Pub Date : 2023-05-09DOI: 10.1142/s0219265923500044
Gunaganti Sravanthi, Nageswara Rao Moparthi
The Internet of Things (IoT) creates a large number of datasets, and these are handled in cloud data centers. IoT services are more delayed when data is sent over longer distances to the cloud. Node deployment is used to improve the performance of the multi-tier IoT-Fog environment by finding minimum distance with low Latency. Several methods have been discussed previously to improve the node deployment strategies but they do not provide good results. To overcome these issues, an Efficient and Multi-Tier Node Deployment Strategy using Variable Tangent Search Optimization Algorithm (VTSOA) is proposed in an IoT-Fog Environment. This Multi-Tier Node Deployment Strategy consists of several layers: IoT device layer, Fog layer, and cloud layer. The IoT device layer collects the data from external devices and is transmitted to the Fog layer. The fog layer contains several nodes. Hence, it increases the Latency of sending the data to the cloud. Therefore, VTSOA-based node deployment is done in the fog layer which finds the minimum distance nodes for effective communication. In this, the proposed approach is implemented in MATLAB. After that, the performance of this method is linked to various optimization algorithms.
{"title":"An Efficient and Multi-Tier Node Deployment Strategy Using Variable Tangent Search in an IOT-Fog Environment","authors":"Gunaganti Sravanthi, Nageswara Rao Moparthi","doi":"10.1142/s0219265923500044","DOIUrl":"https://doi.org/10.1142/s0219265923500044","url":null,"abstract":"The Internet of Things (IoT) creates a large number of datasets, and these are handled in cloud data centers. IoT services are more delayed when data is sent over longer distances to the cloud. Node deployment is used to improve the performance of the multi-tier IoT-Fog environment by finding minimum distance with low Latency. Several methods have been discussed previously to improve the node deployment strategies but they do not provide good results. To overcome these issues, an Efficient and Multi-Tier Node Deployment Strategy using Variable Tangent Search Optimization Algorithm (VTSOA) is proposed in an IoT-Fog Environment. This Multi-Tier Node Deployment Strategy consists of several layers: IoT device layer, Fog layer, and cloud layer. The IoT device layer collects the data from external devices and is transmitted to the Fog layer. The fog layer contains several nodes. Hence, it increases the Latency of sending the data to the cloud. Therefore, VTSOA-based node deployment is done in the fog layer which finds the minimum distance nodes for effective communication. In this, the proposed approach is implemented in MATLAB. After that, the performance of this method is linked to various optimization algorithms.","PeriodicalId":153590,"journal":{"name":"J. Interconnect. Networks","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123034074","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}
The future digital evolution poses challenges that need to be spectral and energy-efficient, as well as highly reliable and resilient. The non-orthogonal multiple access (NOMA) accomplishes massive connectivity, spectral efficiency, effective bandwidth utilization, and low latency. The proposed work involves the code domain NOMA scheme called Sparse Code Multiple Access (SCMA) which provides shaping gain through multi-dimensional constellation and the best performance in terms of bit error rate (BER). It achieves overloading of users through the non-orthogonal allocation of resources which enhances the spectral efficiency and serves more users. The shaping gain can be further improved by reducing the BER and enhancing the capacity of the channel through constellation shaping. This work employs a probabilistic-shaped (PS) constellation where each symbol is transmitted with different probabilities which achieves a reduction of average symbol power and forward error correction (FEC) through channel coding using polar codes which aid in energy efficiency. The output is two-dimensionally spread over Orthogonal Frequency Code Division Multiplexing (OFCDM) subcarriers to achieve a flexible transmission rate through a variable spreading factor. Computer simulations showed better BER performance under AWGN and Rayleigh channels with remarkable gain in SNR which paves the way for future applications in Fifth Generation (5G) beyond networks.
{"title":"An Enhanced Probabilistic-Shaped SCMA NOMA for Wireless Networks","authors":"Ramya Thirunavukkarasu, Ramachandran Balasubramanian","doi":"10.1142/s0219265923500032","DOIUrl":"https://doi.org/10.1142/s0219265923500032","url":null,"abstract":"The future digital evolution poses challenges that need to be spectral and energy-efficient, as well as highly reliable and resilient. The non-orthogonal multiple access (NOMA) accomplishes massive connectivity, spectral efficiency, effective bandwidth utilization, and low latency. The proposed work involves the code domain NOMA scheme called Sparse Code Multiple Access (SCMA) which provides shaping gain through multi-dimensional constellation and the best performance in terms of bit error rate (BER). It achieves overloading of users through the non-orthogonal allocation of resources which enhances the spectral efficiency and serves more users. The shaping gain can be further improved by reducing the BER and enhancing the capacity of the channel through constellation shaping. This work employs a probabilistic-shaped (PS) constellation where each symbol is transmitted with different probabilities which achieves a reduction of average symbol power and forward error correction (FEC) through channel coding using polar codes which aid in energy efficiency. The output is two-dimensionally spread over Orthogonal Frequency Code Division Multiplexing (OFCDM) subcarriers to achieve a flexible transmission rate through a variable spreading factor. Computer simulations showed better BER performance under AWGN and Rayleigh channels with remarkable gain in SNR which paves the way for future applications in Fifth Generation (5G) beyond networks.","PeriodicalId":153590,"journal":{"name":"J. Interconnect. Networks","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115269598","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 : 2023-04-21DOI: 10.1142/s0219265923500056
Shreedhar Yadawad, S. Joshi
One of the major significant problems in the existing techniques in Wireless Sensor Networks (WSNs) is Energy Efficiency (EE) because sensor nodes are battery-powered devices. The energy-efficient data transmission and routing to the sink are critical challenges because WSNs have inherent resource limitations. On the other hand, the clustering process is a crucial strategy that can rapidly increase network lifetime. As a result, WSNs require an energy-efficient routing strategy with optimum route election. These issues are overcome by using Tasmanian Fully Recurrent Deep Learning Network with Pelican Variable Marine Predators Algorithm for Data Aggregation and Cluster-Based Routing in WSN (TFR-DLN-PMPOA-WSN) which is proposed to expand the network lifetime. Initially, Tasmanian Fully Recurrent Deep Learning Network (TFR-DLN) is proposed to elect the Optimal Cluster Head (OCH). After OCH selection, the three parameters, trust, connectivity, and QoS, are optimized for secure routing with the help of the Pelican Variable Marine Predators Optimization Algorithm (PMPOA). Finally, the proposed method finds the minimum distance among the nodes and selects the best routing to increase energy efficiency. The proposed approach will be activated in MATLAB. The efficacy of the TFR-DLN- PMPOA-WSN approach is assessed in terms of several performances. It achieves higher throughput, higher packet delivery ratio, higher detection rate, lower delay, lower energy utilization, and higher network lifespan than the existing methods.
{"title":"Energy-Efficient Data Aggregation and Cluster-Based Routing in Wireless Sensor Networks Using Tasmanian Fully Recurrent Deep Learning Network with Pelican Variable Marine Predators Algorithm","authors":"Shreedhar Yadawad, S. Joshi","doi":"10.1142/s0219265923500056","DOIUrl":"https://doi.org/10.1142/s0219265923500056","url":null,"abstract":"One of the major significant problems in the existing techniques in Wireless Sensor Networks (WSNs) is Energy Efficiency (EE) because sensor nodes are battery-powered devices. The energy-efficient data transmission and routing to the sink are critical challenges because WSNs have inherent resource limitations. On the other hand, the clustering process is a crucial strategy that can rapidly increase network lifetime. As a result, WSNs require an energy-efficient routing strategy with optimum route election. These issues are overcome by using Tasmanian Fully Recurrent Deep Learning Network with Pelican Variable Marine Predators Algorithm for Data Aggregation and Cluster-Based Routing in WSN (TFR-DLN-PMPOA-WSN) which is proposed to expand the network lifetime. Initially, Tasmanian Fully Recurrent Deep Learning Network (TFR-DLN) is proposed to elect the Optimal Cluster Head (OCH). After OCH selection, the three parameters, trust, connectivity, and QoS, are optimized for secure routing with the help of the Pelican Variable Marine Predators Optimization Algorithm (PMPOA). Finally, the proposed method finds the minimum distance among the nodes and selects the best routing to increase energy efficiency. The proposed approach will be activated in MATLAB. The efficacy of the TFR-DLN- PMPOA-WSN approach is assessed in terms of several performances. It achieves higher throughput, higher packet delivery ratio, higher detection rate, lower delay, lower energy utilization, and higher network lifespan than the existing methods.","PeriodicalId":153590,"journal":{"name":"J. Interconnect. Networks","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130330973","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 : 2023-04-17DOI: 10.1142/s0219265923500020
H. Xu, Jinqiu Zhou
In this note, we prove the equivalence of edge connectivity, essential edge connectivity and cyclic edge connectivity in an [Formula: see text]-regular graph, where [Formula: see text].
{"title":"A Note on Connectivity of Regular Graphs","authors":"H. Xu, Jinqiu Zhou","doi":"10.1142/s0219265923500020","DOIUrl":"https://doi.org/10.1142/s0219265923500020","url":null,"abstract":"In this note, we prove the equivalence of edge connectivity, essential edge connectivity and cyclic edge connectivity in an [Formula: see text]-regular graph, where [Formula: see text].","PeriodicalId":153590,"journal":{"name":"J. Interconnect. Networks","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122887548","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 : 2023-02-08DOI: 10.1142/s0219265922500098
Sanjay Sudhir Kulkarni, A. Bavarva
Handover modifies the user equipment using mobility in which base station provides the best one. The repeated handovers may corrupt mobility reliability due to high signaling load and therefore, network capability enhancement is affected. Here, a network management system in a network is difficult one owing to the rising number of complexity issues and base stations. In this paper, Crow Sun Flower Optimization (CSFO)-based handover method is developed for enabling efficient handover in Fifth Generation (5G) network. This handover method mainly consists of four parts, such as User Preference (UP) section, Network Quality of Service (NQ) module, power section, and Decision System (DS) module. The Quality of service (QoS) is controlled by UP section and NQ module, whereas the power module is concentrated on power. Thus, the handover is decided based on three segments and DS module is used to enable the network. The DS module is effectively decided whether to offer handover in 5G network or not. Moreover, the decision is optimally selected based on an optimization technique, named as CSFO algorithm. The developed CSFO technique is newly designed by integrating Crow Search Algorithm (CSA) and Sun Flower Optimization (SFO) technique. Additionally, three performance indicators, including received power, throughput, and user-served ratio, are used to assess how well the created CSFO-based handover model performs. High received power, throughput, and user served ratio of [Formula: see text][Formula: see text]dBm, [Formula: see text][Formula: see text]kbps and 0.071, respectively, are achieved by the developed handover strategy.
切换是一种利用移动性对用户设备进行修改的方法，其中基站提供了最好的移动性。由于信令负荷高，反复切换会破坏移动可靠性，影响网络能力的增强。在这里，由于复杂性问题和基站数量的增加，网络中的网络管理系统是一个困难的系统。为了实现5G网络的高效切换，本文提出了一种基于乌鸦太阳花优化(CSFO)的切换方法。该切换方法主要由用户偏好(UP)模块、网络服务质量(NQ)模块、电源模块和决策系统(DS)模块四部分组成。QoS (Quality of service)由UP段和NQ模块控制，而电源模块集中在电源上。因此，根据三段决定切换，并使用DS模块使能网络。在5G网络中，DS模块可以有效地决定是否提供切换。此外，基于一种优化技术，即CSFO算法，对决策进行最优选择。所开发的CSFO技术是将乌鸦搜索算法(CSA)和太阳花优化(SFO)技术相结合而设计的。此外，使用三个性能指标(包括接收功率、吞吐量和用户服务比率)来评估所创建的基于csfo的切换模型的执行情况。通过所设计的切换策略，实现了[公式:见文][公式:见文]dBm、[公式:见文][公式:见文]kbps和0.071的高接收功率、吞吐量和用户服务比。
{"title":"Crow Sun Flower Optimization-Based Handover Modules in 5G Networks","authors":"Sanjay Sudhir Kulkarni, A. Bavarva","doi":"10.1142/s0219265922500098","DOIUrl":"https://doi.org/10.1142/s0219265922500098","url":null,"abstract":"Handover modifies the user equipment using mobility in which base station provides the best one. The repeated handovers may corrupt mobility reliability due to high signaling load and therefore, network capability enhancement is affected. Here, a network management system in a network is difficult one owing to the rising number of complexity issues and base stations. In this paper, Crow Sun Flower Optimization (CSFO)-based handover method is developed for enabling efficient handover in Fifth Generation (5G) network. This handover method mainly consists of four parts, such as User Preference (UP) section, Network Quality of Service (NQ) module, power section, and Decision System (DS) module. The Quality of service (QoS) is controlled by UP section and NQ module, whereas the power module is concentrated on power. Thus, the handover is decided based on three segments and DS module is used to enable the network. The DS module is effectively decided whether to offer handover in 5G network or not. Moreover, the decision is optimally selected based on an optimization technique, named as CSFO algorithm. The developed CSFO technique is newly designed by integrating Crow Search Algorithm (CSA) and Sun Flower Optimization (SFO) technique. Additionally, three performance indicators, including received power, throughput, and user-served ratio, are used to assess how well the created CSFO-based handover model performs. High received power, throughput, and user served ratio of [Formula: see text][Formula: see text]dBm, [Formula: see text][Formula: see text]kbps and 0.071, respectively, are achieved by the developed handover strategy.","PeriodicalId":153590,"journal":{"name":"J. Interconnect. Networks","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127263334","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 : 2023-02-08DOI: 10.1142/s0219265923500019
Lulu Yang, Xiaohui Hua
Let [Formula: see text] and [Formula: see text] be two connected subgraphs of an interconnection network [Formula: see text]. If the removal of any minimum [Formula: see text]-structure-cut (respectively, minimum [Formula: see text]-substructure-cut) splits [Formula: see text] into exactly two components, one of which is isomorphic to [Formula: see text], then [Formula: see text] is said to be hyper[Formula: see text]-connected (respectively, hyper sub-[Formula: see text]-connected). The hierarchical star network [Formula: see text] is one of alternative interconnection networks for multiprocessor systems. Let [Formula: see text], [Formula: see text] and [Formula: see text]. In this paper, we prove that (i) both the [Formula: see text]-structure connectivity and the sub-[Formula: see text]-structure connectivity of [Formula: see text] are [Formula: see text]; and (ii) both the [Formula: see text]-structure connectivity and the sub-[Formula: see text]-structure connectivity of [Formula: see text] are [Formula: see text]; and (iii) [Formula: see text] is hyper [Formula: see text]-connected and hyper sub-[Formula: see text]-connected, where [Formula: see text] is the complete graph with one vertex and [Formula: see text] is a star with [Formula: see text] vertices.
{"title":"Hyper Star Fault Tolerance of Hierarchical Star Networks","authors":"Lulu Yang, Xiaohui Hua","doi":"10.1142/s0219265923500019","DOIUrl":"https://doi.org/10.1142/s0219265923500019","url":null,"abstract":"Let [Formula: see text] and [Formula: see text] be two connected subgraphs of an interconnection network [Formula: see text]. If the removal of any minimum [Formula: see text]-structure-cut (respectively, minimum [Formula: see text]-substructure-cut) splits [Formula: see text] into exactly two components, one of which is isomorphic to [Formula: see text], then [Formula: see text] is said to be hyper[Formula: see text]-connected (respectively, hyper sub-[Formula: see text]-connected). The hierarchical star network [Formula: see text] is one of alternative interconnection networks for multiprocessor systems. Let [Formula: see text], [Formula: see text] and [Formula: see text]. In this paper, we prove that (i) both the [Formula: see text]-structure connectivity and the sub-[Formula: see text]-structure connectivity of [Formula: see text] are [Formula: see text]; and (ii) both the [Formula: see text]-structure connectivity and the sub-[Formula: see text]-structure connectivity of [Formula: see text] are [Formula: see text]; and (iii) [Formula: see text] is hyper [Formula: see text]-connected and hyper sub-[Formula: see text]-connected, where [Formula: see text] is the complete graph with one vertex and [Formula: see text] is a star with [Formula: see text] vertices.","PeriodicalId":153590,"journal":{"name":"J. Interconnect. Networks","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123009220","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 : 2023-02-06DOI: 10.1142/s0219265922500104
Merlin Thomas Ellumkalayil, Libin Chacko Samuel, S. Naduvath
Let [Formula: see text] be the minimum number of distinct resources or equipment such as channels, transmitters, antennas and surveillance equipment required for a system’s stability. These resources are placed on a system. The system is stable only if the resources of the same type are placed far away from each other or, in other words, they are not adjacent to each other. Let these distinct resources represent different colors assigned on the vertices of a graph [Formula: see text]. Suppose the available resources, denoted by [Formula: see text], are less than [Formula: see text]. In that case, placing [Formula: see text] resources on the vertices of [Formula: see text] will make at least one equipment of the same type adjacent to each other, which thereby make the system unstable. In [Formula: see text]-coloring, the adjacency between the resources of a single resource type is tolerated. The remaining resources are placed on the vertices so that no two resources of the same type are adjacent to each other. In this paper, we discuss some general results on the [Formula: see text]-coloring and the number of bad edges obtained from the same for a graph [Formula: see text]. Also, we determine the minimum number of bad edges obtained from [Formula: see text]-coloring of few derived graph of graphs. The number of bad edges which result from a [Formula: see text]-coloring of [Formula: see text] is denoted by [Formula: see text].
{"title":"Some New Results on δ(k)-Coloring of Graphs","authors":"Merlin Thomas Ellumkalayil, Libin Chacko Samuel, S. Naduvath","doi":"10.1142/s0219265922500104","DOIUrl":"https://doi.org/10.1142/s0219265922500104","url":null,"abstract":"Let [Formula: see text] be the minimum number of distinct resources or equipment such as channels, transmitters, antennas and surveillance equipment required for a system’s stability. These resources are placed on a system. The system is stable only if the resources of the same type are placed far away from each other or, in other words, they are not adjacent to each other. Let these distinct resources represent different colors assigned on the vertices of a graph [Formula: see text]. Suppose the available resources, denoted by [Formula: see text], are less than [Formula: see text]. In that case, placing [Formula: see text] resources on the vertices of [Formula: see text] will make at least one equipment of the same type adjacent to each other, which thereby make the system unstable. In [Formula: see text]-coloring, the adjacency between the resources of a single resource type is tolerated. The remaining resources are placed on the vertices so that no two resources of the same type are adjacent to each other. In this paper, we discuss some general results on the [Formula: see text]-coloring and the number of bad edges obtained from the same for a graph [Formula: see text]. Also, we determine the minimum number of bad edges obtained from [Formula: see text]-coloring of few derived graph of graphs. The number of bad edges which result from a [Formula: see text]-coloring of [Formula: see text] is denoted by [Formula: see text].","PeriodicalId":153590,"journal":{"name":"J. Interconnect. Networks","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127454027","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 : 2023-02-06DOI: 10.1142/s0219265922500050
Kavita K. Patil, T. Kumaran, A. Prasad
The wireless sensor network (WSN) assists an extensive range of sensor nodes and enables several real-time uses. Congestion on the WSN is based on high pocket traffic and low wireless communication capabilities under network topology. Highly loaded nodes will consume power quickly and increase the risk of the network going offline or breaking. Additionally, loss of packet and buffer overflows would result in an outcome of increased end-to-end delay, performance deterioration of heavily loaded nodes, and transport communication loss. In this paper, a novel congestion control system is proposed to diminish the congestion on network and to enhance the throughput of the network. Initially, cluster head (CH) selection is achieved by exhausting K-means clustering algorithm. After the selection of cluster head, an efficient approach for congestion management is designed to select adaptive path by using Adaptive packet rate reduction (APTR) algorithm. Finally, Ant colony optimization (ACO) is utilized for enhancement of wireless sensor network throughput. The objective function increases the wireless sensor network throughput by decreasing the congestion on network. The proposed system is simulated with (Network Simulator NS-2). The proposed K-means C-ACO-ICC-WSN attains higher throughput 99.56%, 95.62% and 93.33%, lower delay 4.16%, 2.12% and 3.11% and minimum congestion level 1.19%, 2.33% and 5.16% and the proposed method is likened with the existing systems as Fuzzy-enabled congestion control through cross layer protocol exploiting OABC on WSN (FC-OABC-CC-WSN), Optimized fuzzy clustering at wireless sensor networks with improved squirrel search algorithm (FLC-ISSA-CC-WSN) and novel energy-aware clustering process through lion pride optimizer (LPO) and fuzzy logic on wireless sensor networks (EAC-LPO-CC-WSN), respectively. Finally, the simulation consequences demonstrate that proposed system may be capable of minimizing that congestion level and improving the throughput of the network.
{"title":"Improved Congestion Control in Wireless Sensor Networks Using Clustering with Metaheuristic Approach","authors":"Kavita K. Patil, T. Kumaran, A. Prasad","doi":"10.1142/s0219265922500050","DOIUrl":"https://doi.org/10.1142/s0219265922500050","url":null,"abstract":"The wireless sensor network (WSN) assists an extensive range of sensor nodes and enables several real-time uses. Congestion on the WSN is based on high pocket traffic and low wireless communication capabilities under network topology. Highly loaded nodes will consume power quickly and increase the risk of the network going offline or breaking. Additionally, loss of packet and buffer overflows would result in an outcome of increased end-to-end delay, performance deterioration of heavily loaded nodes, and transport communication loss. In this paper, a novel congestion control system is proposed to diminish the congestion on network and to enhance the throughput of the network. Initially, cluster head (CH) selection is achieved by exhausting K-means clustering algorithm. After the selection of cluster head, an efficient approach for congestion management is designed to select adaptive path by using Adaptive packet rate reduction (APTR) algorithm. Finally, Ant colony optimization (ACO) is utilized for enhancement of wireless sensor network throughput. The objective function increases the wireless sensor network throughput by decreasing the congestion on network. The proposed system is simulated with (Network Simulator NS-2). The proposed K-means C-ACO-ICC-WSN attains higher throughput 99.56%, 95.62% and 93.33%, lower delay 4.16%, 2.12% and 3.11% and minimum congestion level 1.19%, 2.33% and 5.16% and the proposed method is likened with the existing systems as Fuzzy-enabled congestion control through cross layer protocol exploiting OABC on WSN (FC-OABC-CC-WSN), Optimized fuzzy clustering at wireless sensor networks with improved squirrel search algorithm (FLC-ISSA-CC-WSN) and novel energy-aware clustering process through lion pride optimizer (LPO) and fuzzy logic on wireless sensor networks (EAC-LPO-CC-WSN), respectively. Finally, the simulation consequences demonstrate that proposed system may be capable of minimizing that congestion level and improving the throughput of the network.","PeriodicalId":153590,"journal":{"name":"J. Interconnect. Networks","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121068868","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 : 2023-01-25DOI: 10.1142/s0219265922500049
J. J. Sumesh, C. P. Maheswaran
Typically, wireless sensor networks (WSNs) are used to monitor as well as detect different kinds of objects in realistic monitoring, where security remains as a major confront. Estimation of node trust is established to be an effectual way of enhancing the security, thus aiding in nodes collaboration and decision-making in wireless and wired networks. Nevertheless, conventional methods of trust management generally highlight on trust modeling and fail to notice the overhead issues. In this paper, a security aware ring cluster routing technique is introduced. The routing is undergone based on the multi-objectives including trust (security) parameters, energy, and distance. Here, the trust parameters include both the direct trust evaluation and indirect trust evaluation. Thereby, the lifetime of the network gets maximized even with secured manner. An innovative Self-Adaptive Deer Hunting Optimization (SA-DHO) is presented in this study because the optimization plays a significant role in selecting the neighbors as ring nodes. Finally, the superiority of the suggested approach is demonstrated in relation to various measures.
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Pub Date : 2023-01-20DOI: 10.1142/s0219265922500062
Yingbin Ma, Yanfeng Xue, Xiaoxue Zhang
The proper rainbow vertex connection number of [Formula: see text], denoted by [Formula: see text], is the smallest number of colors needed to properly color the vertices of [Formula: see text] so that [Formula: see text] is rainbow vertex connected. The proper strong rainbow vertex connection number of [Formula: see text], denoted by [Formula: see text], is the smallest number of colors needed to properly color the vertices of [Formula: see text] so that [Formula: see text] is strong rainbow vertex connected. These two concepts are inspired by the concept of proper (strong) rainbow connection number of graphs. In this paper, we first determine the values of [Formula: see text] and [Formula: see text] for some special graphs, such as all cubic graphs of order [Formula: see text], pencil graphs, circular ladders or Möbius ladders. Secondly, we obtain the values of [Formula: see text] and [Formula: see text] for some special graphs, such as all cubic graphs of order [Formula: see text], paths, cycles, wheels, complete multipartite graphs, pencil graphs, circular ladders and Möbius ladders. Finally, we characterize all the connected graphs [Formula: see text] with [Formula: see text] and [Formula: see text].
{"title":"Proper (Strong) Rainbow Connection and Proper (Strong) Rainbow Vertex Connection of Some Special Graphs","authors":"Yingbin Ma, Yanfeng Xue, Xiaoxue Zhang","doi":"10.1142/s0219265922500062","DOIUrl":"https://doi.org/10.1142/s0219265922500062","url":null,"abstract":"The proper rainbow vertex connection number of [Formula: see text], denoted by [Formula: see text], is the smallest number of colors needed to properly color the vertices of [Formula: see text] so that [Formula: see text] is rainbow vertex connected. The proper strong rainbow vertex connection number of [Formula: see text], denoted by [Formula: see text], is the smallest number of colors needed to properly color the vertices of [Formula: see text] so that [Formula: see text] is strong rainbow vertex connected. These two concepts are inspired by the concept of proper (strong) rainbow connection number of graphs. In this paper, we first determine the values of [Formula: see text] and [Formula: see text] for some special graphs, such as all cubic graphs of order [Formula: see text], pencil graphs, circular ladders or Möbius ladders. Secondly, we obtain the values of [Formula: see text] and [Formula: see text] for some special graphs, such as all cubic graphs of order [Formula: see text], paths, cycles, wheels, complete multipartite graphs, pencil graphs, circular ladders and Möbius ladders. Finally, we characterize all the connected graphs [Formula: see text] with [Formula: see text] and [Formula: see text].","PeriodicalId":153590,"journal":{"name":"J. Interconnect. Networks","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133914081","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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