for Secure Communication in Smart Cities","authors":"Mohammed Naif Alatawi","doi":"10.22247/ijcna/2023/223423","DOIUrl":"https://doi.org/10.22247/ijcna/2023/223423","url":null,"abstract":"– The proliferation of sensor networks and other Internet of Things devices has prompted growing privacy and safety concerns. These devices have very little memory, computing power, and storage space. Security for low-powered IoT devices, such as RFID tags, nodes in wireless sensor networks (WSNs), etc., has become increasingly difficult. So, enough security for these devices was achieved by the development of lightweight cryptographic algorithms. In recent years, \"smart cities\" have emerged to improve contemporary lifestyles and further social development. These are enabled by developments in ICT and may open up new avenues for social and economic development. However, not everything is as secure and private as we hope it will be. The effects of the Internet of Things on IoT-based data transmission networks have been the subject of extensive study over the past few decades. Due to this flaw in the authentication process, verifying the identification of such people safely is extremely difficult. The study's goal is to provide a safe authentication technique for IoT that makes use of Hybrid and Adaptive Cryptography (HAC). In this study, we focus on authentication as a potential security risk in IoT data transmission networks. The study proposes a hybrid and adaptive cryptography (HAC) approach to authentication for the Internet of Things as a means of resolving this issue. The proposed technique of cryptographic protection makes use of the exclusive-or (Ex-or) operation, a hashing function, and a hybrid encryption strategy based on the Rivest Shamir Adleman (RSA) and the Advanced Encryption Standard (AES) algorithms. The proposed solution is simple to implement while effectively overcoming the cryptographic system's constraints via a hybrid encryption mechanism. Using the Diffie-Hellman key exchange protocol, the RSA algorithm for privacy, and the SHA-1 algorithm for authenticity, this study aims to provide a unified security architecture for modern networks.","PeriodicalId":36485,"journal":{"name":"International Journal of Computer Networks and Applications","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136152369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.22247/ijcna/2023/223424
Poonam T. Agarkar, Manish D. Chawhan, Rahul N. Nawkhare, Daljeet Singh, Narendra P. Giradkar, Prashant R. Patil
– AODV is one of the widely used routing schemes in WSN and MANET due to its on-demand characteristics and low overhead. The excessive flooding at the time of route discovery consumes lots of node energy. The network performance deteriorates due to the unconstrained and blind flooding of route request (RREQ) packets. The excessive flooding mechanism accounts for multiple reception of RREQ packets at nodes. It causes unwanted path loops, and packet collisions thus exhausting the node batteries. The restricted flooding-based route discovery (RFBRD) mechanism introduced in this paper adopts two different strategies for receiving first and subsequent RREQ packets before they are forwarded. On reception of the first RREQ at an intermediate node, the RREQ is forwarded/restricted based on node densities evaluated for the neighbourhood as well as the network. Four regions and five probabilities are considered based on node densities in the neighbourhood and the network. The mobile nodes lying in the low-density region are allowed to transmit the RREQ packets with higher probability as compared to other nodes present in high-density regions when the RREQ is received for the first time. For subsequent RREQ packets at an intermediate node, the RREQ is forwarded/restricted based on energy ratios and is allowed to forward the RREQ packets, if the node has sufficient residual energy concerning neighbourhood and network energies. Simulation analysis showed enhanced and improved performance in terms of end-to-end delay, and network residual energy concerning traditional AODV.
{"title":"An Efficient Restricted Flooding Based Route Discovery (RFBRD) Scheme for AODV Routing","authors":"Poonam T. Agarkar, Manish D. Chawhan, Rahul N. Nawkhare, Daljeet Singh, Narendra P. Giradkar, Prashant R. Patil","doi":"10.22247/ijcna/2023/223424","DOIUrl":"https://doi.org/10.22247/ijcna/2023/223424","url":null,"abstract":"– AODV is one of the widely used routing schemes in WSN and MANET due to its on-demand characteristics and low overhead. The excessive flooding at the time of route discovery consumes lots of node energy. The network performance deteriorates due to the unconstrained and blind flooding of route request (RREQ) packets. The excessive flooding mechanism accounts for multiple reception of RREQ packets at nodes. It causes unwanted path loops, and packet collisions thus exhausting the node batteries. The restricted flooding-based route discovery (RFBRD) mechanism introduced in this paper adopts two different strategies for receiving first and subsequent RREQ packets before they are forwarded. On reception of the first RREQ at an intermediate node, the RREQ is forwarded/restricted based on node densities evaluated for the neighbourhood as well as the network. Four regions and five probabilities are considered based on node densities in the neighbourhood and the network. The mobile nodes lying in the low-density region are allowed to transmit the RREQ packets with higher probability as compared to other nodes present in high-density regions when the RREQ is received for the first time. For subsequent RREQ packets at an intermediate node, the RREQ is forwarded/restricted based on energy ratios and is allowed to forward the RREQ packets, if the node has sufficient residual energy concerning neighbourhood and network energies. Simulation analysis showed enhanced and improved performance in terms of end-to-end delay, and network residual energy concerning traditional AODV.","PeriodicalId":36485,"journal":{"name":"International Journal of Computer Networks and Applications","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136129433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.22247/ijcna/2023/223430
M. Kayalvizhi, S. Geetha
– Vehicular Ad Hoc Networks (VANETs) have gained prominence in vehicular communication due to their potential to enhance road safety, traffic efficiency, and infotainment services. However, the evolution of Stochastic VANETs (SVANETs) has introduced a layer of uncertainty, where vehicular interactions are influenced by dynamic factors such as varying traffic conditions, changing communication environments, and unpredictable link qualities. Routing within SVANETs presents distinct challenges stemming from the stochastic nature of the environment. Traditional routing protocols struggle to maintain reliable connections amidst fluctuating link conditions, leading to increased latency, dropped packets, and inefficient route utilization. The novel “Decisiveness PSO-Based Gaussian AOMDV (DPSO-GAOMDV) Routing Protocol” is introduced to address these challenges. This innovative protocol combines the predictive power of Gaussian-Anticipatory On-Demand Distance Vector (GAOMDV) routing with the dynamic adaptability of Particle Swarm Optimization (PSO). GAOMDV’s ability to anticipate link stability using Gaussian distribution is integrated with DPSO’s agility in optimizing routing decisions. The simulation phase of the study evaluates the DPSO-GAOMDV protocol under various stochastic vehicular scenarios. The protocol’s performance is thoroughly analyzed by emulating real-world traffic conditions and communication dynamics. The simulation results underscore the protocol’s efficacy in reducing route maintenance overhead, improved packet delivery ratios, and enhanced network stability. The predictive insights and dynamic optimization mechanisms showcase its potential to drive innovative, resilient and efficient routing strategies in the face of stochastic vehicular conditions.
{"title":"Decisiveness PSO-Based Gaussian AOMDV (DPSO-GAOMDV) Routing Protocol: Smart Routing for Dynamic Traffic Conditions in Stochastic Vehicular Ad Hoc Network","authors":"M. Kayalvizhi, S. Geetha","doi":"10.22247/ijcna/2023/223430","DOIUrl":"https://doi.org/10.22247/ijcna/2023/223430","url":null,"abstract":"– Vehicular Ad Hoc Networks (VANETs) have gained prominence in vehicular communication due to their potential to enhance road safety, traffic efficiency, and infotainment services. However, the evolution of Stochastic VANETs (SVANETs) has introduced a layer of uncertainty, where vehicular interactions are influenced by dynamic factors such as varying traffic conditions, changing communication environments, and unpredictable link qualities. Routing within SVANETs presents distinct challenges stemming from the stochastic nature of the environment. Traditional routing protocols struggle to maintain reliable connections amidst fluctuating link conditions, leading to increased latency, dropped packets, and inefficient route utilization. The novel “Decisiveness PSO-Based Gaussian AOMDV (DPSO-GAOMDV) Routing Protocol” is introduced to address these challenges. This innovative protocol combines the predictive power of Gaussian-Anticipatory On-Demand Distance Vector (GAOMDV) routing with the dynamic adaptability of Particle Swarm Optimization (PSO). GAOMDV’s ability to anticipate link stability using Gaussian distribution is integrated with DPSO’s agility in optimizing routing decisions. The simulation phase of the study evaluates the DPSO-GAOMDV protocol under various stochastic vehicular scenarios. The protocol’s performance is thoroughly analyzed by emulating real-world traffic conditions and communication dynamics. The simulation results underscore the protocol’s efficacy in reducing route maintenance overhead, improved packet delivery ratios, and enhanced network stability. The predictive insights and dynamic optimization mechanisms showcase its potential to drive innovative, resilient and efficient routing strategies in the face of stochastic vehicular conditions.","PeriodicalId":36485,"journal":{"name":"International Journal of Computer Networks and Applications","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136129141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.22247/ijcna/2023/223429
H. Ateeq Ahmed, Dhanaraj Cheelu
– Vehicular Ad hoc Networks (VANETs) face challenges in maintaining communication links due to their large network sizes and rapidly changing topologies. Frequent link disconnections can impact the performance of vehicular applications, which are crucial for Intelligent Transport Systems (ITS). The objective of the research is to develop a dynamic link prediction protocol (NDLP) that can predict when a link is likely to become unavailable. By predicting link disconnections in advance, the protocol aims to reroute data packets through alternative paths to ensure uninterrupted communication. In this paper, a novel dynamic link prediction protocol (NDLP) is proposed to determine the duration of availability of the current path. This protocol predicts the duration of current path availability, aiming to pre-emptively predict connection breakdowns and reroute data packets via alternate paths. The proposed methodology involves the use of Newton's divided difference interpolation to assess the presence of active links to adjacent nodes. This technique employs historical data or real-time measurements to predict the future state of links. The primary focus is on predicting link disconnections before they occur and pre-emptively rerouting packets using an alternative path. The estimation of the time of link breakage and the ability to select the best route before the link breakage is analysed. Simulation results have proven the effectiveness of NDLP protocol with its counterpart protocols in terms of delay, packet delivery ratio and throughput.
{"title":"A Novel Dynamic Link Prediction Protocol for Frequent Link Disconnections in Vehicular Ad Hoc Networks","authors":"H. Ateeq Ahmed, Dhanaraj Cheelu","doi":"10.22247/ijcna/2023/223429","DOIUrl":"https://doi.org/10.22247/ijcna/2023/223429","url":null,"abstract":"– Vehicular Ad hoc Networks (VANETs) face challenges in maintaining communication links due to their large network sizes and rapidly changing topologies. Frequent link disconnections can impact the performance of vehicular applications, which are crucial for Intelligent Transport Systems (ITS). The objective of the research is to develop a dynamic link prediction protocol (NDLP) that can predict when a link is likely to become unavailable. By predicting link disconnections in advance, the protocol aims to reroute data packets through alternative paths to ensure uninterrupted communication. In this paper, a novel dynamic link prediction protocol (NDLP) is proposed to determine the duration of availability of the current path. This protocol predicts the duration of current path availability, aiming to pre-emptively predict connection breakdowns and reroute data packets via alternate paths. The proposed methodology involves the use of Newton's divided difference interpolation to assess the presence of active links to adjacent nodes. This technique employs historical data or real-time measurements to predict the future state of links. The primary focus is on predicting link disconnections before they occur and pre-emptively rerouting packets using an alternative path. The estimation of the time of link breakage and the ability to select the best route before the link breakage is analysed. Simulation results have proven the effectiveness of NDLP protocol with its counterpart protocols in terms of delay, packet delivery ratio and throughput.","PeriodicalId":36485,"journal":{"name":"International Journal of Computer Networks and Applications","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136129471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-31DOI: 10.22247/ijcna/2023/223314
Monika Pahuja, Dinesh Kumar
– In recent decades, the world's largest sector has undergone enormous transformations with the emergence of a new platform, denoted as 'healthcare' and based on the IoT (Internet of Things). Numerous hospital administrators are increasing their investment in converting existing activities to maximize the benefits of IoT, creating the foundation for the wireless healthcare system through a vast network of sensing devices and equipment. The wireless sensor system comprises minimal sensor equipment with limited processing capacity. IoT-based WSN systems are beneficial for smart healthcare. Healthcare has become one of the WSN (wireless sensor network)-based IoT application fields that have attracted much more attention from corporate, government sources, etc in the past few years. In the medical industry, the growth of IoT enhances patient safety, employee engagement, and productivity improvement for the overall system. Healthcare-based IoT wireless sensor systems for patients have several benefits: tracking and alerting, patient information management, remotely assisting the healthcare system, etc. In the context of wireless sensor healthcare systems utilizing Internet of Things (IoT) technology, the infrastructure encompasses a range of essential elements. These include sensing devices responsible for data collection, communication protocols facilitating data transmission, data storage devices for retaining collected information, and subscribers who access and utilize the acquired data. The IoT framework in healthcare systems comprises three fundamental components: the publisher, broker, and subscriber. The publisher is known for sensors and wearable devices. Brokers process the sensing data and then make it available to subscribers. The three components are connected via a wireless connection like Bluetooth, Wi-Fi, etc. The routing protocols are used for wireless connections in healthcare based on IoT systems. There are various categories of routing protocols used in the wireless healthcare network. This paper discusses various routing protocols with types, and comparison tables of routing protocols are depicted. A comprehensive review of healthcare-based IoT applications and an advanced medical care system benefits doctors and patients. The experts monitor ECG (electrocardiography), blood pressure, temperature, etc. The comparison of several methods based on throughput, E2D (end-to-end) delay, consumption, and data packet delay ratio (PDR) is depicted in this paper for a better understanding of the existing systems.
{"title":"Taxonomy of Various Routing Protocols of IoT-Based on Wireless Sensor Networks for Healthcare: Review","authors":"Monika Pahuja, Dinesh Kumar","doi":"10.22247/ijcna/2023/223314","DOIUrl":"https://doi.org/10.22247/ijcna/2023/223314","url":null,"abstract":"– In recent decades, the world's largest sector has undergone enormous transformations with the emergence of a new platform, denoted as 'healthcare' and based on the IoT (Internet of Things). Numerous hospital administrators are increasing their investment in converting existing activities to maximize the benefits of IoT, creating the foundation for the wireless healthcare system through a vast network of sensing devices and equipment. The wireless sensor system comprises minimal sensor equipment with limited processing capacity. IoT-based WSN systems are beneficial for smart healthcare. Healthcare has become one of the WSN (wireless sensor network)-based IoT application fields that have attracted much more attention from corporate, government sources, etc in the past few years. In the medical industry, the growth of IoT enhances patient safety, employee engagement, and productivity improvement for the overall system. Healthcare-based IoT wireless sensor systems for patients have several benefits: tracking and alerting, patient information management, remotely assisting the healthcare system, etc. In the context of wireless sensor healthcare systems utilizing Internet of Things (IoT) technology, the infrastructure encompasses a range of essential elements. These include sensing devices responsible for data collection, communication protocols facilitating data transmission, data storage devices for retaining collected information, and subscribers who access and utilize the acquired data. The IoT framework in healthcare systems comprises three fundamental components: the publisher, broker, and subscriber. The publisher is known for sensors and wearable devices. Brokers process the sensing data and then make it available to subscribers. The three components are connected via a wireless connection like Bluetooth, Wi-Fi, etc. The routing protocols are used for wireless connections in healthcare based on IoT systems. There are various categories of routing protocols used in the wireless healthcare network. This paper discusses various routing protocols with types, and comparison tables of routing protocols are depicted. A comprehensive review of healthcare-based IoT applications and an advanced medical care system benefits doctors and patients. The experts monitor ECG (electrocardiography), blood pressure, temperature, etc. The comparison of several methods based on throughput, E2D (end-to-end) delay, consumption, and data packet delay ratio (PDR) is depicted in this paper for a better understanding of the existing systems.","PeriodicalId":36485,"journal":{"name":"International Journal of Computer Networks and Applications","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48519748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-31DOI: 10.22247/ijcna/2023/223312
P. Sakthi, Shunmuga Sundaram, K. Vijayan
– Recent technological developments include wireless sensor networks in modern and intelligent environments. Finding the localization of the sensor node is a problem in the research community field. Localization on a two-dimensional plane, a key focus in WSNs, is to maximize the lifespan and overall performance of sensor nodes by minimizing their energy consumption. The compiled data that base stations receive from packets.in wireless sensor networks can be used to make decisions with the help of localization. A cost-effective method of solving the problem is not the Internet of Things with GPR tracking sensor zones. There are several approaches to locating wireless sensor networks with unclear sensor locations. The main challenge lies in accurately determining the location of the base station's sensor node with a minor localization error during wireless communication. The proposed method, Distributed clustering Distance Algorithm (DCDA) using machine learning, considers the distance estimation error, location in accuracy, and fault tolerance issue with WSNs. According to the findings, the average localization error is 11% and 11.3%, respectively. For anchor nodes 20-80 and 200-450. As a result, when compared to contemporary methods of localization with centroid weighted algorithm (LCWA), Distance vector hop algorithm (DV-Hop), Coefficient for reparation algorithm (CRA), and Weighted Distributed Hyperbolic algorithm (WDHA) methods, the demonstrated Distributed clustering Distance Algorithm (DCDA) gives greater accuracy. According to the experimental results, the suggested algorithm significantly improves the number of alive nodes compared to the LBCA and G. Gupta FT algorithms. Specifically, the proposed algorithm achieves a remarkable 96% increase in active and functional nodes within the wireless sensor network.
{"title":"Prediction Model to Analyze Source Node Localization Using Machine Learning and Fault-Tolerant in Wireless Sensor Networks","authors":"P. Sakthi, Shunmuga Sundaram, K. Vijayan","doi":"10.22247/ijcna/2023/223312","DOIUrl":"https://doi.org/10.22247/ijcna/2023/223312","url":null,"abstract":"– Recent technological developments include wireless sensor networks in modern and intelligent environments. Finding the localization of the sensor node is a problem in the research community field. Localization on a two-dimensional plane, a key focus in WSNs, is to maximize the lifespan and overall performance of sensor nodes by minimizing their energy consumption. The compiled data that base stations receive from packets.in wireless sensor networks can be used to make decisions with the help of localization. A cost-effective method of solving the problem is not the Internet of Things with GPR tracking sensor zones. There are several approaches to locating wireless sensor networks with unclear sensor locations. The main challenge lies in accurately determining the location of the base station's sensor node with a minor localization error during wireless communication. The proposed method, Distributed clustering Distance Algorithm (DCDA) using machine learning, considers the distance estimation error, location in accuracy, and fault tolerance issue with WSNs. According to the findings, the average localization error is 11% and 11.3%, respectively. For anchor nodes 20-80 and 200-450. As a result, when compared to contemporary methods of localization with centroid weighted algorithm (LCWA), Distance vector hop algorithm (DV-Hop), Coefficient for reparation algorithm (CRA), and Weighted Distributed Hyperbolic algorithm (WDHA) methods, the demonstrated Distributed clustering Distance Algorithm (DCDA) gives greater accuracy. According to the experimental results, the suggested algorithm significantly improves the number of alive nodes compared to the LBCA and G. Gupta FT algorithms. Specifically, the proposed algorithm achieves a remarkable 96% increase in active and functional nodes within the wireless sensor network.","PeriodicalId":36485,"journal":{"name":"International Journal of Computer Networks and Applications","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41543233","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-31DOI: 10.22247/ijcna/2023/223316
K. Prabu, P. Sudhakar
– Amid the soaring cyber threats and security breaches, we introduce an automated intrusion detection and prevention model to bolster threat assessment and security data solutions. Our model, utilizing the state-of-the-art Automatic Intrusion Detection System (AIDS) and real-time data analysis, promptly identifies and responds to potential security breaches. It gathers security data from multiple sources, such as network traffic, system logs, user behaviour, and external threat intelligence feeds, enhancing overall cybersecurity defenses. The increasing volume of data sharing and network traffic has raised concerns about cybersecurity. To address this issue, we propose the Automatic Intrusion Detection System (AiDS) is defined as monitoring the network for suspicious activity for managing network traffic. The activities detected are monitored based on the alerts, and the operation centres are analyzed using the appropriate actions to remediate the threat. The Automatic intrusion Detection System and the Intrusion Prevention System (IPS) have been used to prevent and secure network data. By using the technique of Automatic intrusion Detection System (AiDS), the identification of the endpoint protection, which is related to the hunting engine, risk management, incident response mobile security, and access management and by using the technique of Intrusion Prevention System (AiPS) the vulnerability of threat management and the analysis of the data in the network is proposed. The result describes the 97.2% of data in the KDD 99 data set, the accuracy and sensitivity of the data from the network is 92.8%, and the system's formation. The approximate data in the database is 75%. The security services' intrusion and the system's data formation in the digital threat data have been accessed successfully
{"title":"An Automated Intrusion Detection and Prevention Model for Enhanced Network Security and Threat Assessment","authors":"K. Prabu, P. Sudhakar","doi":"10.22247/ijcna/2023/223316","DOIUrl":"https://doi.org/10.22247/ijcna/2023/223316","url":null,"abstract":"– Amid the soaring cyber threats and security breaches, we introduce an automated intrusion detection and prevention model to bolster threat assessment and security data solutions. Our model, utilizing the state-of-the-art Automatic Intrusion Detection System (AIDS) and real-time data analysis, promptly identifies and responds to potential security breaches. It gathers security data from multiple sources, such as network traffic, system logs, user behaviour, and external threat intelligence feeds, enhancing overall cybersecurity defenses. The increasing volume of data sharing and network traffic has raised concerns about cybersecurity. To address this issue, we propose the Automatic Intrusion Detection System (AiDS) is defined as monitoring the network for suspicious activity for managing network traffic. The activities detected are monitored based on the alerts, and the operation centres are analyzed using the appropriate actions to remediate the threat. The Automatic intrusion Detection System and the Intrusion Prevention System (IPS) have been used to prevent and secure network data. By using the technique of Automatic intrusion Detection System (AiDS), the identification of the endpoint protection, which is related to the hunting engine, risk management, incident response mobile security, and access management and by using the technique of Intrusion Prevention System (AiPS) the vulnerability of threat management and the analysis of the data in the network is proposed. The result describes the 97.2% of data in the KDD 99 data set, the accuracy and sensitivity of the data from the network is 92.8%, and the system's formation. The approximate data in the database is 75%. The security services' intrusion and the system's data formation in the digital threat data have been accessed successfully","PeriodicalId":36485,"journal":{"name":"International Journal of Computer Networks and Applications","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47271988","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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