Pub Date : 2023-09-30DOI: 10.1186/s13638-023-02290-z
I. Evelyn Ezhilarasi, J. Christopher Clement, Joseph M. Arul
Abstract Cognitive radio network is a promising technology to enhance the spectrum utilization and to resolve the spectrum scarcity issues. But the malicious users play havoc with the network during spectrum sensing and demean the network performance. It is mandatory to identify such malicious attacks and address it. There have been many traditional methods to mitigate the cognitive radio network attacks. In this paper, we have surveyed advanced attack mitigation techniques like machine learning, deep learning and blockchain. Thus, by detecting and addressing the malicious activities, the throughput and overall network performance can be improved.
{"title":"A survey on cognitive radio network attack mitigation using machine learning and blockchain","authors":"I. Evelyn Ezhilarasi, J. Christopher Clement, Joseph M. Arul","doi":"10.1186/s13638-023-02290-z","DOIUrl":"https://doi.org/10.1186/s13638-023-02290-z","url":null,"abstract":"Abstract Cognitive radio network is a promising technology to enhance the spectrum utilization and to resolve the spectrum scarcity issues. But the malicious users play havoc with the network during spectrum sensing and demean the network performance. It is mandatory to identify such malicious attacks and address it. There have been many traditional methods to mitigate the cognitive radio network attacks. In this paper, we have surveyed advanced attack mitigation techniques like machine learning, deep learning and blockchain. Thus, by detecting and addressing the malicious activities, the throughput and overall network performance can be improved.","PeriodicalId":12040,"journal":{"name":"EURASIP Journal on Wireless Communications and Networking","volume":"2013 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136279570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-28DOI: 10.1186/s13638-023-02310-y
Miaoxin Xu
Abstract Efficient utilization of network resources, particularly channel bandwidth allocation, is critical for optimizing the overall system performance and ensuring fair resource allocation among multiple distributed computing nodes. Traditional methods for channel bandwidth allocation, based on fixed allocation schemes or static heuristics, often need more adaptability to dynamic changes in the network and may not fully exploit the system’s potential. To address these limitations, we employ reinforcement learning algorithms to learn optimal channel allocation policies by intermingling with the environment and getting feedback on the outcomes of their actions. This allows devices to adapt to changing network conditions and optimize resource usage. Our proposed framework is experimentally evaluated through simulation experiments. The results demonstrate that the framework consistently achieves higher system throughput than conventional static allocation methods and state-of-the-art bandwidth allocation techniques. It also exhibits lower latency values, indicating faster data transmission and reduced communication delays. Additionally, the hybrid approach shows improved resource utilization efficiency, efficiently leveraging the strengths of both Q-learning and reinforcement learning for optimized resource allocation and management.
{"title":"A novel machine learning-based framework for channel bandwidth allocation and optimization in distributed computing environments","authors":"Miaoxin Xu","doi":"10.1186/s13638-023-02310-y","DOIUrl":"https://doi.org/10.1186/s13638-023-02310-y","url":null,"abstract":"Abstract Efficient utilization of network resources, particularly channel bandwidth allocation, is critical for optimizing the overall system performance and ensuring fair resource allocation among multiple distributed computing nodes. Traditional methods for channel bandwidth allocation, based on fixed allocation schemes or static heuristics, often need more adaptability to dynamic changes in the network and may not fully exploit the system’s potential. To address these limitations, we employ reinforcement learning algorithms to learn optimal channel allocation policies by intermingling with the environment and getting feedback on the outcomes of their actions. This allows devices to adapt to changing network conditions and optimize resource usage. Our proposed framework is experimentally evaluated through simulation experiments. The results demonstrate that the framework consistently achieves higher system throughput than conventional static allocation methods and state-of-the-art bandwidth allocation techniques. It also exhibits lower latency values, indicating faster data transmission and reduced communication delays. Additionally, the hybrid approach shows improved resource utilization efficiency, efficiently leveraging the strengths of both Q-learning and reinforcement learning for optimized resource allocation and management.","PeriodicalId":12040,"journal":{"name":"EURASIP Journal on Wireless Communications and Networking","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135386749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-25DOI: 10.1186/s13638-023-02308-6
Yonggue Han, Dongkyu Sim
Abstract We consider the deployment of a large-scale circular layout-distributed antenna system. To maximize energy efficiency, we define the optimization problem with the approximated analysis and find the number of deployed antennas as a closed-form solution. In simulation results, we verify that the analysis based on approximation is accurate and the closed-form solution can achieve near-optimal energy efficiency without an exhaustive search method.
{"title":"The optimization of the number of deployed antennas in large-scale CL-DAS for energy efficiency","authors":"Yonggue Han, Dongkyu Sim","doi":"10.1186/s13638-023-02308-6","DOIUrl":"https://doi.org/10.1186/s13638-023-02308-6","url":null,"abstract":"Abstract We consider the deployment of a large-scale circular layout-distributed antenna system. To maximize energy efficiency, we define the optimization problem with the approximated analysis and find the number of deployed antennas as a closed-form solution. In simulation results, we verify that the analysis based on approximation is accurate and the closed-form solution can achieve near-optimal energy efficiency without an exhaustive search method.","PeriodicalId":12040,"journal":{"name":"EURASIP Journal on Wireless Communications and Networking","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135816918","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-19DOI: 10.1186/s13638-023-02301-z
Amr M. Mahfouz, Ahmed S. Ismail, Wageda I. El Sobky, Hany Nasry
Abstract Wireless ad hoc sensor networks have recently emerged as a premier research topic. They have great long-term economic potential and ability to transform our lives and pose many new system building challenges. Sensor networks also pose a number of new conceptual and optimization problems. Most of researches in wireless sensor networks are focused in obtaining better target coverage in order to reduce energy and cost of the network. The problem of planar target analysis is one of the crucial problems that should be considered while studying coverage problem of sensor networks. By combining computational geometry and graph theoretic techniques, specifically the Voronoi diagram and graph search algorithms, this paper introduces a novel sensor network coverage model that deals with plane target problem based on Clifford algebra which is a powerful tool that is coordinate free. Also, the calculations of the node coverage rate for the plane target in the sensor network using Clifford algebra are presented. Then, the maximum clearance path (worst-case coverage) of the sensor network for a plane target is proposed. The optimality and reliability of the proposed algorithm have been proved using simulation. Also, a comparison between the breach weight of the point target and the plane target is provided.
{"title":"A novel model for representing a plane target and finding the worst-case coverage in wireless sensor network based on Clifford algebra","authors":"Amr M. Mahfouz, Ahmed S. Ismail, Wageda I. El Sobky, Hany Nasry","doi":"10.1186/s13638-023-02301-z","DOIUrl":"https://doi.org/10.1186/s13638-023-02301-z","url":null,"abstract":"Abstract Wireless ad hoc sensor networks have recently emerged as a premier research topic. They have great long-term economic potential and ability to transform our lives and pose many new system building challenges. Sensor networks also pose a number of new conceptual and optimization problems. Most of researches in wireless sensor networks are focused in obtaining better target coverage in order to reduce energy and cost of the network. The problem of planar target analysis is one of the crucial problems that should be considered while studying coverage problem of sensor networks. By combining computational geometry and graph theoretic techniques, specifically the Voronoi diagram and graph search algorithms, this paper introduces a novel sensor network coverage model that deals with plane target problem based on Clifford algebra which is a powerful tool that is coordinate free. Also, the calculations of the node coverage rate for the plane target in the sensor network using Clifford algebra are presented. Then, the maximum clearance path (worst-case coverage) of the sensor network for a plane target is proposed. The optimality and reliability of the proposed algorithm have been proved using simulation. Also, a comparison between the breach weight of the point target and the plane target is provided.","PeriodicalId":12040,"journal":{"name":"EURASIP Journal on Wireless Communications and Networking","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135014906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-18DOI: 10.1186/s13638-023-02305-9
Hyunjin You, Doochan Ko, Daniel Kim, Richard Wong, Inwhee Joe
Abstract With online work environments and other distributed computing systems—such as cloud technologies or Internet of Things systems—becoming increasingly popular today due to the COVID-19 pandemic and general technological advances, the question of how to keep them secure has also become a pertinent concern. With this increased dependence on online systems for companies, cyberattacks have also been on the rise. To protect terminal devices, many companies have resorted to implementing a single boundary-defense model. This method has yielded positive results in securing the network from external threats, but it does not effectively protect network from internal security threats. With the vulnerabilities in the internal network security in mind, a dynamic access control method used with a zero-trust software-defined perimeter security model could be a viable solution. This study proposes a dynamic access control method using an engine with a new reward and penalty point-based system (RP Engine) and a dynamic task engine (DT Engine) for a zero-trust SDP security model.
{"title":"Dynamic access control method for SDP-based network environments","authors":"Hyunjin You, Doochan Ko, Daniel Kim, Richard Wong, Inwhee Joe","doi":"10.1186/s13638-023-02305-9","DOIUrl":"https://doi.org/10.1186/s13638-023-02305-9","url":null,"abstract":"Abstract With online work environments and other distributed computing systems—such as cloud technologies or Internet of Things systems—becoming increasingly popular today due to the COVID-19 pandemic and general technological advances, the question of how to keep them secure has also become a pertinent concern. With this increased dependence on online systems for companies, cyberattacks have also been on the rise. To protect terminal devices, many companies have resorted to implementing a single boundary-defense model. This method has yielded positive results in securing the network from external threats, but it does not effectively protect network from internal security threats. With the vulnerabilities in the internal network security in mind, a dynamic access control method used with a zero-trust software-defined perimeter security model could be a viable solution. This study proposes a dynamic access control method using an engine with a new reward and penalty point-based system (RP Engine) and a dynamic task engine (DT Engine) for a zero-trust SDP security model.","PeriodicalId":12040,"journal":{"name":"EURASIP Journal on Wireless Communications and Networking","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135154814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-14DOI: 10.1186/s13638-023-02302-y
Mostafa M. Abdelhakam, Mahmoud M. Elmesalawy, Ibrahim I. Ibrahim, Samir G. Sayed
Abstract In this paper, the flexibility of unmanned aerial vehicles (UAVs), as well as the benefits of coordinated multi-point (CoMP) transmission, are utilized for mitigating the interference in cellular networks. Specifically, the joint problem of CoMP clusters and UAVs’ trajectories is addressed for downlink transmission in a UAV-assisted cellular system. The problem is presented as a non-convex optimization problem that aims to maximize the sum rate of the ground users by taking into account the clustering, UAV mobility and backhaul capacity constraints. Since the formulated problem is known to be NP-hard, we partition it into two sub-problems. Particularly, by using coalitional game theory, the CoMP clusters are obtained with a given UAVs’ trajectories. Then, UAVs’ trajectories are optimized with given CoMP clusters using successive convex approximation technique. Based on the block coordinate descent method, the two sub-problems are solved alternatively until convergence. Numerical results are conducted and demonstrated the effectiveness of the proposed algorithm.
{"title":"Joint trajectory and CoMP clustering optimization in UAV-assisted cellular systems: a coalition formation game approach","authors":"Mostafa M. Abdelhakam, Mahmoud M. Elmesalawy, Ibrahim I. Ibrahim, Samir G. Sayed","doi":"10.1186/s13638-023-02302-y","DOIUrl":"https://doi.org/10.1186/s13638-023-02302-y","url":null,"abstract":"Abstract In this paper, the flexibility of unmanned aerial vehicles (UAVs), as well as the benefits of coordinated multi-point (CoMP) transmission, are utilized for mitigating the interference in cellular networks. Specifically, the joint problem of CoMP clusters and UAVs’ trajectories is addressed for downlink transmission in a UAV-assisted cellular system. The problem is presented as a non-convex optimization problem that aims to maximize the sum rate of the ground users by taking into account the clustering, UAV mobility and backhaul capacity constraints. Since the formulated problem is known to be NP-hard, we partition it into two sub-problems. Particularly, by using coalitional game theory, the CoMP clusters are obtained with a given UAVs’ trajectories. Then, UAVs’ trajectories are optimized with given CoMP clusters using successive convex approximation technique. Based on the block coordinate descent method, the two sub-problems are solved alternatively until convergence. Numerical results are conducted and demonstrated the effectiveness of the proposed algorithm.","PeriodicalId":12040,"journal":{"name":"EURASIP Journal on Wireless Communications and Networking","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134913959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-13DOI: 10.1186/s13638-023-02307-7
Yu Du, Yijun Guo, Jianjun Hao, Hao Zhu
Abstract In this paper, we concentrate on a non-orthogonal multiple access (NOMA)-enabled UAV data collection network for Internet of Things devices (IoTDs), where a unmanned aerial vehicle (UAV) is deployed as an aerial base station. During its flight period, the UAV can collect data from IoTDs and take advantage of the simultaneous wireless information and power transfer technology to charge the batteries of IoTDs. With the aid of NOMA, spectrum efficiency has been improved. We aim to prolong the lifetime of the IoT network, via jointly optimizing the UAV trajectory, the time allocation for information communication and wireless power transfer, the IoTDs’ transmit power, as well as the IoTDs’ group scheduling for NOMA. Then, we use the block coordinate decent and successive convex approximation techniques to tackle the non-convexity of the formulated problem. Numerical results show that the proposed solution increases the residual energy of the IoTDs, thus prolonging the lifetime of the network.
{"title":"Residual energy maximization for NOMA-enabled UAV-assisted data collection network: trajectory optimization and resource allocation","authors":"Yu Du, Yijun Guo, Jianjun Hao, Hao Zhu","doi":"10.1186/s13638-023-02307-7","DOIUrl":"https://doi.org/10.1186/s13638-023-02307-7","url":null,"abstract":"Abstract In this paper, we concentrate on a non-orthogonal multiple access (NOMA)-enabled UAV data collection network for Internet of Things devices (IoTDs), where a unmanned aerial vehicle (UAV) is deployed as an aerial base station. During its flight period, the UAV can collect data from IoTDs and take advantage of the simultaneous wireless information and power transfer technology to charge the batteries of IoTDs. With the aid of NOMA, spectrum efficiency has been improved. We aim to prolong the lifetime of the IoT network, via jointly optimizing the UAV trajectory, the time allocation for information communication and wireless power transfer, the IoTDs’ transmit power, as well as the IoTDs’ group scheduling for NOMA. Then, we use the block coordinate decent and successive convex approximation techniques to tackle the non-convexity of the formulated problem. Numerical results show that the proposed solution increases the residual energy of the IoTDs, thus prolonging the lifetime of the network.","PeriodicalId":12040,"journal":{"name":"EURASIP Journal on Wireless Communications and Networking","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135734715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-13DOI: 10.1186/s13638-023-02304-w
Lili Guo, Shibing Zhang, Xiaodong Ji, Senyi Shi
Abstract This paper investigates an optimization problem corresponding to energy efficiency maximization of an unmanned aerial vehicle (UAV)-enabled relaying system, where a fixed-wing UAV acts as an amplify-and-forward mobile relay to assist data transmission between a source node and a destination node. On the premise of satisfying the speed and acceleration constraints of the UAV, the energy efficiency (EE) of the relaying system is maximized by jointly optimizing the UAV’s trajectory and the individual transmit power levels of the source and the UAV relay. The initial joint optimization problem is non-convex and cannot be solved directly. Therefore, the joint optimization problem is decomposed into two sub-problems which are solved by applying the successive convex approximation technique and the Dinkelbach’s algorithm. On this basis, an efficient iterative algorithm is proposed to tackle the joint optimization problem through the block coordinate descent technique. Simulation results demonstrated that by conducting the proposed algorithm, the flight trajectory of the UAV and the individual transmit power levels of the nodes can be flexibly adjusted according to the system conditions, and the proposed algorithm contributes to the higher EE compared with the benchmark schemes.
{"title":"Energy efficiency maximization for UAV-enabled amplify-and-forward relaying via joint power and trajectory optimization","authors":"Lili Guo, Shibing Zhang, Xiaodong Ji, Senyi Shi","doi":"10.1186/s13638-023-02304-w","DOIUrl":"https://doi.org/10.1186/s13638-023-02304-w","url":null,"abstract":"Abstract This paper investigates an optimization problem corresponding to energy efficiency maximization of an unmanned aerial vehicle (UAV)-enabled relaying system, where a fixed-wing UAV acts as an amplify-and-forward mobile relay to assist data transmission between a source node and a destination node. On the premise of satisfying the speed and acceleration constraints of the UAV, the energy efficiency (EE) of the relaying system is maximized by jointly optimizing the UAV’s trajectory and the individual transmit power levels of the source and the UAV relay. The initial joint optimization problem is non-convex and cannot be solved directly. Therefore, the joint optimization problem is decomposed into two sub-problems which are solved by applying the successive convex approximation technique and the Dinkelbach’s algorithm. On this basis, an efficient iterative algorithm is proposed to tackle the joint optimization problem through the block coordinate descent technique. Simulation results demonstrated that by conducting the proposed algorithm, the flight trajectory of the UAV and the individual transmit power levels of the nodes can be flexibly adjusted according to the system conditions, and the proposed algorithm contributes to the higher EE compared with the benchmark schemes.","PeriodicalId":12040,"journal":{"name":"EURASIP Journal on Wireless Communications and Networking","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135741358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-05DOI: 10.1186/s13638-023-02296-7
Samaneh Bidabadi, Messaoud Ahmed Ouameur, Miloud Bagaa, Daniel Massicotte
Abstract This paper focuses on energy-efficient resource allocation in reconfigurable intelligent surface (RIS)-assisted multiple-input-single-output (MISO) communication systems. Specifically, it revisits the solution to the energy efficiency (EE) problem using the alternating optimization (AO) approach. In each AO iteration, the RIS phase optimization is achieved using the gradient descent method, which unfortunately does not guarantee convergence. To overcome this limitation, we propose two alternatives: the Wolfe-based gradient-descent (GAW) EE maximization Algorithm and the trust region (TR)-based EE maximization algorithm. Additionally, we use Dinkelbach’s algorithm to obtain the optimal transmit power allocation. Our results demonstrate that the proposed methods outperform the existing approach that uses sequential fractional programming (SFP) for phase optimization and the traditional relay-based method.
{"title":"Energy efficient resource allocation for re-configurable intelligent surface-assisted wireless networks","authors":"Samaneh Bidabadi, Messaoud Ahmed Ouameur, Miloud Bagaa, Daniel Massicotte","doi":"10.1186/s13638-023-02296-7","DOIUrl":"https://doi.org/10.1186/s13638-023-02296-7","url":null,"abstract":"Abstract This paper focuses on energy-efficient resource allocation in reconfigurable intelligent surface (RIS)-assisted multiple-input-single-output (MISO) communication systems. Specifically, it revisits the solution to the energy efficiency (EE) problem using the alternating optimization (AO) approach. In each AO iteration, the RIS phase optimization is achieved using the gradient descent method, which unfortunately does not guarantee convergence. To overcome this limitation, we propose two alternatives: the Wolfe-based gradient-descent (GAW) EE maximization Algorithm and the trust region (TR)-based EE maximization algorithm. Additionally, we use Dinkelbach’s algorithm to obtain the optimal transmit power allocation. Our results demonstrate that the proposed methods outperform the existing approach that uses sequential fractional programming (SFP) for phase optimization and the traditional relay-based method.","PeriodicalId":12040,"journal":{"name":"EURASIP Journal on Wireless Communications and Networking","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135253957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-18DOI: 10.1186/s13638-023-02223-w
Jiang Lan, Wang Chengjun, Zhang Wei
{"title":"Retraction Note: Investigation of the evaluation system of SMEs’ industrial cluster management performance based on wireless network development","authors":"Jiang Lan, Wang Chengjun, Zhang Wei","doi":"10.1186/s13638-023-02223-w","DOIUrl":"https://doi.org/10.1186/s13638-023-02223-w","url":null,"abstract":"","PeriodicalId":12040,"journal":{"name":"EURASIP Journal on Wireless Communications and Networking","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135435644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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