Pub Date : 2022-12-30DOI: 10.22247/ijcna/2022/217700
K. Abdul Basith, T. Shankar
{"title":"Minimalistic Error via Clibat Algorithm for Attack-Defence Model on Wireless Sensor Networks (WSN)","authors":"K. Abdul Basith, T. Shankar","doi":"10.22247/ijcna/2022/217700","DOIUrl":"https://doi.org/10.22247/ijcna/2022/217700","url":null,"abstract":"","PeriodicalId":36485,"journal":{"name":"International Journal of Computer Networks and Applications","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43563715","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 : 2022-12-30DOI: 10.22247/ijcna/2022/217704
V. Maruthi Prasad, B. Bharathi
{"title":"A Novel Trust Negotiation Protocol for Analysing and Approving IoT Edge Computing Devices Using Machine Learning Algorithm","authors":"V. Maruthi Prasad, B. Bharathi","doi":"10.22247/ijcna/2022/217704","DOIUrl":"https://doi.org/10.22247/ijcna/2022/217704","url":null,"abstract":"","PeriodicalId":36485,"journal":{"name":"International Journal of Computer Networks and Applications","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45024389","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}
– Over the clustered wireless network systems, development in wireless technology has had a more substantial influence. Entities need to communicate with one another in order to create a sustainable ecosystem. Clustering methods help connect and organise the sensor nodes by load balancing and extending the network lifetime. Only now, various techniques have been developed for solving routing problems but have yet to focus on routing reliability with avoidance of data collision in real scenarios. This research is carried out for the reliability of routing by multi-objective optimization in static and dynamic environments through agent-based analysis with avoidance of data collision and depletion of energy. This study introduces a fuzzy-based multipath clustering technique that exhibits both static and dynamic clustering formation properties. The designated region starts the clustering process once the sensor nodes are ready to begin the data transmission procedure. The proposed technique works in two steps: a) fuzzy cluster head selection; and b) multi-objective agent-based multipath routing protocols for shortest route path discovery. The enhancement made in cluster creation and selection is the critical feature. A well-organized sensor ecosystem has lessened the negative impacts of network collision and energy exhaustion. The packet delivery ratio, communication overhead, and energy consumption are the performance metrics examined when simulating the specified protocol using the computer language NS2. The devised fuzzy-based multi-path routing (FC-MRP) clustering technique outperforms the AODV (Ad-hoc on-demand distance vector routing) protocol, according to the results. The average percentage of improvement concerning PDR, Throughput, end-to-end latency, Overhead, Energy utilised, Energy efficiency, Network lifetime, and PLR is found to be +2.53, +2.23, -18.58, -22.46, -17.95, +23.00, +4.11, -18.09 respectively.
{"title":"A Novel Agent-Based Multipath Routing Protocol to Extend Lifetime and Enhancing Reliability of Clustered Wireless Sensor Networks","authors":"Binaya Kumar Patra, Sarojananda Mishra, Sanjay Kumar Patra","doi":"10.22247/ijcna/2022/217702","DOIUrl":"https://doi.org/10.22247/ijcna/2022/217702","url":null,"abstract":"– Over the clustered wireless network systems, development in wireless technology has had a more substantial influence. Entities need to communicate with one another in order to create a sustainable ecosystem. Clustering methods help connect and organise the sensor nodes by load balancing and extending the network lifetime. Only now, various techniques have been developed for solving routing problems but have yet to focus on routing reliability with avoidance of data collision in real scenarios. This research is carried out for the reliability of routing by multi-objective optimization in static and dynamic environments through agent-based analysis with avoidance of data collision and depletion of energy. This study introduces a fuzzy-based multipath clustering technique that exhibits both static and dynamic clustering formation properties. The designated region starts the clustering process once the sensor nodes are ready to begin the data transmission procedure. The proposed technique works in two steps: a) fuzzy cluster head selection; and b) multi-objective agent-based multipath routing protocols for shortest route path discovery. The enhancement made in cluster creation and selection is the critical feature. A well-organized sensor ecosystem has lessened the negative impacts of network collision and energy exhaustion. The packet delivery ratio, communication overhead, and energy consumption are the performance metrics examined when simulating the specified protocol using the computer language NS2. The devised fuzzy-based multi-path routing (FC-MRP) clustering technique outperforms the AODV (Ad-hoc on-demand distance vector routing) protocol, according to the results. The average percentage of improvement concerning PDR, Throughput, end-to-end latency, Overhead, Energy utilised, Energy efficiency, Network lifetime, and PLR is found to be +2.53, +2.23, -18.58, -22.46, -17.95, +23.00, +4.11, -18.09 respectively.","PeriodicalId":36485,"journal":{"name":"International Journal of Computer Networks and Applications","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45652730","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 : 2022-10-01DOI: 10.22247/ijcna/2022/215916
R. Mangalagowri, R. Venkataraman
– Cloud computing demonstrates excellent power to yield cost-efficient, easily manageable, flexible, and charged resources whenever required, over the Internet. Cloud computing, can make the potential of the hardware resources to increase huge through best and shared usage. The growth of the cloud computing concept has also resulted in security challenges, considering that there are resource sharing, and it is moderated with the help of a Hypervisor which can be the target of malicious guest Virtual Machines (VM) and remote intruders. The hypervisor itself is attacked by hackers. Since the hypervisor is attacked, the VMs under the hypervisor is also attacked by the attackers. Hence, to prevent the problems stated above, in this study, Enhanced Particle Swarm Optimization (EPSO) with Hypervisor Attack Detection using Advanced Encryption Standard (HADAES) algorithm is introduced with the intent of improving the cloud performance on the whole. This work contains important phases such as system model, optimal resource allocation, and hypervisor attack detection. The system model contains the data center model, migration request model, and energy model over the cloud computing environment. Resource allocation is done by using the EPSO algorithm which is used to select the optimal resources using local and global best values. Hypervisor attack detection is done by using HADAES algorithm. It is helpful to determine the hypervisor and VM attackers also it is focused to provide higher security for cloud data. From the test result, it is concluded that the proposed algorithm yields superior performance concerning improved reliability, throughput, and reduced energy consumption, cost complexity, and time complexity than the existing methods. The effectiveness of IDS depends on its capacity to strike a balance between the number of defenses and the number of false positives or detecting errors. algorithm. The best and the mean costs of the population members and the execution time when applying the EPSO method. In this study, an innovative time-adaptive PSO is proposed based on the movement patterns named the movement pattern adaptation PSO (EPSO).
{"title":"Hypervisor Attack Detection Using Advanced Encryption Standard (HADAES) Algorithm on Cloud Data","authors":"R. Mangalagowri, R. Venkataraman","doi":"10.22247/ijcna/2022/215916","DOIUrl":"https://doi.org/10.22247/ijcna/2022/215916","url":null,"abstract":"– Cloud computing demonstrates excellent power to yield cost-efficient, easily manageable, flexible, and charged resources whenever required, over the Internet. Cloud computing, can make the potential of the hardware resources to increase huge through best and shared usage. The growth of the cloud computing concept has also resulted in security challenges, considering that there are resource sharing, and it is moderated with the help of a Hypervisor which can be the target of malicious guest Virtual Machines (VM) and remote intruders. The hypervisor itself is attacked by hackers. Since the hypervisor is attacked, the VMs under the hypervisor is also attacked by the attackers. Hence, to prevent the problems stated above, in this study, Enhanced Particle Swarm Optimization (EPSO) with Hypervisor Attack Detection using Advanced Encryption Standard (HADAES) algorithm is introduced with the intent of improving the cloud performance on the whole. This work contains important phases such as system model, optimal resource allocation, and hypervisor attack detection. The system model contains the data center model, migration request model, and energy model over the cloud computing environment. Resource allocation is done by using the EPSO algorithm which is used to select the optimal resources using local and global best values. Hypervisor attack detection is done by using HADAES algorithm. It is helpful to determine the hypervisor and VM attackers also it is focused to provide higher security for cloud data. From the test result, it is concluded that the proposed algorithm yields superior performance concerning improved reliability, throughput, and reduced energy consumption, cost complexity, and time complexity than the existing methods. The effectiveness of IDS depends on its capacity to strike a balance between the number of defenses and the number of false positives or detecting errors. algorithm. The best and the mean costs of the population members and the execution time when applying the EPSO method. In this study, an innovative time-adaptive PSO is proposed based on the movement patterns named the movement pattern adaptation PSO (EPSO).","PeriodicalId":36485,"journal":{"name":"International Journal of Computer Networks and Applications","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47496294","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 : 2022-10-01DOI: 10.22247/ijcna/2022/215922
S. Preema, M. Thilagu
– Rapid technological development in the wireless communication sector has improved mobile ad hoc networks (MANETs) to serve a variety of domains, such as military activities, emergency operations, civilian settings, and disaster management. Self-organizing mobile nodes in MANET work together to create a dynamic network architecture to make connections. Before reaching its destination node in a MANET, data must pass through several intermediate nodes. For the creation and maintenance of routes, local link connection is crucial. This paper proposes the Deft Particle Swarm Optimization-based Routing Protocol (DPSORP) to reduce delay, which minimizes energy consumption. DPSORP gives precedence for local and global optimal routes. Before using a route for data transmission, DPSORP assesses its quality using two distinct kinds of rules. DPSORP uses a multi-path for data transmission rather than relying on a single path. Using the NS3 simulator and common network performance metrics and parameters, DPSORP is evaluated. The findings demonstrate unequivocally that the proposed routing protocol, DPSORP, outperforms existing routing protocols in terms of reducing delay and energy consumption .
{"title":"Deft Particle Swarm Optimization-Based Routing Protocol (DPSORP) for Energy Consumption Minimization in Mobile Ad-Hoc Network","authors":"S. Preema, M. Thilagu","doi":"10.22247/ijcna/2022/215922","DOIUrl":"https://doi.org/10.22247/ijcna/2022/215922","url":null,"abstract":"– Rapid technological development in the wireless communication sector has improved mobile ad hoc networks (MANETs) to serve a variety of domains, such as military activities, emergency operations, civilian settings, and disaster management. Self-organizing mobile nodes in MANET work together to create a dynamic network architecture to make connections. Before reaching its destination node in a MANET, data must pass through several intermediate nodes. For the creation and maintenance of routes, local link connection is crucial. This paper proposes the Deft Particle Swarm Optimization-based Routing Protocol (DPSORP) to reduce delay, which minimizes energy consumption. DPSORP gives precedence for local and global optimal routes. Before using a route for data transmission, DPSORP assesses its quality using two distinct kinds of rules. DPSORP uses a multi-path for data transmission rather than relying on a single path. Using the NS3 simulator and common network performance metrics and parameters, DPSORP is evaluated. The findings demonstrate unequivocally that the proposed routing protocol, DPSORP, outperforms existing routing protocols in terms of reducing delay and energy consumption .","PeriodicalId":36485,"journal":{"name":"International Journal of Computer Networks and Applications","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43560344","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 : 2022-10-01DOI: 10.22247/ijcna/2022/215913
G. Sripriya, T. Santha
– The Mobile Ad Hoc Network (MANET), with its high dynamics, vulnerable links, and total decentralization, poses significant security issues. The MAODV (Multicast Ad-hoc On-Demand Distance Vector) protocol, a crucial routing protocol used in ad-hoc networks, falls short of security standards and is susceptible to assaults brought on by the hostile environment. The harmful nodal points can readily damage Mobile Ad-Hoc Networks (MANETs), which are made up of numerous wireless networks. The hardest task will be sharing bandwidth between wireless nodes while maintaining Quality of Service (QoS) for routing. To identify the potentially harmful nodes, trust-based routing strategies must be developed. The proposed effort entails constructing trust-based QoS routing with a secure mix of social and QoS trust. The suggested design's first method begins with the eradication of dead nodes, which leads to a packet collecting error. These dead nodes may also cause difficulty in the route analysis when employing trust mechanisms for communication. The suggested approach will perform better in terms of forwarding node selection based on packet behavioral characteristics. The forward node will be chosen depending on several parameters, including the residual energy between nodal locations, channel quality between nodes, and connection quality. The proposed method is simulated using the Network Simulator tool (NS2), and the simulation results show that the proposed approach is accurate and efficient in identifying and detaching problematic nodes at regular intervals.
–移动自组织网络（MANET）具有高动态性、易受攻击的链路和完全的去中心化，带来了重大的安全问题。MAODV（Multicast Ad-hoc On Demand Distance Vector，多播自组织点播距离矢量）协议是自组织网络中使用的一种关键路由协议，它不符合安全标准，容易受到敌对环境的攻击。有害的节点很容易破坏由众多无线网络组成的移动自组织网络。最困难的任务将是在无线节点之间共享带宽，同时保持路由的服务质量（QoS）。为了识别潜在的有害节点，必须制定基于信任的路由策略。所提出的努力需要构建具有社会信任和QoS信任的安全组合的基于信任的QoS路由。建议设计的第一种方法从消除死节点开始，这会导致数据包收集错误。当采用信任机制进行通信时，这些死节点也可能导致路由分析困难。所建议的方法在基于分组行为特征的转发节点选择方面将表现得更好。将根据几个参数来选择前向节点，包括节点位置之间的剩余能量、节点之间的信道质量和连接质量。使用网络模拟器工具（NS2）对所提出的方法进行了仿真，仿真结果表明，该方法在定期识别和分离有问题的节点方面是准确有效的。
{"title":"A Trust-Based Design for Secure and Quality of Service Routing in Mobile Ad Hoc Networks","authors":"G. Sripriya, T. Santha","doi":"10.22247/ijcna/2022/215913","DOIUrl":"https://doi.org/10.22247/ijcna/2022/215913","url":null,"abstract":"– The Mobile Ad Hoc Network (MANET), with its high dynamics, vulnerable links, and total decentralization, poses significant security issues. The MAODV (Multicast Ad-hoc On-Demand Distance Vector) protocol, a crucial routing protocol used in ad-hoc networks, falls short of security standards and is susceptible to assaults brought on by the hostile environment. The harmful nodal points can readily damage Mobile Ad-Hoc Networks (MANETs), which are made up of numerous wireless networks. The hardest task will be sharing bandwidth between wireless nodes while maintaining Quality of Service (QoS) for routing. To identify the potentially harmful nodes, trust-based routing strategies must be developed. The proposed effort entails constructing trust-based QoS routing with a secure mix of social and QoS trust. The suggested design's first method begins with the eradication of dead nodes, which leads to a packet collecting error. These dead nodes may also cause difficulty in the route analysis when employing trust mechanisms for communication. The suggested approach will perform better in terms of forwarding node selection based on packet behavioral characteristics. The forward node will be chosen depending on several parameters, including the residual energy between nodal locations, channel quality between nodes, and connection quality. The proposed method is simulated using the Network Simulator tool (NS2), and the simulation results show that the proposed approach is accurate and efficient in identifying and detaching problematic nodes at regular intervals.","PeriodicalId":36485,"journal":{"name":"International Journal of Computer Networks and Applications","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44729969","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 : 2022-10-01DOI: 10.22247/ijcna/2022/215920
Carmen Beatriz Espinosa Garrido, Sandra Sendra Compte, Luis Rosales Roldan, Alejandra Aldrette Malacara
– The Internet of Things is a new paradigm that facilitates collecting business or personal data through smart devices with Internet connections. IoT devices are heterogeneous and have a limited computational capacity which represents a challenge for protecting data against cyber-attacks. This article surveys communication protocols, cybersecurity attacks and intrusion detection systems (IDSs). This study identifies the IoT protocols used for data transmission, and cybersecurity challenges and then presents a comparative analysis of IDSs. Next, the IoT cybersecurity framework, IoTCyFra, is surveyed by cybersecurity specialists. IoTCyFra is a validated IoT cybersecurity framework with an organizational structure that safeguards data and detects cybersecurity threats in an IoT infrastructure. It also explores how an IDS protects against cyberattacks through an IoT-controlled environment. Finally, the results and conclusions are reported.
{"title":"Survey and testing of the IoT Cybersecurity Framework Using Intrusion Detection Systems","authors":"Carmen Beatriz Espinosa Garrido, Sandra Sendra Compte, Luis Rosales Roldan, Alejandra Aldrette Malacara","doi":"10.22247/ijcna/2022/215920","DOIUrl":"https://doi.org/10.22247/ijcna/2022/215920","url":null,"abstract":"– The Internet of Things is a new paradigm that facilitates collecting business or personal data through smart devices with Internet connections. IoT devices are heterogeneous and have a limited computational capacity which represents a challenge for protecting data against cyber-attacks. This article surveys communication protocols, cybersecurity attacks and intrusion detection systems (IDSs). This study identifies the IoT protocols used for data transmission, and cybersecurity challenges and then presents a comparative analysis of IDSs. Next, the IoT cybersecurity framework, IoTCyFra, is surveyed by cybersecurity specialists. IoTCyFra is a validated IoT cybersecurity framework with an organizational structure that safeguards data and detects cybersecurity threats in an IoT infrastructure. It also explores how an IDS protects against cyberattacks through an IoT-controlled environment. Finally, the results and conclusions are reported.","PeriodicalId":36485,"journal":{"name":"International Journal of Computer Networks and Applications","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46543574","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 : 2022-10-01DOI: 10.22247/ijcna/2022/215921
Pooja Mishra, Sandeep Malik
– Internet of Medical Things (IoMT) are networks which are targeted towards design of healthcare communication interfaces with low latency and high security. In order to design such interfaces, efficient models for data encryption, hashing, privacy, and quality of service (QoS) awareness are needed. A wide variety of standard medical interfaces are proposed by researchers, which assist in reducing network redundancies for high-throughput and low latency communications. These interfaces also implement security models that ensure data encryption & privacy. But due to incorporation of encryption methods, QoS performance of the IoMT devices reduces, which limits their real-time usability for in-patient monitoring & treatment. In order to improve IoMT QoS while maintaining high security, this text proposes design of QSIH, which is a QoS-aware sidechain model that can be used for securing IoMT networks. The proposed model describes design of a blockchain-based data storage & communication interface, which is capable of removing a wide variety of network attacks. The delay needed for communication in any blockchain-based interface increases exponentially w.r.t. number of blocks added to the system. In order to reduce this delay, a novel machine learning model based on Genetic Algorithm optimization is proposed. The proposed model splits the main blockchain into multiple shards in a QoS-aware manner, thereby ensuring low delay, and high communication throughput. The shards (or sidechains) are managed using an interactive Q-Learning (IQL), which is able to expand or contract these chains depending upon network’s QoS performance. Sidechains which are unused for large periods of time are combined together, and archived for future reference. The archived sidechains are formed from main blockchain, and are merged with other sidechains depending upon archival requirements of the network. Due to such a dynamic side chaining model, the proposed QSIH model is capable of reducing network communication delay by 18%, increase throughput by 14%, reduce storage cost by 5%, while maintaining high level of security & privacy in the network. The model was tested under different IoMT scenarios, and it was observed that it showcased consistent performance across different network emulations.
{"title":"QSIH: Design of a Novel QoS-Aware Sidechain- Based IoT Network Design for Secure Healthcare Deployments","authors":"Pooja Mishra, Sandeep Malik","doi":"10.22247/ijcna/2022/215921","DOIUrl":"https://doi.org/10.22247/ijcna/2022/215921","url":null,"abstract":"– Internet of Medical Things (IoMT) are networks which are targeted towards design of healthcare communication interfaces with low latency and high security. In order to design such interfaces, efficient models for data encryption, hashing, privacy, and quality of service (QoS) awareness are needed. A wide variety of standard medical interfaces are proposed by researchers, which assist in reducing network redundancies for high-throughput and low latency communications. These interfaces also implement security models that ensure data encryption & privacy. But due to incorporation of encryption methods, QoS performance of the IoMT devices reduces, which limits their real-time usability for in-patient monitoring & treatment. In order to improve IoMT QoS while maintaining high security, this text proposes design of QSIH, which is a QoS-aware sidechain model that can be used for securing IoMT networks. The proposed model describes design of a blockchain-based data storage & communication interface, which is capable of removing a wide variety of network attacks. The delay needed for communication in any blockchain-based interface increases exponentially w.r.t. number of blocks added to the system. In order to reduce this delay, a novel machine learning model based on Genetic Algorithm optimization is proposed. The proposed model splits the main blockchain into multiple shards in a QoS-aware manner, thereby ensuring low delay, and high communication throughput. The shards (or sidechains) are managed using an interactive Q-Learning (IQL), which is able to expand or contract these chains depending upon network’s QoS performance. Sidechains which are unused for large periods of time are combined together, and archived for future reference. The archived sidechains are formed from main blockchain, and are merged with other sidechains depending upon archival requirements of the network. Due to such a dynamic side chaining model, the proposed QSIH model is capable of reducing network communication delay by 18%, increase throughput by 14%, reduce storage cost by 5%, while maintaining high level of security & privacy in the network. The model was tested under different IoMT scenarios, and it was observed that it showcased consistent performance across different network emulations.","PeriodicalId":36485,"journal":{"name":"International Journal of Computer Networks and Applications","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48831772","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 : 2022-10-01DOI: 10.22247/ijcna/2022/215917
V. Sridhar, S. Roslin
– The rising wireless service constraints and user compactness have to lead the progress of 6G communication in the modern days. The benefit of 6G over the presented technologies is a huge support for mixed applications and mobility maintenance. Device to Device (D2D) data transmission in 6G has great attention since it gives a better data delivery rate (DDR). Recently, several methods were established for D2D data transmission. However, energy consumption was not considered to improve the network throughput. To handle such problems, an artificial intelligence technique called Deep Neural Regressive Tangent Transfer Classifier (DNRTTC) model is introduced in this research for D2D data transmission in a 6G system. The designed method includes several layers to attain energy-efficient D2D data transmission. The primary layer is the input layer and it includes several mobile nodes as input. Nodes are transmitted to the hidden layer one. For each node, energy, received signal strength, and connection speed of each mobile node is calculated. Then the similarity analysis is done in the following layer where each node is analyzed with its threshold value. The result is sent to the output layer where the better resource mobile nodes are identified by using the activation function. This leads to attaining energy-efficient D2D data transmission in 6G. Results illustrate that the DNRTTC outperformed compared to conventional methods with better energy efficiency, packet delivery ratio, throughput.
-不断增加的无线服务限制和用户紧凑性必须引领现代6G通信的发展。6G相对于现有技术的优势是对混合应用程序和移动性维护的巨大支持。6G中的设备到设备(D2D)数据传输备受关注，因为它提供了更好的数据传输速率(DDR)。近年来，建立了几种D2D数据传输方法。然而，没有考虑能源消耗来提高网络吞吐量。为了解决这些问题，本研究引入了一种名为深度神经回归切线传输分类器(Deep Neural Regressive Tangent Transfer Classifier, DNRTTC)模型的人工智能技术，用于6G系统中的D2D数据传输。设计的方法包括多层，以实现节能的D2D数据传输。最主要的一层是输入层，它包括几个移动节点作为输入。节点被传输到隐藏层。对于每个节点，计算每个移动节点的能量、接收信号强度和连接速度。然后在下一层进行相似性分析，其中对每个节点进行阈值分析。结果被发送到输出层，在输出层中使用激活函数识别更好的资源移动节点。这可以在6G中实现节能的D2D数据传输。结果表明，与传统方法相比，DNRTTC具有更好的能效、数据包传输率和吞吐量。
{"title":"Energy Efficient Device to Device Data Transmission Based on Deep Artificial Learning in 6G Networks","authors":"V. Sridhar, S. Roslin","doi":"10.22247/ijcna/2022/215917","DOIUrl":"https://doi.org/10.22247/ijcna/2022/215917","url":null,"abstract":"– The rising wireless service constraints and user compactness have to lead the progress of 6G communication in the modern days. The benefit of 6G over the presented technologies is a huge support for mixed applications and mobility maintenance. Device to Device (D2D) data transmission in 6G has great attention since it gives a better data delivery rate (DDR). Recently, several methods were established for D2D data transmission. However, energy consumption was not considered to improve the network throughput. To handle such problems, an artificial intelligence technique called Deep Neural Regressive Tangent Transfer Classifier (DNRTTC) model is introduced in this research for D2D data transmission in a 6G system. The designed method includes several layers to attain energy-efficient D2D data transmission. The primary layer is the input layer and it includes several mobile nodes as input. Nodes are transmitted to the hidden layer one. For each node, energy, received signal strength, and connection speed of each mobile node is calculated. Then the similarity analysis is done in the following layer where each node is analyzed with its threshold value. The result is sent to the output layer where the better resource mobile nodes are identified by using the activation function. This leads to attaining energy-efficient D2D data transmission in 6G. Results illustrate that the DNRTTC outperformed compared to conventional methods with better energy efficiency, packet delivery ratio, throughput.","PeriodicalId":36485,"journal":{"name":"International Journal of Computer Networks and Applications","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44378330","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 : 2022-10-01DOI: 10.22247/ijcna/2022/215919
V. Veerakumaran, A. Rajini
– Mobile Wireless Sensor Network (MWSN) is a dispersed network having autonomous sensor nodes which monitors physical occurrences or environmental variables in real-time. Most MWSNs have limited energy, so energy efficiency is critical. A node’s data will be routed by one of two standard methods: single-long-hop or short-multi-hop routing paths. The quantity of energy required to deliver a packet grows directly proportional to the packet’s travel distance in MWSN. Single-hop communication in MWSN, on the other hand, is typically relatively energy-intensive. The nodes located nearer to the sink are considerably perform well than the rest of the nodes in MWSN because of the multi-hop connection, resulting in a shorter lifespan for the MWSN. In this paper, Hybrid Optimization-based Efficient Routing Protocol (HOERP) is proposed to minimize the energy consumption in MWSN. HOERP involves grey wolf optimization and particle swarm optimization, where local search is done by grey wolf optimization and the global search optimization is done by particle swarm optimization. Utilizing the nonlinear parameters in HOERP assist in identifying the optimized cum successful route leading to consume less energy. HOERP is evaluated in NS3 using the metrics standardly used in network-oriented researches. Result highlights that HOERP consumes less energy to deliver data packets than the current routing protocols.
{"title":"Hybrid Optimization-Based Efficient Routing Protocol for Energy Consumption Minimization in Mobile Wireless Sensor Network","authors":"V. Veerakumaran, A. Rajini","doi":"10.22247/ijcna/2022/215919","DOIUrl":"https://doi.org/10.22247/ijcna/2022/215919","url":null,"abstract":"– Mobile Wireless Sensor Network (MWSN) is a dispersed network having autonomous sensor nodes which monitors physical occurrences or environmental variables in real-time. Most MWSNs have limited energy, so energy efficiency is critical. A node’s data will be routed by one of two standard methods: single-long-hop or short-multi-hop routing paths. The quantity of energy required to deliver a packet grows directly proportional to the packet’s travel distance in MWSN. Single-hop communication in MWSN, on the other hand, is typically relatively energy-intensive. The nodes located nearer to the sink are considerably perform well than the rest of the nodes in MWSN because of the multi-hop connection, resulting in a shorter lifespan for the MWSN. In this paper, Hybrid Optimization-based Efficient Routing Protocol (HOERP) is proposed to minimize the energy consumption in MWSN. HOERP involves grey wolf optimization and particle swarm optimization, where local search is done by grey wolf optimization and the global search optimization is done by particle swarm optimization. Utilizing the nonlinear parameters in HOERP assist in identifying the optimized cum successful route leading to consume less energy. HOERP is evaluated in NS3 using the metrics standardly used in network-oriented researches. Result highlights that HOERP consumes less energy to deliver data packets than the current routing protocols.","PeriodicalId":36485,"journal":{"name":"International Journal of Computer Networks and Applications","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49245642","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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