International Journal of Network Management最新文献

{"title":"Thinking and exploration of the teaching mode of empirical accounting course based on the Internet of Things and deep learning","authors":"Shengyi Yang,&nbsp;Shaoying Zhu","doi":"10.1002/nem.2242","DOIUrl":"10.1002/nem.2242","url":null,"abstract":"<p>Empirical accounting is a relatively new course. It was first produced in the United States in the 1960s. After years of research and development, a relatively complete theoretical system has been formed. Empirical accounting teaching is a new content of accounting higher education in our country, which plays an important role in popularizing and improving the empirical study of accounting in our country. After investigating and analysing the empirical accounting teaching in most colleges in my country, this paper summarizes and analyzes the current status of empirical accounting teaching and discusses the optimization measures of its empirical accounting teaching mode based on the Internet of Things and deep learning. The experimental results show that this method can effectively improve students' learning efficiency and teachers' teaching satisfaction.</p>","PeriodicalId":14154,"journal":{"name":"International Journal of Network Management","volume":"34 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2023-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/nem.2242","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43731111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A blockchain-enabled security management framework for mobile edge computing","authors":"Jafar A. Alzubi,&nbsp;Omar A. Alzubi,&nbsp;Ashish Singh,&nbsp;Tareq Mahmod Alzubi","doi":"10.1002/nem.2240","DOIUrl":"10.1002/nem.2240","url":null,"abstract":"<p>Mobile edge computing (MEC) integrates mobile and edge computing technologies to provide efficient computing services with low latency. It includes several Internet of Things (IoT) and edge devices that process the user data at the network's edge. The architectural characteristic of MEC supports many internet-based services, which attract more number of users, including attackers. The safety and privacy of the MEC environment, especially user information is a significant concern. A lightweight accessing and sharing protocol is required because edge devices are resource constraints. This paper addresses this issue by proposing a blockchain-enabled security management framework for MEC environments. This approach provides another level of security and includes blockchain security features like temper resistance, immutable, transparent, traceable, and distributed ledger in the MEC environment. The framework guarantees secure data storage in the MEC environment. The contributions of this paper are twofold: (1) We propose a blockchain-enabled security management framework for MEC environments that address the security and privacy concerns, and (2) we demonstrate through simulations that the framework has high performance and is suitable for resource-constrained MEC devices. In addition, a smart contract-based access and sharing mechanism is proposed. Our research uses a combination of theoretical analysis and simulation experiments to demonstrate that the proposed framework offers high security, low latency, legitimate access, high throughput, and low operations cost.</p>","PeriodicalId":14154,"journal":{"name":"International Journal of Network Management","volume":"33 5","pages":""},"PeriodicalIF":1.5,"publicationDate":"2023-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46445927","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}

{"title":"Accelerating network softwarization in the cognitive age","authors":"Kohei Shiomoto,&nbsp;Young-Tak Kim,&nbsp;Christian Esteve Rothenberg,&nbsp;Barbara Martini,&nbsp;Eiji Oki","doi":"10.1002/nem.2241","DOIUrl":"10.1002/nem.2241","url":null,"abstract":"<p>This special issue contains extended versions of three best papers from the IEEE International Conference on Network Softwarization (NetSoft 2021, https://netsoft2021.ieee-netsoft.org/). The theme of NetSoft 2021 was “Accelerating Network Softwarization in the Cognitive Age.” The General Co-Chairs were Kohei Shiomoto, Tokyo City University, Japan and Young-Tak Kim, Yeungnam University, Korea. The TPC-Co-Chairs were Christian Esteve Rothenberg, University of Campinas, Brazil; Barbara Martini, CNIT, Italy; and Eiji Oki, Kyoto University, Japan.</p><p>The first paper, titled “RNN-EdgeQL: An Auto-Scaling and Placement Approach for SFC,” proposes an innovative prediction-based scaling and placement algorithm for service function chains (SFCs) that improves service level agreements (SLAs) and reduces operational costs. The authors use a variant of recurrent neural networks (RNNs) called gated recurrent unit (GRU) for resource demand prediction and an algorithm that applies Q-Learning on Edge computing environment (EdgeQL) to place scaled-out virtual network functions (VNFs) in appropriate locations. The proposed algorithm is tested on realistic temporal dynamic load models and achieves the lowest overall latency, lowest SLA violations, and lowest VNFs requirement compared with existing algorithms.</p><p>The second paper, titled “SRv6-based Time-Sensitive Networks (TSN) with Low Overhead Rerouting,” proposes a software-defined network (SDN)-based approach for low-overhead TSN network updates using segment routing over IPv6 (SRv6) for path control. The authors introduce the concept of TSN subgraphs to quickly reschedule flows traversing problematic areas and propose a TSN-aware routing heuristic to minimize convergence time. The proposed approach yields faster recovery and significantly reduces the number of required reconfigurations upon failures, at the expense of a small SRv6 encoding/decoding overhead.</p><p>The third paper, titled “Analysis of Network Function Sharing in Content Delivery Network-as-a-Service Slicing Scenarios,” investigates the potential efficiencies that can be achieved when sharing a virtual cache function among Internet service providers (ISPs) that are sharing a common physical infrastructure. The authors simulate the sharing of virtualized cache functions and analyze the implications of limiting the storage capacity of the caches at the edge. The paper provides insights into the potential cost savings that can be achieved by sharing network infrastructures and virtualized cache functions among ISPs.</p><p>We believe that these three papers make significant contributions and offer valuable insights into the challenges and opportunities of managing softwarized networks. We hope that this special issue will inspire further research in this area and lead to the development of more efficient and effective network management solutions.</p><p>We would like to thank the authors for their excellent contributions and the reviewers for","PeriodicalId":14154,"journal":{"name":"International Journal of Network Management","volume":"33 4","pages":""},"PeriodicalIF":1.5,"publicationDate":"2023-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/nem.2241","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45535227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Issue Information","authors":"","doi":"10.1002/pd.6177","DOIUrl":"https://doi.org/10.1002/pd.6177","url":null,"abstract":"No abstract is available for this article.","PeriodicalId":14154,"journal":{"name":"International Journal of Network Management","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42673009","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}

{"title":"Joint service placement and user assignment model in multi-access edge computing networks against base-station failure","authors":"Haruto Taka,&nbsp;Fujun He,&nbsp;Eiji Oki","doi":"10.1002/nem.2233","DOIUrl":"10.1002/nem.2233","url":null,"abstract":"<p>Multi-access edge computing (MEC) enables users to exploit the resources of cloud computing at a base station (BS) in proximity to the users where an MEC server is hosted. While we have advantage of being able to communicate with low latency and small network load in MEC networks, the resources in BSs are limited. One challenge is where to provide users with services from to make efficient use of resources. Furthermore, to enhance the reliability of MEC system, the case that a BS fails needs to be considered. This paper proposes a service placement and user assignment model with preventive start-time optimization against a single BS failure in MEC networks. The proposed model preventively determines the service placement and user assignment in each BS failure pattern to minimize the worst-case penalty which is the largest penalty among all failure patterns. We formulate the proposed model as an integer linear programming problem. We prove that the considered problem is NP-hard. When the problem size becomes large, it may not be solved in a practical computation time. To solve larger size problems, we introduce two algorithms: one is the greedy algorithm with allocation upgrade and the other is with allocation upgrade and preemption. The results show that the introduced algorithms obtain solutions with smaller worst-case penalty than the benchmark in a practical time.</p>","PeriodicalId":14154,"journal":{"name":"International Journal of Network Management","volume":"33 6","pages":""},"PeriodicalIF":1.5,"publicationDate":"2023-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42045703","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}

{"title":"Placement of virtual network functions for network services","authors":"Brajesh Kumar Umrao,&nbsp;Dharmendra Kumar Yadav","doi":"10.1002/nem.2232","DOIUrl":"10.1002/nem.2232","url":null,"abstract":"<div>\u0000 \u0000 <p>Network function virtualization (NFV) is a name of technology for replacing hardware-based network functions with software programs. Virtual network function (VNF) is a software program that replaces the hardware-based network functionality. The replacement of the hardware-based network functions (middleboxes) with software programs promises the on-demand provisioning of network functions and reduces capital and operational expenses of the network. Due to this replaced network can adapt to the different network functions. Network service providers deploy various network services with different objectives, such as reducing the network's active servers and traffic latency or network operational expenses. In this article, a VNF placement problem is studied to optimize the total operating costs of the networks. To solve the VNF placement problem, we proposed an integer linear program (ILP) model, which has been implemented using CPLEX. Although an ILP-based approach gives an optimal solution, it takes a long execution time to find the solution. Due to the long execution time, the ILP-based approach is not suitable for the real-time VNF placement problem. To address this challenge, we proposed a heuristic based on dynamic programming that performs better than the existing approaches. The simulation results of the proposed solution using real-world topologies show that the heuristic approach finds a feasible solution that is only 1 to 1.34 times far from the optimal one. Moreover, experimental results show that the proposed heuristic is 15 to 423 times faster than the ILP.</p>\u0000 </div>","PeriodicalId":14154,"journal":{"name":"International Journal of Network Management","volume":"33 6","pages":""},"PeriodicalIF":1.5,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44934759","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}

{"title":"Dynamic management network system of automobile detection applying edge computing","authors":"Xianhong Cao","doi":"10.1002/nem.2231","DOIUrl":"https://doi.org/10.1002/nem.2231","url":null,"abstract":"Dynamic vehicle detection requires the transmission of large amounts of data collected by different types of sensors to the edge computing nodes. This is likely to cause network delays and congestion, affecting the computation of the edge computing nodes and thus posing serious security risks. Therefore, optimizing data transmission between vehicles and edge computing nodes is a new challenge to be addressed in the practical application of edge computing‐based vehicle dynamic detection architectures. The data requirements of VDT for vehicle detection dynamic detection in different environments are considered, the optimization objectives and constraints are analysed, and a deviation detection and greedy algorithm is proposed in this paper to address the problems of long mixed‐integer linear programme solution time and insufficient practical applications, and the performance of the algorithm is evaluated through simulation experiments conducted by simulation of urban mobility, a traffic flow simulation tool, and PreScan, a vehicle simulation test software. The results show that compared with the deviation detection algorithm, the greedy algorithm can reduce the communication overhead by 82.6%–86.2% in all cases and improve the performance by 13.6%–19.5%, which is more suitable for practical applications. The results of this paper contribute to the automation and modernization of vehicle technology management and information transfer.","PeriodicalId":14154,"journal":{"name":"International Journal of Network Management","volume":"31 4","pages":""},"PeriodicalIF":1.5,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50802380","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}

{"title":"Characterizing the Bitcoin network topology with Node-Probe","authors":"Meryam Essaid,&nbsp;Changhyun Lee,&nbsp;Hongteak Ju","doi":"10.1002/nem.2230","DOIUrl":"10.1002/nem.2230","url":null,"abstract":"<p>In blockchain networks, topology discovery is a prerequisite when investigating the network characteristics (e.g., performance and robustness), which can provide a deeper comprehension of the behavior of the nodes and topology dynamicity. In this paper, we conduct a longitudinal study on the Bitcoin topology by collecting network snapshots from 2018 to 2022 with Node-Probe, our topology discovery technique that uses recursive scanning to find all reachable nodes in the Bitcoin network. Using Node-Probe, we have collected 5-week-long snapshots (36-day-long snapshots) of the Bitcoin main network and analyzed the network properties, community structure, and topology dynamicity. We confirm that our approach achieves a precision of 99% with a recall of 98% in inferring the topology. Analytical results on community structure show that the Bitcoin network has \u0000<math>\u0000 <mo>×</mo>\u0000 <mn>4</mn></math> more communities than what should be expected from a random network. Meanwhile, analytical results on dynamicity indicate that the topology stands firmly on heavy and long-running nodes. Improving the propagation mechanism using master nodes could improve the propagation delay by proximity \u0000<math>\u0000 <mo>×</mo>\u0000 <mn>25</mn></math> compared with the Bitcoin default protocol. Considering a K-anonymity attack, any transaction from one of the autonomous systems containing only a single Bitcoin node can easily be linked to real users' IP information.</p>","PeriodicalId":14154,"journal":{"name":"International Journal of Network Management","volume":"33 6","pages":""},"PeriodicalIF":1.5,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42874730","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}

{"title":"Dynamic management network system of automobile detection applying edge computing","authors":"Xianhong Cao","doi":"10.1002/nem.2231","DOIUrl":"https://doi.org/10.1002/nem.2231","url":null,"abstract":"<p>Dynamic vehicle detection requires the transmission of large amounts of data collected by different types of sensors to the edge computing nodes. This is likely to cause network delays and congestion, affecting the computation of the edge computing nodes and thus posing serious security risks. Therefore, optimizing data transmission between vehicles and edge computing nodes is a new challenge to be addressed in the practical application of edge computing-based vehicle dynamic detection architectures. The data requirements of VDT for vehicle detection dynamic detection in different environments are considered, the optimization objectives and constraints are analysed, and a deviation detection and greedy algorithm is proposed in this paper to address the problems of long mixed-integer linear programme solution time and insufficient practical applications, and the performance of the algorithm is evaluated through simulation experiments conducted by simulation of urban mobility, a traffic flow simulation tool, and PreScan, a vehicle simulation test software. The results show that compared with the deviation detection algorithm, the greedy algorithm can reduce the communication overhead by 82.6%–86.2% in all cases and improve the performance by 13.6%–19.5%, which is more suitable for practical applications. The results of this paper contribute to the automation and modernization of vehicle technology management and information transfer.</p>","PeriodicalId":14154,"journal":{"name":"International Journal of Network Management","volume":"33 5","pages":""},"PeriodicalIF":1.5,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/nem.2231","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50142662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Detection of car parking space by using Hybrid Deep DenseNet Optimization algorithm","authors":"Vankadhara Rajyalakshmi,&nbsp;Kuruva Lakshmanna","doi":"10.1002/nem.2228","DOIUrl":"10.1002/nem.2228","url":null,"abstract":"<p>Internet of Things (IoT) and related applications have revolutionized most of our societal activities, enhancing the quality of human life. This study presents an IoT-based model that enables optimized parking space utilization. The paper implements a Hybrid Deep DenseNet Optimization (HDDNO) algorithm for predicting parking spot availability involving Machine Learning (ML) and deep learning techniques. The HDDNO-based ML model uses secondary data from the National Research Council Park (CNRPark) in Pisa, Italy. Different regression algorithms are employed to forecast parking lot availability for a given time as part of the prediction process. The DenseNet technique has generated promising results, whereas the HDDNO model yielded better accuracy. The use of five optimizers, namely, Adaptive Moment Estimation (Adam), Root Mean Squared Propagation (RMSprop), Adaptive Gradient (AdaGrad), AdaDelta, and Stochastic Gradient Descent (SGD), have played significant roles in minimizing the loss of the model. The part of Adam has enabled the HDDNO model to generate predictions with high accuracy 99.19% and low loss 0.0306%. This proposed methodology would significantly improve environmental safety and act as an initiative toward developing smart cities.</p>","PeriodicalId":14154,"journal":{"name":"International Journal of Network Management","volume":"34 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2023-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46960201","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}